OLS_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7cd2ddc6",
   "metadata": {},
   "source": [
    "# 1. Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8899b7a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#standard libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#OLS analysis\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.stats.api as sms\n",
    "from statsmodels.stats.multitest import multipletests\n",
    "from statsmodels.stats.stattools import durbin_watson\n",
    "from scipy.stats import chi2_contingency\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b947773",
   "metadata": {},
   "source": [
    "# 2. Plot colors and settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ab1d7dec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#plot colors: [grey, blue, orange, green, pink, brown, purple, yellow, red]\n",
    "light = ['#8c8c8c', '#88bde6', '#fbb258', '#90cd97', '#f6aac8', '#bfa454', '#bc99c7', '#eddd46', '#f07d6e']\n",
    "medium = ['#4d4d4d', '#5da6da', '#faa43a', '#60bd68', '#f17cb1', '#b2912f', '#b276b2', '#dece3f', '#f15954']\n",
    "dark_bright = ['#000000', '#265dab', '#df5c24', '#059749', '#e5126d', '#9d732a', '#7a3a96', '#c7b52e', '#cb2026']\n",
    "\n",
    "#grid/rule lines: light grey\n",
    "grid = ['#e0e0e0']\n",
    "\n",
    "#plot parameters\n",
    "plt.rcParams[\"axes.spines.right\"] = False\n",
    "plt.rcParams[\"axes.spines.top\"] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2be963b9",
   "metadata": {},
   "source": [
    "# 3. Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dcef216f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#CSVs from data_cleaning.py\n",
    "df_modeling_drop_first = pd.read_csv('data_cleaning/df_modeling_drop_first.csv')\n",
    "dropped_columns = pd.read_csv('data_cleaning/dropped_columns.csv')\n",
    "\n",
    "#df from EDA for one testing linear regression assumption\n",
    "df_1 = pd.read_csv('data_cleaning/df_title_loc_comp_salary.csv')\n",
    "df_1 = df_1.drop('Unnamed: 0', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "31d1c580",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1287 entries, 0 to 1286\n",
      "Columns: 988 entries, Unnamed: 0 to Levels_Unknown\n",
      "dtypes: float64(363), int64(625)\n",
      "memory usage: 9.7 MB\n"
     ]
    }
   ],
   "source": [
    "df_modeling_drop_first.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "96b8707c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Analysis skills</th>\n",
       "      <th>Communication skills</th>\n",
       "      <th>Research</th>\n",
       "      <th>R</th>\n",
       "      <th>Machine learning</th>\n",
       "      <th>Bachelor's degree</th>\n",
       "      <th>Master's degree</th>\n",
       "      <th>Doctoral degree</th>\n",
       "      <th>...</th>\n",
       "      <th>Location_West Hollywood, CA</th>\n",
       "      <th>Location_West Sacramento, CA</th>\n",
       "      <th>Location_Westlake Village, CA</th>\n",
       "      <th>Location_Woodland Hills, CA</th>\n",
       "      <th>Levels_Jr.</th>\n",
       "      <th>Levels_Lead</th>\n",
       "      <th>Levels_Principal</th>\n",
       "      <th>Levels_Sr.</th>\n",
       "      <th>Levels_Staff</th>\n",
       "      <th>Levels_Unknown</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>150000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>150000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 988 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    Salary  Analysis skills  Communication skills  Research    R  \\\n",
       "0           0  110000.0              1.0                   1.0       1.0  1.0   \n",
       "1           1  120000.0              0.0                   0.0       0.0  1.0   \n",
       "2           2  150000.0              0.0                   0.0       0.0  0.0   \n",
       "3           3  150000.0              0.0                   1.0       0.0  1.0   \n",
       "4           4  130000.0              0.0                   0.0       0.0  0.0   \n",
       "\n",
       "   Machine learning  Bachelor's degree  Master's degree  Doctoral degree  ...  \\\n",
       "0               1.0                1.0              1.0              1.0  ...   \n",
       "1               0.0                1.0              1.0              0.0  ...   \n",
       "2               1.0                1.0              1.0              1.0  ...   \n",
       "3               0.0                0.0              1.0              0.0  ...   \n",
       "4               0.0                0.0              0.0              1.0  ...   \n",
       "\n",
       "   Location_West Hollywood, CA  Location_West Sacramento, CA  \\\n",
       "0                            0                             0   \n",
       "1                            0                             0   \n",
       "2                            0                             0   \n",
       "3                            0                             0   \n",
       "4                            0                             0   \n",
       "\n",
       "   Location_Westlake Village, CA  Location_Woodland Hills, CA  Levels_Jr.  \\\n",
       "0                              0                            0           1   \n",
       "1                              0                            0           0   \n",
       "2                              0                            0           0   \n",
       "3                              0                            0           0   \n",
       "4                              0                            0           1   \n",
       "\n",
       "   Levels_Lead  Levels_Principal  Levels_Sr.  Levels_Staff  Levels_Unknown  \n",
       "0            0                 0           0             0               0  \n",
       "1            0                 0           0             0               1  \n",
       "2            0                 0           0             1               0  \n",
       "3            0                 0           0             0               1  \n",
       "4            0                 0           0             0               0  \n",
       "\n",
       "[5 rows x 988 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_modeling_drop_first.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d74521fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Company_23andMe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Title_Applied Scientist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Levels_Distinguished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Location_Alameda, CA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                        0\n",
       "0           0          Company_23andMe\n",
       "1           1  Title_Applied Scientist\n",
       "2           2     Levels_Distinguished\n",
       "3           3     Location_Alameda, CA"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropped_columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcff9a9c",
   "metadata": {},
   "source": [
    "# 4. Data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c3fb8dbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_modeling_drop_first = df_modeling_drop_first.drop('Unnamed: 0', axis=1)\n",
    "dropped_columns = dropped_columns.drop('Unnamed: 0', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "22f91046",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df_modeling_drop_first.columns[1:]:\n",
    "    df_modeling_drop_first.loc[:,i] = df_modeling_drop_first.loc[:,i].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "628cc38a",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_drop_first = df_modeling_drop_first.copy()\n",
    "y = X_drop_first.pop('Salary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5b988b91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1287, 986)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_drop_first.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af591fdd",
   "metadata": {},
   "source": [
    "# 5. OLS analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3469cd7a",
   "metadata": {},
   "source": [
    "Ordinary least squares (OLS) regression fits a hyperplane to the data of the form:\n",
    "\n",
    "$$y = X\\beta + \\epsilon$$\n",
    "\n",
    "where $X$ is an $n \\times p$ matrix ($n$ is the number of rows and $p$ is the number of predictors), and $\\epsilon$ is the irreducible error."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1806ea20",
   "metadata": {},
   "source": [
    "The objective of OLS is to estimate the coefficients, $\\beta$, which can be used to estimate $y$. The estimated $\\beta$ is determined by minimizing the residual sum of squares:\n",
    "\n",
    "$$RSS = \\sum_i^{n}{(y_{i} - \\hat{y_{i}})^{2}} $$\n",
    "\n",
    "where $\\hat{y}$ is the estimated response, $\\hat{y} = X\\hat{\\beta}$, and $\\hat{\\beta}$ is the estimated coefficient."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13cb1576",
   "metadata": {},
   "source": [
    "With 986 predictors, using an $\\alpha$ of 0.05 will result in about 49 Type I errors. Therefore, use a multiple testing technique to determine a more conservative value to reduce the number of Type I errors (at the expense of making more Type II errors)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fe547fb8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\malex\\anaconda3\\lib\\site-packages\\statsmodels\\tsa\\tsatools.py:142: FutureWarning: In a future version of pandas all arguments of concat except for the argument 'objs' will be keyword-only\n",
      "  x = pd.concat(x[::order], 1)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>Salary</td>      <th>  R-squared:         </th> <td>   0.960</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.894</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   14.44</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 29 Dec 2021</td> <th>  Prob (F-statistic):</th> <td>1.63e-161</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>19:28:06</td>     <th>  Log-Likelihood:    </th> <td> -13127.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  1287</td>      <th>  AIC:               </th> <td>2.787e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   480</td>      <th>  BIC:               </th> <td>3.203e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>   806</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "                                  <td></td>                                    <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>                                                            <td> 1.721e+05</td> <td> 2.59e+04</td> <td>    6.650</td> <td> 0.000</td> <td> 1.21e+05</td> <td> 2.23e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Analysis skills</th>                                                  <td> 1568.1528</td> <td> 3150.382</td> <td>    0.498</td> <td> 0.619</td> <td>-4622.092</td> <td> 7758.397</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Communication skills</th>                                             <td> 1687.3015</td> <td> 4193.280</td> <td>    0.402</td> <td> 0.688</td> <td>-6552.152</td> <td> 9926.755</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Research</th>                                                         <td>-7264.7381</td> <td> 4040.328</td> <td>   -1.798</td> <td> 0.073</td> <td>-1.52e+04</td> <td>  674.177</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>R</th>                                                                <td>-1115.9204</td> <td> 2956.543</td> <td>   -0.377</td> <td> 0.706</td> <td>-6925.286</td> <td> 4693.445</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Machine learning</th>                                                 <td>-1701.4333</td> <td> 2942.585</td> <td>   -0.578</td> <td> 0.563</td> <td>-7483.372</td> <td> 4080.506</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bachelor's degree</th>                                                <td>-4203.0410</td> <td> 2530.474</td> <td>   -1.661</td> <td> 0.097</td> <td>-9175.217</td> <td>  769.135</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Master's degree</th>                                                  <td> 5423.6759</td> <td> 2445.846</td> <td>    2.218</td> <td> 0.027</td> <td>  617.788</td> <td> 1.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Doctoral degree</th>                                                  <td>-1.154e+04</td> <td> 6766.282</td> <td>   -1.706</td> <td> 0.089</td> <td>-2.48e+04</td> <td> 1752.196</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Doctor of Philosophy</th>                                             <td> 2.452e+04</td> <td> 7368.802</td> <td>    3.327</td> <td> 0.001</td> <td>    1e+04</td> <td>  3.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Power BI</th>                                                         <td> 3147.2365</td> <td> 6989.562</td> <td>    0.450</td> <td> 0.653</td> <td>-1.06e+04</td> <td> 1.69e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Relational databases</th>                                             <td>-1.093e+04</td> <td> 6961.624</td> <td>   -1.570</td> <td> 0.117</td> <td>-2.46e+04</td> <td> 2750.452</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Manufacturing</th>                                                    <td> 4663.0619</td> <td> 8290.597</td> <td>    0.562</td> <td> 0.574</td> <td>-1.16e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microsoft Excel</th>                                                  <td>-8833.6073</td> <td> 6155.664</td> <td>   -1.435</td> <td> 0.152</td> <td>-2.09e+04</td> <td> 3261.770</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Molecular biology</th>                                                <td>-4.811e+04</td> <td> 2.37e+04</td> <td>   -2.032</td> <td> 0.043</td> <td>-9.46e+04</td> <td>-1585.793</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Product management</th>                                               <td>-1376.1135</td> <td> 5101.609</td> <td>   -0.270</td> <td> 0.787</td> <td>-1.14e+04</td> <td> 8648.133</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Usability</th>                                                        <td>-2.876e+04</td> <td> 1.74e+04</td> <td>   -1.656</td> <td> 0.098</td> <td>-6.29e+04</td> <td> 5356.171</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Natural language processing</th>                                      <td>-5739.1037</td> <td> 3278.657</td> <td>   -1.750</td> <td> 0.081</td> <td>-1.22e+04</td> <td>  703.191</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Python</th>                                                           <td> 2326.1333</td> <td> 2833.827</td> <td>    0.821</td> <td> 0.412</td> <td>-3242.106</td> <td> 7894.373</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SQL</th>                                                              <td>-4983.2880</td> <td> 3546.286</td> <td>   -1.405</td> <td> 0.161</td> <td> -1.2e+04</td> <td> 1984.874</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ICD coding</th>                                                       <td>-4.526e+04</td> <td> 2.06e+04</td> <td>   -2.195</td> <td> 0.029</td> <td>-8.58e+04</td> <td>-4735.104</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Statistical analysis</th>                                             <td>-2.916e+04</td> <td> 6616.826</td> <td>   -4.407</td> <td> 0.000</td> <td>-4.22e+04</td> <td>-1.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Tableau</th>                                                          <td>-2099.8870</td> <td> 3439.030</td> <td>   -0.611</td> <td> 0.542</td> <td>-8857.302</td> <td> 4657.528</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data visualization</th>                                               <td> 1840.2062</td> <td> 4179.410</td> <td>    0.440</td> <td> 0.660</td> <td>-6371.993</td> <td> 1.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Yoga</th>                                                             <td>-1.799e+04</td> <td> 1.23e+04</td> <td>   -1.465</td> <td> 0.144</td> <td>-4.21e+04</td> <td> 6142.720</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Writing skills</th>                                                   <td>-2.977e+04</td> <td> 5591.280</td> <td>   -5.325</td> <td> 0.000</td> <td>-4.08e+04</td> <td>-1.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>C++</th>                                                              <td>-1.017e+04</td> <td> 3817.192</td> <td>   -2.665</td> <td> 0.008</td> <td>-1.77e+04</td> <td>-2673.124</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Leadership</th>                                                       <td> 1.668e+04</td> <td> 4801.977</td> <td>    3.473</td> <td> 0.001</td> <td> 7240.491</td> <td> 2.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Computer vision</th>                                                  <td> 2.132e+04</td> <td> 6196.791</td> <td>    3.441</td> <td> 0.001</td> <td> 9148.361</td> <td> 3.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>C</th>                                                                <td>-4131.5882</td> <td> 4388.373</td> <td>   -0.941</td> <td> 0.347</td> <td>-1.28e+04</td> <td> 4491.208</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Haskell</th>                                                          <td>-8272.7557</td> <td> 5538.084</td> <td>   -1.494</td> <td> 0.136</td> <td>-1.92e+04</td> <td> 2609.129</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Objective-C</th>                                                      <td>-8272.7557</td> <td> 5538.084</td> <td>   -1.494</td> <td> 0.136</td> <td>-1.92e+04</td> <td> 2609.129</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Clojure</th>                                                          <td>-1.449e+04</td> <td> 1.36e+04</td> <td>   -1.063</td> <td> 0.288</td> <td>-4.13e+04</td> <td> 1.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MATLAB</th>                                                           <td>-2.115e+04</td> <td> 9501.189</td> <td>   -2.226</td> <td> 0.026</td> <td>-3.98e+04</td> <td>-2479.283</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Scala</th>                                                            <td>-6461.0809</td> <td> 5062.653</td> <td>   -1.276</td> <td> 0.202</td> <td>-1.64e+04</td> <td> 3486.620</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Hadoop</th>                                                           <td>-6249.1807</td> <td> 4820.980</td> <td>   -1.296</td> <td> 0.196</td> <td>-1.57e+04</td> <td> 3223.651</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bachelor of Science</th>                                              <td> 4197.3844</td> <td> 3347.418</td> <td>    1.254</td> <td> 0.210</td> <td>-2380.020</td> <td> 1.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Web development</th>                                                  <td>-7526.8776</td> <td> 2.64e+04</td> <td>   -0.285</td> <td> 0.776</td> <td>-5.95e+04</td> <td> 4.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CSS</th>                                                              <td> 1.196e+04</td> <td> 1.84e+04</td> <td>    0.650</td> <td> 0.516</td> <td>-2.42e+04</td> <td> 4.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PyTorch</th>                                                          <td> 1.105e+04</td> <td>  2.6e+04</td> <td>    0.425</td> <td> 0.671</td> <td>   -4e+04</td> <td> 6.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TensorFlow</th>                                                       <td>  766.5459</td> <td> 4063.853</td> <td>    0.189</td> <td> 0.850</td> <td>-7218.594</td> <td> 8751.686</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microsoft Powerpoint</th>                                             <td> 3.288e+04</td> <td> 1.23e+04</td> <td>    2.677</td> <td> 0.008</td> <td> 8750.809</td> <td>  5.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Experimental design</th>                                              <td> -2.69e+04</td> <td> 1.47e+04</td> <td>   -1.830</td> <td> 0.068</td> <td>-5.58e+04</td> <td> 1977.393</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Statistics</th>                                                       <td>-2863.1648</td> <td> 8322.545</td> <td>   -0.344</td> <td> 0.731</td> <td>-1.92e+04</td> <td> 1.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data collection</th>                                                  <td>-7007.3344</td> <td> 4517.241</td> <td>   -1.551</td> <td> 0.122</td> <td>-1.59e+04</td> <td> 1868.676</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data analytics</th>                                                   <td>-1.391e+04</td> <td> 5410.872</td> <td>   -2.570</td> <td> 0.010</td> <td>-2.45e+04</td> <td>-3275.334</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>iOS</th>                                                              <td>-1.139e+04</td> <td> 9964.307</td> <td>   -1.143</td> <td> 0.254</td> <td> -3.1e+04</td> <td> 8193.633</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cooking</th>                                                          <td> 6462.5589</td> <td> 1.01e+04</td> <td>    0.638</td> <td> 0.524</td> <td>-1.34e+04</td> <td> 2.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Attribution modeling</th>                                             <td>-2.406e+04</td> <td> 1.34e+04</td> <td>   -1.793</td> <td> 0.074</td> <td>-5.04e+04</td> <td> 2303.602</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Project management</th>                                               <td>-4428.8051</td> <td> 5817.213</td> <td>   -0.761</td> <td> 0.447</td> <td>-1.59e+04</td> <td> 7001.545</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Customer service</th>                                                 <td> 1.088e+04</td> <td> 2.01e+04</td> <td>    0.542</td> <td> 0.588</td> <td>-2.85e+04</td> <td> 5.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Statistical software</th>                                             <td>-1.249e+04</td> <td> 1.02e+04</td> <td>   -1.226</td> <td> 0.221</td> <td>-3.25e+04</td> <td> 7529.244</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Analytics</th>                                                        <td> 9139.2212</td> <td> 4075.020</td> <td>    2.243</td> <td> 0.025</td> <td> 1132.139</td> <td> 1.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Workday</th>                                                          <td> 5.236e+04</td> <td> 2.47e+04</td> <td>    2.120</td> <td> 0.034</td> <td> 3840.271</td> <td> 1.01e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SAS</th>                                                              <td>  -65.7898</td> <td> 7016.128</td> <td>   -0.009</td> <td> 0.993</td> <td>-1.39e+04</td> <td> 1.37e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Supply chain</th>                                                     <td>-3.296e+04</td> <td>  1.2e+04</td> <td>   -2.751</td> <td> 0.006</td> <td>-5.65e+04</td> <td>-9423.015</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Spark</th>                                                            <td>-2017.5278</td> <td> 3967.438</td> <td>   -0.509</td> <td> 0.611</td> <td>-9813.219</td> <td> 5778.164</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Shell Scripting</th>                                                  <td> 6.461e+04</td> <td> 1.03e+04</td> <td>    6.286</td> <td> 0.000</td> <td> 4.44e+04</td> <td> 8.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data management</th>                                                  <td>-1.288e+04</td> <td> 8472.422</td> <td>   -1.520</td> <td> 0.129</td> <td>-2.95e+04</td> <td> 3766.770</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>AI</th>                                                               <td> 1.404e+04</td> <td> 7672.075</td> <td>    1.829</td> <td> 0.068</td> <td>-1039.510</td> <td> 2.91e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Apache Hive</th>                                                      <td>-4736.4867</td> <td> 1.48e+04</td> <td>   -0.319</td> <td> 0.750</td> <td>-3.39e+04</td> <td> 2.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MapReduce</th>                                                        <td>-3903.5203</td> <td> 9502.438</td> <td>   -0.411</td> <td> 0.681</td> <td>-2.26e+04</td> <td> 1.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Go</th>                                                               <td> 1.669e+04</td> <td> 4650.256</td> <td>    3.589</td> <td> 0.000</td> <td> 7552.769</td> <td> 2.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data analysis skills</th>                                             <td>-1.981e+04</td> <td> 7603.759</td> <td>   -2.605</td> <td> 0.009</td> <td>-3.47e+04</td> <td>-4867.552</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Database design</th>                                                  <td> -3.13e+04</td> <td> 1.14e+04</td> <td>   -2.737</td> <td> 0.006</td> <td>-5.38e+04</td> <td>-8828.415</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Java</th>                                                             <td> 5786.3383</td> <td> 8383.273</td> <td>    0.690</td> <td> 0.490</td> <td>-1.07e+04</td> <td> 2.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>US work authorization</th>                                            <td>-5540.3917</td> <td> 5632.850</td> <td>   -0.984</td> <td> 0.326</td> <td>-1.66e+04</td> <td> 5527.700</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Software deployment</th>                                              <td>-2.412e+04</td> <td> 7881.543</td> <td>   -3.060</td> <td> 0.002</td> <td>-3.96e+04</td> <td>-8633.704</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Signal processing</th>                                                <td> 8439.7086</td> <td> 6884.123</td> <td>    1.226</td> <td> 0.221</td> <td>-5087.033</td> <td>  2.2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Agile</th>                                                            <td>-1.552e+04</td> <td> 9209.552</td> <td>   -1.686</td> <td> 0.093</td> <td>-3.36e+04</td> <td> 2573.281</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>APIs</th>                                                             <td> 2.374e+04</td> <td> 1.15e+04</td> <td>    2.063</td> <td> 0.040</td> <td> 1132.783</td> <td> 4.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Organizational skills</th>                                            <td> 5.895e+04</td> <td> 1.89e+04</td> <td>    3.115</td> <td> 0.002</td> <td> 2.18e+04</td> <td> 9.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cassandra</th>                                                        <td> 1.144e+04</td> <td> 1.14e+04</td> <td>    1.006</td> <td> 0.315</td> <td>-1.09e+04</td> <td> 3.38e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Predictive analytics</th>                                             <td> 1270.8500</td> <td> 5878.287</td> <td>    0.216</td> <td> 0.829</td> <td>-1.03e+04</td> <td> 1.28e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Deep learning</th>                                                    <td> -293.2060</td> <td> 2939.024</td> <td>   -0.100</td> <td> 0.921</td> <td>-6068.149</td> <td> 5481.737</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Marketing automation</th>                                             <td>  155.8872</td> <td> 1.43e+04</td> <td>    0.011</td> <td> 0.991</td> <td>-2.78e+04</td> <td> 2.82e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SDKs</th>                                                             <td>-1.889e+04</td> <td> 5516.846</td> <td>   -3.423</td> <td> 0.001</td> <td>-2.97e+04</td> <td>-8046.089</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Maven</th>                                                            <td>-1.889e+04</td> <td> 5516.846</td> <td>   -3.423</td> <td> 0.001</td> <td>-2.97e+04</td> <td>-8046.089</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Database management</th>                                              <td>  858.3181</td> <td> 1.09e+04</td> <td>    0.079</td> <td> 0.937</td> <td>-2.06e+04</td> <td> 2.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Laboratory information management systems</th>                        <td> 4.774e+04</td> <td>  1.4e+04</td> <td>    3.398</td> <td> 0.001</td> <td> 2.01e+04</td> <td> 7.53e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>REST</th>                                                             <td>-1.555e+04</td> <td> 1.23e+04</td> <td>   -1.265</td> <td> 0.206</td> <td>-3.97e+04</td> <td> 8602.744</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>System design</th>                                                    <td>-3023.1080</td> <td> 1.15e+04</td> <td>   -0.264</td> <td> 0.792</td> <td>-2.56e+04</td> <td> 1.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Distributed systems</th>                                              <td>-4525.4353</td> <td> 6002.717</td> <td>   -0.754</td> <td> 0.451</td> <td>-1.63e+04</td> <td> 7269.414</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E-commerce</th>                                                       <td>   96.5088</td> <td> 5241.925</td> <td>    0.018</td> <td> 0.985</td> <td>-1.02e+04</td> <td> 1.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>NumPy</th>                                                            <td>-5682.0849</td> <td> 6220.954</td> <td>   -0.913</td> <td> 0.362</td> <td>-1.79e+04</td> <td> 6541.582</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SciPy</th>                                                            <td>-6258.8624</td> <td> 5760.474</td> <td>   -1.087</td> <td> 0.278</td> <td>-1.76e+04</td> <td> 5059.999</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Elasticsearch</th>                                                    <td> 5290.5526</td> <td> 8419.228</td> <td>    0.628</td> <td> 0.530</td> <td>-1.13e+04</td> <td> 2.18e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Clinical Laboratory Scientist License</th>                            <td>-1.673e+04</td> <td> 1.22e+04</td> <td>   -1.366</td> <td> 0.173</td> <td>-4.08e+04</td> <td> 7334.022</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Master of Business Administration</th>                                <td>-3.015e+04</td> <td> 1.26e+04</td> <td>   -2.395</td> <td> 0.017</td> <td>-5.49e+04</td> <td>-5419.565</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Business analysis</th>                                                <td>-2.885e+04</td> <td> 9903.775</td> <td>   -2.914</td> <td> 0.004</td> <td>-4.83e+04</td> <td>-9394.847</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data modeling</th>                                                    <td> 6196.4105</td> <td> 5779.885</td> <td>    1.072</td> <td> 0.284</td> <td>-5160.592</td> <td> 1.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Root cause analysis</th>                                              <td> 2.541e+04</td> <td> 1.03e+04</td> <td>    2.468</td> <td> 0.014</td> <td> 5182.368</td> <td> 4.56e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Software architecture</th>                                            <td>  -3.1e+04</td> <td> 1.14e+04</td> <td>   -2.721</td> <td> 0.007</td> <td>-5.34e+04</td> <td>-8610.570</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>OS Kernels</th>                                                       <td> 1.897e+04</td> <td> 9055.197</td> <td>    2.095</td> <td> 0.037</td> <td> 1180.299</td> <td> 3.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MySQL</th>                                                            <td>-2758.7494</td> <td> 1.25e+04</td> <td>   -0.220</td> <td> 0.826</td> <td>-2.74e+04</td> <td> 2.18e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Quantitative research</th>                                            <td>-7624.4875</td> <td> 8833.899</td> <td>   -0.863</td> <td> 0.389</td> <td> -2.5e+04</td> <td> 9733.405</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PostgreSQL</th>                                                       <td> 3574.1017</td> <td> 1.15e+04</td> <td>    0.311</td> <td> 0.756</td> <td> -1.9e+04</td> <td> 2.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Digital marketing</th>                                                <td> 3526.6312</td> <td> 9411.775</td> <td>    0.375</td> <td> 0.708</td> <td> -1.5e+04</td> <td>  2.2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>A/B testing</th>                                                      <td>-8081.3349</td> <td> 4934.542</td> <td>   -1.638</td> <td> 0.102</td> <td>-1.78e+04</td> <td> 1614.638</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Big data</th>                                                         <td>-4.466e+04</td> <td>  1.4e+04</td> <td>   -3.201</td> <td> 0.001</td> <td>-7.21e+04</td> <td>-1.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pandas</th>                                                           <td> 1.447e+04</td> <td> 6325.775</td> <td>    2.287</td> <td> 0.023</td> <td> 2038.709</td> <td> 2.69e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Management</th>                                                       <td> 2.785e+04</td> <td> 1.09e+04</td> <td>    2.547</td> <td> 0.011</td> <td> 6360.890</td> <td> 4.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ETL</th>                                                              <td>-1.145e+04</td> <td> 1.25e+04</td> <td>   -0.916</td> <td> 0.360</td> <td> -3.6e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Unit testing</th>                                                     <td>-7.975e+04</td> <td>  1.5e+04</td> <td>   -5.305</td> <td> 0.000</td> <td>-1.09e+05</td> <td>-5.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Military</th>                                                         <td>-3.774e+04</td> <td>  1.7e+04</td> <td>   -2.220</td> <td> 0.027</td> <td>-7.11e+04</td> <td>-4338.045</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>UNIX</th>                                                             <td> 3.083e+04</td> <td> 1.04e+04</td> <td>    2.957</td> <td> 0.003</td> <td> 1.03e+04</td> <td> 5.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Criminal background check</th>                                        <td>-1451.9179</td> <td>  1.3e+04</td> <td>   -0.111</td> <td> 0.911</td> <td> -2.7e+04</td> <td> 2.41e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Test automation</th>                                                  <td>-1.301e+04</td> <td> 6359.840</td> <td>   -2.046</td> <td> 0.041</td> <td>-2.55e+04</td> <td> -512.834</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Quality assurance</th>                                                <td>-1.301e+04</td> <td> 6359.840</td> <td>   -2.046</td> <td> 0.041</td> <td>-2.55e+04</td> <td> -512.834</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Test cases</th>                                                       <td>-1.301e+04</td> <td> 6359.840</td> <td>   -2.046</td> <td> 0.041</td> <td>-2.55e+04</td> <td> -512.834</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Ab Initio</th>                                                        <td>-4.026e+04</td> <td> 9941.372</td> <td>   -4.050</td> <td> 0.000</td> <td>-5.98e+04</td> <td>-2.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Library services</th>                                                 <td>-4.026e+04</td> <td> 9941.372</td> <td>   -4.050</td> <td> 0.000</td> <td>-5.98e+04</td> <td>-2.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Keras</th>                                                            <td>-2.128e+04</td> <td> 5143.921</td> <td>   -4.137</td> <td> 0.000</td> <td>-3.14e+04</td> <td>-1.12e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Flow cytometry</th>                                                   <td>-3875.1202</td> <td> 1.01e+04</td> <td>   -0.385</td> <td> 0.700</td> <td>-2.36e+04</td> <td> 1.59e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Assays</th>                                                           <td>-3875.1202</td> <td> 1.01e+04</td> <td>   -0.385</td> <td> 0.700</td> <td>-2.36e+04</td> <td> 1.59e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sage</th>                                                             <td> 8897.0666</td> <td> 8747.332</td> <td>    1.017</td> <td> 0.310</td> <td>-8290.727</td> <td> 2.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data mining</th>                                                      <td>-1.692e+04</td> <td> 4899.721</td> <td>   -3.453</td> <td> 0.001</td> <td>-2.65e+04</td> <td>-7289.318</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bioinformatics</th>                                                   <td>-2730.4071</td> <td> 1.22e+04</td> <td>   -0.224</td> <td> 0.823</td> <td>-2.67e+04</td> <td> 2.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Laboratory experience</th>                                            <td>-5.461e+04</td> <td> 1.55e+04</td> <td>   -3.517</td> <td> 0.000</td> <td>-8.51e+04</td> <td>-2.41e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Teaching</th>                                                         <td> 6655.7545</td> <td> 1.66e+04</td> <td>    0.400</td> <td> 0.689</td> <td> -2.6e+04</td> <td> 3.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Stata</th>                                                            <td> 1.816e+04</td> <td> 1.27e+04</td> <td>    1.433</td> <td> 0.152</td> <td>-6732.295</td> <td> 4.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pre-employment physical examination</th>                              <td>-6.561e+04</td> <td>  1.4e+04</td> <td>   -4.688</td> <td> 0.000</td> <td>-9.31e+04</td> <td>-3.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GIS</th>                                                              <td>-6569.6958</td> <td> 1.16e+04</td> <td>   -0.566</td> <td> 0.571</td> <td>-2.94e+04</td> <td> 1.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Apache</th>                                                           <td> 3330.8810</td> <td> 1.46e+04</td> <td>    0.228</td> <td> 0.820</td> <td>-2.54e+04</td> <td> 3.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Adobe Photoshop</th>                                                  <td> 5.594e+04</td> <td> 1.17e+04</td> <td>    4.765</td> <td> 0.000</td> <td> 3.29e+04</td> <td>  7.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Fraud</th>                                                            <td>-9529.6522</td> <td> 3924.065</td> <td>   -2.429</td> <td> 0.016</td> <td>-1.72e+04</td> <td>-1819.184</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Math</th>                                                             <td> 3742.4855</td> <td> 1.12e+04</td> <td>    0.335</td> <td> 0.738</td> <td>-1.82e+04</td> <td> 2.57e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Clinical trials</th>                                                  <td> -581.9703</td> <td> 1.02e+04</td> <td>   -0.057</td> <td> 0.954</td> <td>-2.06e+04</td> <td> 1.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Presentation skills</th>                                              <td>  1.83e+04</td> <td> 1.04e+04</td> <td>    1.766</td> <td> 0.078</td> <td>-2063.227</td> <td> 3.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Live chat</th>                                                        <td>-3.458e+04</td> <td>  1.7e+04</td> <td>   -2.033</td> <td> 0.043</td> <td> -6.8e+04</td> <td>-1154.262</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Algorithm design</th>                                                 <td>-1452.9775</td> <td> 1.17e+04</td> <td>   -0.124</td> <td> 0.901</td> <td>-2.44e+04</td> <td> 2.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Senior leadership</th>                                                <td> 1664.7955</td> <td> 9792.260</td> <td>    0.170</td> <td> 0.865</td> <td>-1.76e+04</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>LabView</th>                                                          <td>-3621.7247</td> <td> 1.45e+04</td> <td>   -0.250</td> <td> 0.803</td> <td>-3.21e+04</td> <td> 2.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Product development</th>                                              <td>-3.004e+04</td> <td> 1.37e+04</td> <td>   -2.197</td> <td> 0.029</td> <td>-5.69e+04</td> <td>-3169.504</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Git</th>                                                              <td>-1.875e+04</td> <td> 9279.942</td> <td>   -2.020</td> <td> 0.044</td> <td> -3.7e+04</td> <td> -512.899</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Recruiting</th>                                                       <td> -565.4436</td> <td> 3473.204</td> <td>   -0.163</td> <td> 0.871</td> <td>-7390.006</td> <td> 6259.118</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>IT sourcing</th>                                                      <td> -565.4436</td> <td> 3473.204</td> <td>   -0.163</td> <td> 0.871</td> <td>-7390.006</td> <td> 6259.118</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sourcing</th>                                                         <td> -565.4436</td> <td> 3473.204</td> <td>   -0.163</td> <td> 0.871</td> <td>-7390.006</td> <td> 6259.118</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HR sourcing</th>                                                      <td> -565.4436</td> <td> 3473.204</td> <td>   -0.163</td> <td> 0.871</td> <td>-7390.006</td> <td> 6259.118</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Torch</th>                                                            <td>-2612.1471</td> <td> 2.61e+04</td> <td>   -0.100</td> <td> 0.920</td> <td>-5.39e+04</td> <td> 4.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>JavaScript</th>                                                       <td>-2.912e+04</td> <td> 2.15e+04</td> <td>   -1.354</td> <td> 0.176</td> <td>-7.14e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GitHub</th>                                                           <td>-2.959e+04</td> <td> 1.15e+04</td> <td>   -2.571</td> <td> 0.010</td> <td>-5.22e+04</td> <td>-6975.065</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intellectual property law</th>                                        <td> 1557.2427</td> <td> 1.31e+04</td> <td>    0.119</td> <td> 0.905</td> <td>-2.41e+04</td> <td> 2.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Conversion optimization</th>                                          <td> 4.696e+04</td> <td> 1.99e+04</td> <td>    2.358</td> <td> 0.019</td> <td> 7822.573</td> <td> 8.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Jenkins</th>                                                          <td> 5.087e+04</td> <td> 2.47e+04</td> <td>    2.055</td> <td> 0.040</td> <td> 2240.904</td> <td> 9.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Azure</th>                                                            <td> 3079.5824</td> <td> 7370.612</td> <td>    0.418</td> <td> 0.676</td> <td>-1.14e+04</td> <td> 1.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Node.js</th>                                                          <td>-3.817e+04</td> <td> 3.34e+04</td> <td>   -1.143</td> <td> 0.253</td> <td>-1.04e+05</td> <td> 2.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Business development</th>                                             <td>     1e+04</td> <td> 2.01e+04</td> <td>    0.498</td> <td> 0.619</td> <td>-2.95e+04</td> <td> 4.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Apache Pig</th>                                                       <td>  2.46e+04</td> <td> 1.39e+04</td> <td>    1.772</td> <td> 0.077</td> <td>-2676.008</td> <td> 5.19e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Teradata</th>                                                         <td>-6552.3291</td> <td> 1.12e+04</td> <td>   -0.587</td> <td> 0.558</td> <td>-2.85e+04</td> <td> 1.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Google Analytics</th>                                                 <td> -3.56e+04</td> <td> 1.54e+04</td> <td>   -2.305</td> <td> 0.022</td> <td>-6.59e+04</td> <td>-5249.165</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sentiment analytics</th>                                              <td>-2.825e+04</td> <td> 1.57e+04</td> <td>   -1.804</td> <td> 0.072</td> <td> -5.9e+04</td> <td> 2511.854</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Industrial equipment</th>                                             <td>-8739.5431</td> <td> 8243.187</td> <td>   -1.060</td> <td> 0.290</td> <td>-2.49e+04</td> <td> 7457.648</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Mechanical knowledge</th>                                             <td>-8739.5431</td> <td> 8243.187</td> <td>   -1.060</td> <td> 0.290</td> <td>-2.49e+04</td> <td> 7457.648</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Ansible</th>                                                          <td>-3.261e+04</td> <td> 3.69e+04</td> <td>   -0.883</td> <td> 0.377</td> <td>-1.05e+05</td> <td> 3.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cloud architecture</th>                                               <td> 1.366e+04</td> <td>  1.4e+04</td> <td>    0.978</td> <td> 0.329</td> <td>-1.38e+04</td> <td> 4.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Linux</th>                                                            <td> 1.091e+05</td> <td> 1.89e+04</td> <td>    5.767</td> <td> 0.000</td> <td> 7.19e+04</td> <td> 1.46e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cleaning</th>                                                         <td>-8.235e+04</td> <td> 1.95e+04</td> <td>   -4.216</td> <td> 0.000</td> <td>-1.21e+05</td> <td> -4.4e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Computer skills</th>                                                  <td>-3.159e+04</td> <td> 2.87e+04</td> <td>   -1.100</td> <td> 0.272</td> <td> -8.8e+04</td> <td> 2.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>JSON</th>                                                             <td> 3.326e+04</td> <td> 1.45e+04</td> <td>    2.295</td> <td> 0.022</td> <td> 4781.770</td> <td> 6.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>High school diploma or GED</th>                                       <td>-1.546e+04</td> <td> 1.46e+04</td> <td>   -1.061</td> <td> 0.289</td> <td>-4.41e+04</td> <td> 1.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microservices</th>                                                    <td>-1.307e+04</td> <td> 1.28e+04</td> <td>   -1.023</td> <td> 0.307</td> <td>-3.82e+04</td> <td>  1.2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>NoSQL</th>                                                            <td>-2842.8863</td> <td> 8159.515</td> <td>   -0.348</td> <td> 0.728</td> <td>-1.89e+04</td> <td> 1.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>21 years or older</th>                                                <td>-1.785e+04</td> <td> 1.29e+04</td> <td>   -1.382</td> <td> 0.168</td> <td>-4.32e+04</td> <td> 7525.820</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Drug discovery</th>                                                   <td>-2.804e+04</td> <td>  2.1e+04</td> <td>   -1.337</td> <td> 0.182</td> <td>-6.93e+04</td> <td> 1.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Supply chain management</th>                                          <td> 2639.7967</td> <td> 8083.052</td> <td>    0.327</td> <td> 0.744</td> <td>-1.32e+04</td> <td> 1.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>.NET</th>                                                             <td>-4341.4630</td> <td> 1.85e+04</td> <td>   -0.235</td> <td> 0.814</td> <td>-4.06e+04</td> <td> 3.19e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kubernetes</th>                                                       <td>  693.7107</td> <td> 1.12e+04</td> <td>    0.062</td> <td> 0.951</td> <td>-2.13e+04</td> <td> 2.27e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ADAS</th>                                                             <td>-8124.8212</td> <td> 1.28e+04</td> <td>   -0.636</td> <td> 0.525</td> <td>-3.32e+04</td> <td>  1.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Master of Science</th>                                                <td>-1.083e+04</td> <td> 5503.301</td> <td>   -1.967</td> <td> 0.050</td> <td>-2.16e+04</td> <td>  -11.715</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microsoft Access</th>                                                 <td>  159.8419</td> <td> 1.43e+04</td> <td>    0.011</td> <td> 0.991</td> <td>-2.79e+04</td> <td> 2.83e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lean</th>                                                             <td>-7305.1188</td> <td> 7294.369</td> <td>   -1.001</td> <td> 0.317</td> <td>-2.16e+04</td> <td> 7027.721</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Perl</th>                                                             <td>-3.272e+04</td> <td> 1.21e+04</td> <td>   -2.709</td> <td> 0.007</td> <td>-5.64e+04</td> <td>-8985.028</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>PHP</th>                                                              <td> 7748.4529</td> <td> 1.84e+04</td> <td>    0.421</td> <td> 0.674</td> <td>-2.84e+04</td> <td> 4.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>OOP</th>                                                              <td>-1.194e+04</td> <td> 1.48e+04</td> <td>   -0.810</td> <td> 0.418</td> <td>-4.09e+04</td> <td>  1.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>D3.js</th>                                                            <td> 2.438e+04</td> <td> 1.37e+04</td> <td>    1.777</td> <td> 0.076</td> <td>-2575.187</td> <td> 5.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Software development</th>                                             <td>-2.045e+04</td> <td> 6713.579</td> <td>   -3.045</td> <td> 0.002</td> <td>-3.36e+04</td> <td>-7253.506</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Mentoring</th>                                                        <td> 1.482e+04</td> <td> 6321.205</td> <td>    2.344</td> <td> 0.019</td> <td> 2397.913</td> <td> 2.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lucene</th>                                                           <td> 4.343e+04</td> <td> 2.01e+04</td> <td>    2.163</td> <td> 0.031</td> <td> 3983.847</td> <td> 8.29e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data structures</th>                                                  <td> -2.18e+04</td> <td> 7959.027</td> <td>   -2.739</td> <td> 0.006</td> <td>-3.74e+04</td> <td>-6164.042</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Jira</th>                                                             <td>-2.604e+04</td> <td> 2.07e+04</td> <td>   -1.257</td> <td> 0.209</td> <td>-6.68e+04</td> <td> 1.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Master of Engineering</th>                                            <td> 3.616e+04</td> <td> 1.28e+04</td> <td>    2.814</td> <td> 0.005</td> <td> 1.09e+04</td> <td> 6.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Confluence</th>                                                       <td>-2.302e+04</td> <td> 2.73e+04</td> <td>   -0.843</td> <td> 0.399</td> <td>-7.66e+04</td> <td> 3.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Employee evaluation</th>                                              <td>-1.273e+04</td> <td> 2.01e+04</td> <td>   -0.633</td> <td> 0.527</td> <td>-5.22e+04</td> <td> 2.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Auto estimating</th>                                                  <td>-9126.2096</td> <td> 1.35e+04</td> <td>   -0.675</td> <td> 0.500</td> <td>-3.57e+04</td> <td> 1.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Construction estimating</th>                                          <td>-1.572e+04</td> <td> 5147.651</td> <td>   -3.053</td> <td> 0.002</td> <td>-2.58e+04</td> <td>-5603.286</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Banking</th>                                                          <td>-4330.7072</td> <td> 2.19e+04</td> <td>   -0.198</td> <td> 0.844</td> <td>-4.74e+04</td> <td> 3.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Martech</th>                                                          <td>-5.547e+04</td> <td> 1.42e+04</td> <td>   -3.916</td> <td> 0.000</td> <td>-8.33e+04</td> <td>-2.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Docker</th>                                                           <td> 9.735e+04</td> <td> 1.85e+04</td> <td>    5.252</td> <td> 0.000</td> <td> 6.09e+04</td> <td> 1.34e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bachelor of Arts</th>                                                 <td>-2.137e+04</td> <td> 1.55e+04</td> <td>   -1.376</td> <td> 0.169</td> <td>-5.19e+04</td> <td> 9143.183</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Business intelligence</th>                                            <td> 5883.6711</td> <td> 1.55e+04</td> <td>    0.379</td> <td> 0.705</td> <td>-2.46e+04</td> <td> 3.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Ontology</th>                                                         <td> 1.469e+05</td> <td> 1.64e+04</td> <td>    8.975</td> <td> 0.000</td> <td> 1.15e+05</td> <td> 1.79e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Neo4j</th>                                                            <td>-3.804e+04</td> <td> 1.04e+04</td> <td>   -3.655</td> <td> 0.000</td> <td>-5.85e+04</td> <td>-1.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Market research</th>                                                  <td>  100.6002</td> <td> 9870.179</td> <td>    0.010</td> <td> 0.992</td> <td>-1.93e+04</td> <td> 1.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Windows</th>                                                          <td>-2.231e+04</td> <td>  1.8e+04</td> <td>   -1.236</td> <td> 0.217</td> <td>-5.78e+04</td> <td> 1.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SPSS</th>                                                             <td>-1960.1768</td> <td> 2.83e+04</td> <td>   -0.069</td> <td> 0.945</td> <td>-5.76e+04</td> <td> 5.36e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Social media management</th>                                          <td>  945.3113</td> <td> 7738.656</td> <td>    0.122</td> <td> 0.903</td> <td>-1.43e+04</td> <td> 1.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time management</th>                                                  <td>  3.06e+04</td> <td> 1.44e+04</td> <td>    2.128</td> <td> 0.034</td> <td> 2339.974</td> <td> 5.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Forecasting</th>                                                      <td>-9539.5949</td> <td> 1.55e+04</td> <td>   -0.614</td> <td> 0.540</td> <td>-4.01e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Financial modeling</th>                                               <td>-2.104e+04</td> <td> 1.17e+04</td> <td>   -1.792</td> <td> 0.074</td> <td>-4.41e+04</td> <td> 2032.222</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Internet of things</th>                                               <td>-8919.0819</td> <td> 1.19e+04</td> <td>   -0.748</td> <td> 0.455</td> <td>-3.24e+04</td> <td> 1.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CI/CD</th>                                                            <td>-8742.6270</td> <td> 2.57e+04</td> <td>   -0.340</td> <td> 0.734</td> <td>-5.92e+04</td> <td> 4.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data warehouse</th>                                                   <td>-4.907e+04</td> <td> 2.12e+04</td> <td>   -2.311</td> <td> 0.021</td> <td>-9.08e+04</td> <td>-7356.286</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Application development</th>                                          <td>-1.106e+04</td> <td> 1.49e+04</td> <td>   -0.741</td> <td> 0.459</td> <td>-4.04e+04</td> <td> 1.83e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Scripting</th>                                                        <td>-5.822e+04</td> <td> 7867.026</td> <td>   -7.400</td> <td> 0.000</td> <td>-7.37e+04</td> <td>-4.28e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bash</th>                                                             <td> 1452.1761</td> <td> 1.48e+04</td> <td>    0.098</td> <td> 0.922</td> <td>-2.77e+04</td> <td> 3.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microsoft Office</th>                                                 <td>-1.868e+04</td> <td> 8721.855</td> <td>   -2.141</td> <td> 0.033</td> <td>-3.58e+04</td> <td>-1538.888</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>QuickBooks</th>                                                       <td> 2.148e+04</td> <td> 1.61e+04</td> <td>    1.336</td> <td> 0.182</td> <td>-1.01e+04</td> <td> 5.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Public health</th>                                                    <td> 9683.9446</td> <td> 2.58e+04</td> <td>    0.375</td> <td> 0.708</td> <td> -4.1e+04</td> <td> 6.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Marketing</th>                                                        <td>-1.448e+04</td> <td> 1.13e+04</td> <td>   -1.281</td> <td> 0.201</td> <td>-3.67e+04</td> <td> 7735.867</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TypeScript</th>                                                       <td>-4036.1577</td> <td> 5456.295</td> <td>   -0.740</td> <td> 0.460</td> <td>-1.48e+04</td> <td> 6685.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Swift</th>                                                            <td>-9655.6609</td> <td> 5517.100</td> <td>   -1.750</td> <td> 0.081</td> <td>-2.05e+04</td> <td> 1184.991</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sensors</th>                                                          <td>-3.406e+04</td> <td> 9287.167</td> <td>   -3.668</td> <td> 0.000</td> <td>-5.23e+04</td> <td>-1.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Performance marketing</th>                                            <td>-8171.2490</td> <td> 1.01e+04</td> <td>   -0.805</td> <td> 0.421</td> <td>-2.81e+04</td> <td> 1.18e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SSIS</th>                                                             <td>-7.704e+04</td> <td> 1.61e+04</td> <td>   -4.773</td> <td> 0.000</td> <td>-1.09e+05</td> <td>-4.53e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Financial services</th>                                               <td> 3.849e+04</td> <td> 1.09e+04</td> <td>    3.537</td> <td> 0.000</td> <td> 1.71e+04</td> <td> 5.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Telecommunication</th>                                                <td> 2.825e+04</td> <td> 2.78e+04</td> <td>    1.018</td> <td> 0.309</td> <td>-2.63e+04</td> <td> 8.28e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Associate's degree</th>                                               <td>-6.475e+04</td> <td> 2.17e+04</td> <td>   -2.989</td> <td> 0.003</td> <td>-1.07e+05</td> <td>-2.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GitLab</th>                                                           <td> 2.261e+04</td> <td> 1.12e+04</td> <td>    2.014</td> <td> 0.045</td> <td>  550.990</td> <td> 4.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Full-stack development</th>                                           <td> -986.0430</td> <td> 2.89e+04</td> <td>   -0.034</td> <td> 0.973</td> <td>-5.78e+04</td> <td> 5.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Regression analysis</th>                                              <td>-1.915e+04</td> <td> 8290.597</td> <td>   -2.309</td> <td> 0.021</td> <td>-3.54e+04</td> <td>-2855.424</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Legal drafting</th>                                                   <td>-2717.0338</td> <td> 8064.652</td> <td>   -0.337</td> <td> 0.736</td> <td>-1.86e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Drafting</th>                                                         <td>-2717.0338</td> <td> 8064.652</td> <td>   -0.337</td> <td> 0.736</td> <td>-1.86e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Design thinking</th>                                                  <td> -1.44e+04</td> <td> 1.18e+04</td> <td>   -1.219</td> <td> 0.223</td> <td>-3.76e+04</td> <td> 8811.007</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>AWS</th>                                                              <td> 1.814e+04</td> <td> 1.52e+04</td> <td>    1.195</td> <td> 0.233</td> <td>-1.17e+04</td> <td>  4.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Terraform</th>                                                        <td> 1.072e+04</td> <td> 3.12e+04</td> <td>    0.343</td> <td> 0.732</td> <td>-5.07e+04</td> <td> 7.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bank Secrecy Act</th>                                                 <td>-3.964e+04</td> <td> 8853.520</td> <td>   -4.478</td> <td> 0.000</td> <td> -5.7e+04</td> <td>-2.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cognos</th>                                                           <td>-3.964e+04</td> <td> 8853.520</td> <td>   -4.478</td> <td> 0.000</td> <td> -5.7e+04</td> <td>-2.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Filing</th>                                                           <td> 1.121e+04</td> <td> 1.95e+04</td> <td>    0.576</td> <td> 0.565</td> <td> -2.7e+04</td> <td> 4.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Negotiation</th>                                                      <td>-5.656e+04</td> <td> 2.66e+04</td> <td>   -2.126</td> <td> 0.034</td> <td>-1.09e+05</td> <td>-4282.244</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Graph databases</th>                                                  <td>-3116.7735</td> <td> 6385.921</td> <td>   -0.488</td> <td> 0.626</td> <td>-1.57e+04</td> <td> 9431.041</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>DynamoDB</th>                                                         <td>-6462.5722</td> <td> 1.66e+04</td> <td>   -0.390</td> <td> 0.697</td> <td> -3.9e+04</td> <td> 2.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SEM</th>                                                              <td>-3.487e+04</td> <td> 1.05e+04</td> <td>   -3.327</td> <td> 0.001</td> <td>-5.55e+04</td> <td>-1.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Web services</th>                                                     <td> 1.318e+04</td> <td> 1.18e+04</td> <td>    1.118</td> <td> 0.264</td> <td>-9980.887</td> <td> 3.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Patient monitoring</th>                                               <td> 3.385e+04</td> <td> 2.27e+04</td> <td>    1.490</td> <td> 0.137</td> <td>-1.08e+04</td> <td> 7.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Qualitative research</th>                                             <td>-2.524e+04</td> <td> 1.34e+04</td> <td>   -1.885</td> <td> 0.060</td> <td>-5.16e+04</td> <td> 1067.069</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>HITRUST</th>                                                          <td>-1.273e+04</td> <td> 1.54e+04</td> <td>   -0.828</td> <td> 0.408</td> <td>-4.29e+04</td> <td> 1.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Continuous integration</th>                                           <td>-8040.9962</td> <td>  1.4e+04</td> <td>   -0.576</td> <td> 0.565</td> <td>-3.55e+04</td> <td> 1.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>System testing</th>                                                   <td> 3924.8247</td> <td> 2.01e+04</td> <td>    0.195</td> <td> 0.845</td> <td>-3.56e+04</td> <td> 4.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kanban</th>                                                           <td>   58.0628</td> <td> 1.26e+04</td> <td>    0.005</td> <td> 0.996</td> <td>-2.47e+04</td> <td> 2.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Rust</th>                                                             <td>  139.5141</td> <td>  1.4e+04</td> <td>    0.010</td> <td> 0.992</td> <td>-2.74e+04</td> <td> 2.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Research & development</th>                                           <td> 5.129e+04</td> <td>  1.3e+04</td> <td>    3.947</td> <td> 0.000</td> <td> 2.58e+04</td> <td> 7.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Dart</th>                                                             <td>-5619.5032</td> <td> 4727.756</td> <td>   -1.189</td> <td> 0.235</td> <td>-1.49e+04</td> <td> 3670.151</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pricing</th>                                                          <td> 6.487e+04</td> <td> 1.92e+04</td> <td>    3.374</td> <td> 0.001</td> <td> 2.71e+04</td> <td> 1.03e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>OpenCV</th>                                                           <td>-7032.0034</td> <td> 2.04e+04</td> <td>   -0.345</td> <td> 0.730</td> <td> -4.7e+04</td> <td>  3.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Affiliate marketing</th>                                              <td> 1334.3409</td> <td> 1.39e+04</td> <td>    0.096</td> <td> 0.924</td> <td>-2.61e+04</td> <td> 2.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Ruby on Rails</th>                                                    <td>   69.4623</td> <td> 1.03e+04</td> <td>    0.007</td> <td> 0.995</td> <td>-2.02e+04</td> <td> 2.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Growing experience</th>                                               <td>-8626.2141</td> <td> 1.25e+04</td> <td>   -0.689</td> <td> 0.491</td> <td>-3.32e+04</td> <td>  1.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Scrum</th>                                                            <td> 3.446e+04</td> <td> 9848.779</td> <td>    3.499</td> <td> 0.001</td> <td> 1.51e+04</td> <td> 5.38e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>VBA</th>                                                              <td> 4.785e+04</td> <td> 2.38e+04</td> <td>    2.012</td> <td> 0.045</td> <td> 1121.832</td> <td> 9.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Ceridian</th>                                                         <td>-2.258e+04</td> <td> 2.85e+04</td> <td>   -0.793</td> <td> 0.428</td> <td>-7.85e+04</td> <td> 3.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MTA</th>                                                              <td> 2.533e+04</td> <td> 1.05e+04</td> <td>    2.407</td> <td> 0.016</td> <td> 4650.107</td> <td>  4.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>New Relic</th>                                                        <td> 7843.1707</td> <td> 2.01e+04</td> <td>    0.390</td> <td> 0.696</td> <td>-3.16e+04</td> <td> 4.73e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sailpoint</th>                                                        <td> 1.933e+04</td> <td> 2.96e+04</td> <td>    0.653</td> <td> 0.514</td> <td>-3.88e+04</td> <td> 7.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>DevOps</th>                                                           <td>-1.332e+04</td> <td> 8715.071</td> <td>   -1.528</td> <td> 0.127</td> <td>-3.04e+04</td> <td> 3803.787</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Backbone.js</th>                                                      <td>-3.384e+04</td> <td> 6221.590</td> <td>   -5.439</td> <td> 0.000</td> <td>-4.61e+04</td> <td>-2.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Computer networking</th>                                              <td> -719.2005</td> <td> 7111.260</td> <td>   -0.101</td> <td> 0.919</td> <td>-1.47e+04</td> <td> 1.33e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Calibration</th>                                                      <td>-9133.6624</td> <td> 1.19e+04</td> <td>   -0.767</td> <td> 0.444</td> <td>-3.25e+04</td> <td> 1.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Computer science</th>                                                 <td> -9.21e+04</td> <td> 2.55e+04</td> <td>   -3.607</td> <td> 0.000</td> <td>-1.42e+05</td> <td>-4.19e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Survival analysis</th>                                                <td>-2.548e+04</td> <td> 1.38e+04</td> <td>   -1.842</td> <td> 0.066</td> <td>-5.27e+04</td> <td> 1702.707</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Project management methodology</th>                                   <td>-2.147e+04</td> <td> 5056.241</td> <td>   -4.247</td> <td> 0.000</td> <td>-3.14e+04</td> <td>-1.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Figma</th>                                                            <td>-7914.3272</td> <td> 2575.138</td> <td>   -3.073</td> <td> 0.002</td> <td> -1.3e+04</td> <td>-2854.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Visual design</th>                                                    <td>-7914.3272</td> <td> 2575.138</td> <td>   -3.073</td> <td> 0.002</td> <td> -1.3e+04</td> <td>-2854.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>InVision</th>                                                         <td>-7914.3272</td> <td> 2575.138</td> <td>   -3.073</td> <td> 0.002</td> <td> -1.3e+04</td> <td>-2854.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>User research</th>                                                    <td>-7914.3272</td> <td> 2575.138</td> <td>   -3.073</td> <td> 0.002</td> <td> -1.3e+04</td> <td>-2854.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cloud computing</th>                                                  <td> -2.08e+04</td> <td> 1.46e+04</td> <td>   -1.425</td> <td> 0.155</td> <td>-4.95e+04</td> <td> 7890.837</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Flask</th>                                                            <td>-1811.9563</td> <td> 1.67e+04</td> <td>   -0.109</td> <td> 0.913</td> <td>-3.46e+04</td> <td> 3.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Six Sigma Certification</th>                                          <td>  2.34e+04</td> <td> 8794.165</td> <td>    2.661</td> <td> 0.008</td> <td> 6124.191</td> <td> 4.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lean Six Sigma Certification</th>                                     <td>  2.34e+04</td> <td> 8794.165</td> <td>    2.661</td> <td> 0.008</td> <td> 6124.191</td> <td> 4.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>React</th>                                                            <td> 4.089e+04</td> <td> 1.42e+04</td> <td>    2.881</td> <td> 0.004</td> <td>  1.3e+04</td> <td> 6.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Computer graphics</th>                                                <td> -973.5861</td> <td> 1.56e+04</td> <td>   -0.062</td> <td> 0.950</td> <td>-3.16e+04</td> <td> 2.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Operations research</th>                                              <td>  740.9268</td> <td>  1.8e+04</td> <td>    0.041</td> <td> 0.967</td> <td>-3.47e+04</td> <td> 3.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Human resources</th>                                                  <td>-1.164e+04</td> <td> 9732.149</td> <td>   -1.196</td> <td> 0.232</td> <td>-3.08e+04</td> <td> 7482.174</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SaaS</th>                                                             <td> 2108.1078</td> <td> 1.89e+04</td> <td>    0.112</td> <td> 0.911</td> <td> -3.5e+04</td> <td> 3.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Driver's License</th>                                                 <td>-3.021e+04</td> <td> 1.17e+04</td> <td>   -2.574</td> <td> 0.010</td> <td>-5.33e+04</td> <td>-7152.119</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Marketing mix modeling</th>                                           <td> 9949.9272</td> <td> 5554.826</td> <td>    1.791</td> <td> 0.074</td> <td> -964.852</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Continuous improvement</th>                                           <td> 9493.0284</td> <td> 1.07e+04</td> <td>    0.884</td> <td> 0.377</td> <td>-1.16e+04</td> <td> 3.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Linguistics</th>                                                      <td>-2.452e+04</td> <td> 1.57e+04</td> <td>   -1.558</td> <td> 0.120</td> <td>-5.54e+04</td> <td> 6396.211</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Geometry</th>                                                         <td>-3.543e+04</td> <td> 2.04e+04</td> <td>   -1.739</td> <td> 0.083</td> <td>-7.55e+04</td> <td> 4607.883</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Agriculture</th>                                                      <td>-3716.7572</td> <td> 8968.730</td> <td>   -0.414</td> <td> 0.679</td> <td>-2.13e+04</td> <td> 1.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Supervising experience</th>                                           <td>-3716.7572</td> <td> 8968.730</td> <td>   -0.414</td> <td> 0.679</td> <td>-2.13e+04</td> <td> 1.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>DB2</th>                                                              <td>-4.402e+04</td> <td> 1.65e+04</td> <td>   -2.666</td> <td> 0.008</td> <td>-7.65e+04</td> <td>-1.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Inventory control</th>                                                <td> -1.44e+04</td> <td> 1.78e+04</td> <td>   -0.809</td> <td> 0.419</td> <td>-4.94e+04</td> <td> 2.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Alteryx</th>                                                          <td> 4266.4865</td> <td> 2.71e+04</td> <td>    0.158</td> <td> 0.875</td> <td>-4.89e+04</td> <td> 5.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pass drug screening</th>                                              <td> 7223.6617</td> <td> 9545.228</td> <td>    0.757</td> <td> 0.450</td> <td>-1.15e+04</td> <td>  2.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Integration testing</th>                                              <td>-3.225e+04</td> <td> 1.47e+04</td> <td>   -2.190</td> <td> 0.029</td> <td>-6.12e+04</td> <td>-3310.909</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Program management</th>                                               <td>-2.181e+04</td> <td> 1.44e+04</td> <td>   -1.512</td> <td> 0.131</td> <td>-5.01e+04</td> <td> 6523.833</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Databases</th>                                                        <td> 3.251e+04</td> <td> 2.54e+04</td> <td>    1.278</td> <td> 0.202</td> <td>-1.75e+04</td> <td> 8.25e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>RDF</th>                                                              <td> 1.683e+04</td> <td> 1.22e+04</td> <td>    1.381</td> <td> 0.168</td> <td>-7123.274</td> <td> 4.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Change management</th>                                                <td> 3237.9009</td> <td> 1.29e+04</td> <td>    0.250</td> <td> 0.802</td> <td>-2.22e+04</td> <td> 2.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ICD-10</th>                                                           <td>-3.148e+04</td> <td> 1.04e+04</td> <td>   -3.030</td> <td> 0.003</td> <td>-5.19e+04</td> <td>-1.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>18 years or older</th>                                                <td>-6398.7547</td> <td> 8692.938</td> <td>   -0.736</td> <td> 0.462</td> <td>-2.35e+04</td> <td> 1.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lever</th>                                                            <td>-2.605e+04</td> <td> 1.19e+04</td> <td>   -2.185</td> <td> 0.029</td> <td>-4.95e+04</td> <td>-2628.964</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CRM software</th>                                                     <td>-2.072e+04</td> <td> 5861.043</td> <td>   -3.535</td> <td> 0.000</td> <td>-3.22e+04</td> <td>-9200.762</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intelligence targeting</th>                                           <td>-2.072e+04</td> <td> 5861.043</td> <td>   -3.535</td> <td> 0.000</td> <td>-3.22e+04</td> <td>-9200.762</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Customer segmentation</th>                                            <td>-2.072e+04</td> <td> 5861.043</td> <td>   -3.535</td> <td> 0.000</td> <td>-3.22e+04</td> <td>-9200.762</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Service-oriented architecture</th>                                    <td> 4.127e+04</td> <td> 2.38e+04</td> <td>    1.735</td> <td> 0.083</td> <td>-5470.154</td> <td>  8.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Julia</th>                                                            <td>-2.926e+04</td> <td> 1.19e+04</td> <td>   -2.460</td> <td> 0.014</td> <td>-5.26e+04</td> <td>-5884.259</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Team management</th>                                                  <td>-1.196e+04</td> <td> 8018.968</td> <td>   -1.492</td> <td> 0.136</td> <td>-2.77e+04</td> <td> 3795.069</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>AdRoll</th>                                                           <td>-1.921e+04</td> <td> 1.31e+04</td> <td>   -1.464</td> <td> 0.144</td> <td> -4.5e+04</td> <td> 6573.110</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Medical records</th>                                                  <td>  3.97e+04</td> <td> 9764.716</td> <td>    4.065</td> <td> 0.000</td> <td> 2.05e+04</td> <td> 5.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Project planning</th>                                                 <td>-2.516e+04</td> <td> 1.37e+04</td> <td>   -1.843</td> <td> 0.066</td> <td> -5.2e+04</td> <td> 1665.455</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Strategic planning</th>                                               <td>-4874.2787</td> <td> 1.41e+04</td> <td>   -0.345</td> <td> 0.731</td> <td>-3.27e+04</td> <td> 2.29e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Reliable transportation</th>                                          <td>-8326.7221</td> <td> 1.22e+04</td> <td>   -0.683</td> <td> 0.495</td> <td>-3.23e+04</td> <td> 1.56e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Debugging</th>                                                        <td> 3.376e+04</td> <td> 1.81e+04</td> <td>    1.861</td> <td> 0.063</td> <td>-1889.722</td> <td> 6.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>EHR systems</th>                                                      <td>-1.036e+04</td> <td> 1.19e+04</td> <td>   -0.868</td> <td> 0.386</td> <td>-3.38e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Scalability</th>                                                      <td>  384.4163</td> <td> 2.61e+04</td> <td>    0.015</td> <td> 0.988</td> <td>-5.08e+04</td> <td> 5.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>C#</th>                                                               <td>-1.195e+04</td> <td> 1.34e+04</td> <td>   -0.891</td> <td> 0.373</td> <td>-3.83e+04</td> <td> 1.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Technical writing</th>                                                <td>-9441.4127</td> <td> 2.32e+04</td> <td>   -0.406</td> <td> 0.685</td> <td>-5.51e+04</td> <td> 3.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Design patterns</th>                                                  <td> 4.425e+04</td> <td> 1.56e+04</td> <td>    2.839</td> <td> 0.005</td> <td> 1.36e+04</td> <td> 7.49e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Solr</th>                                                             <td>-9144.2840</td> <td> 2.47e+04</td> <td>   -0.370</td> <td> 0.711</td> <td>-5.77e+04</td> <td> 3.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Image processing</th>                                                 <td>-1.537e+04</td> <td> 1.33e+04</td> <td>   -1.158</td> <td> 0.247</td> <td>-4.14e+04</td> <td> 1.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Biostatistics</th>                                                    <td> 8104.2126</td> <td> 1.54e+04</td> <td>    0.526</td> <td> 0.599</td> <td>-2.22e+04</td> <td> 3.84e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Production design</th>                                                <td>-2.562e+04</td> <td> 1.29e+04</td> <td>   -1.981</td> <td> 0.048</td> <td> -5.1e+04</td> <td> -201.914</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Operating systems</th>                                                <td>-2.988e+04</td> <td> 1.29e+04</td> <td>   -2.317</td> <td> 0.021</td> <td>-5.52e+04</td> <td>-4545.624</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Google Cloud Platform</th>                                            <td>-1.136e+05</td> <td> 2.38e+04</td> <td>   -4.765</td> <td> 0.000</td> <td> -1.6e+05</td> <td>-6.67e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>FDA regulations</th>                                                  <td>-1.355e+04</td> <td>  1.1e+04</td> <td>   -1.232</td> <td> 0.219</td> <td>-3.52e+04</td> <td> 8058.997</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Certified Nephrology Nurse</th>                                       <td>-1.862e+04</td> <td> 8260.763</td> <td>   -2.254</td> <td> 0.025</td> <td>-3.48e+04</td> <td>-2384.764</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Training & development</th>                                           <td> 6.627e+04</td> <td>  2.7e+04</td> <td>    2.450</td> <td> 0.015</td> <td> 1.31e+04</td> <td> 1.19e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Google Ads</th>                                                       <td> 2202.1140</td> <td> 2.46e+04</td> <td>    0.090</td> <td> 0.929</td> <td>-4.61e+04</td> <td> 5.05e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Medical terminology</th>                                              <td>-9269.1533</td> <td>  1.3e+04</td> <td>   -0.716</td> <td> 0.474</td> <td>-3.47e+04</td> <td> 1.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Algebra</th>                                                          <td>-3.837e+04</td> <td> 2.47e+04</td> <td>   -1.555</td> <td> 0.121</td> <td>-8.69e+04</td> <td> 1.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Search engines</th>                                                   <td>-3.083e+04</td> <td> 1.23e+04</td> <td>   -2.511</td> <td> 0.012</td> <td> -5.5e+04</td> <td>-6706.413</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Current immunizations</th>                                            <td> 5.282e+04</td> <td> 1.74e+04</td> <td>    3.031</td> <td> 0.003</td> <td> 1.86e+04</td> <td> 8.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Translation</th>                                                      <td> 7361.2876</td> <td>  1.5e+04</td> <td>    0.491</td> <td> 0.624</td> <td>-2.21e+04</td> <td> 3.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Tooling</th>                                                          <td> 2.015e+04</td> <td> 1.79e+04</td> <td>    1.126</td> <td> 0.261</td> <td> -1.5e+04</td> <td> 5.53e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Quantitative analysis</th>                                            <td>-7127.4239</td> <td> 1.74e+04</td> <td>   -0.409</td> <td> 0.683</td> <td>-4.14e+04</td> <td> 2.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Investment</th>                                                       <td>-1.794e+04</td> <td> 1.61e+04</td> <td>   -1.111</td> <td> 0.267</td> <td>-4.97e+04</td> <td> 1.38e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Database marketing</th>                                               <td>-2.286e+04</td> <td> 1.15e+04</td> <td>   -1.992</td> <td> 0.047</td> <td>-4.54e+04</td> <td> -312.574</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Construction</th>                                                     <td>-1.499e+04</td> <td> 7388.625</td> <td>   -2.029</td> <td> 0.043</td> <td>-2.95e+04</td> <td> -472.920</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Construction management software</th>                                 <td>  727.0345</td> <td> 5932.402</td> <td>    0.123</td> <td> 0.903</td> <td>-1.09e+04</td> <td> 1.24e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ProCore</th>                                                          <td>  727.0345</td> <td> 5932.402</td> <td>    0.123</td> <td> 0.903</td> <td>-1.09e+04</td> <td> 1.24e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Test-driven development</th>                                          <td>-1.429e+04</td> <td>  1.1e+04</td> <td>   -1.305</td> <td> 0.193</td> <td>-3.58e+04</td> <td> 7230.656</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Cloud infrastructure</th>                                             <td>-4.807e+04</td> <td> 1.42e+04</td> <td>   -3.378</td> <td> 0.001</td> <td> -7.6e+04</td> <td>-2.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Robotics</th>                                                         <td> 5.832e+04</td> <td> 3.68e+04</td> <td>    1.586</td> <td> 0.113</td> <td>-1.39e+04</td> <td> 1.31e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>System architecture</th>                                              <td>-4.566e+04</td> <td> 1.87e+04</td> <td>   -2.448</td> <td> 0.015</td> <td>-8.23e+04</td> <td>-9012.225</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Packaging</th>                                                        <td>-4.115e+04</td> <td> 1.28e+04</td> <td>   -3.220</td> <td> 0.001</td> <td>-6.63e+04</td> <td> -1.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Customer relationship management</th>                                 <td>-5752.1427</td> <td> 1.36e+04</td> <td>   -0.423</td> <td> 0.673</td> <td>-3.25e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sales</th>                                                            <td> 3.944e+04</td> <td> 1.45e+04</td> <td>    2.720</td> <td> 0.007</td> <td>  1.1e+04</td> <td> 6.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Data science</th>                                                     <td>  5.79e+04</td> <td> 1.53e+04</td> <td>    3.783</td> <td> 0.000</td> <td> 2.78e+04</td> <td>  8.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SOAP</th>                                                             <td>-4.817e+04</td> <td> 1.31e+04</td> <td>   -3.675</td> <td> 0.000</td> <td>-7.39e+04</td> <td>-2.24e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Assembly</th>                                                         <td>-8714.1508</td> <td> 7228.193</td> <td>   -1.206</td> <td> 0.229</td> <td>-2.29e+04</td> <td> 5488.659</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Encryption</th>                                                       <td>-8714.1508</td> <td> 7228.193</td> <td>   -1.206</td> <td> 0.229</td> <td>-2.29e+04</td> <td> 5488.659</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SPARQL</th>                                                           <td> 9104.2128</td> <td> 1.47e+04</td> <td>    0.619</td> <td> 0.536</td> <td>-1.98e+04</td> <td>  3.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ServiceNow</th>                                                       <td> 9841.5713</td> <td> 1.41e+04</td> <td>    0.697</td> <td> 0.486</td> <td>-1.79e+04</td> <td> 3.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Taxonomy</th>                                                         <td> -3.88e+04</td> <td> 1.19e+04</td> <td>   -3.270</td> <td> 0.001</td> <td>-6.21e+04</td> <td>-1.55e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Oracle</th>                                                           <td>-4.688e+04</td> <td> 1.47e+04</td> <td>   -3.190</td> <td> 0.002</td> <td>-7.57e+04</td> <td> -1.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Doctor of Dentistry</th>                                              <td>-3.643e+04</td> <td> 1.49e+04</td> <td>   -2.437</td> <td> 0.015</td> <td>-6.58e+04</td> <td>-7057.174</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>VMWare</th>                                                           <td>-3.393e+04</td> <td> 1.99e+04</td> <td>   -1.707</td> <td> 0.088</td> <td> -7.3e+04</td> <td> 5118.595</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Database administration</th>                                          <td>-3.935e+04</td> <td> 1.12e+04</td> <td>   -3.522</td> <td> 0.000</td> <td>-6.13e+04</td> <td>-1.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Clinical development</th>                                             <td>-1.144e+04</td> <td> 6195.451</td> <td>   -1.846</td> <td> 0.066</td> <td>-2.36e+04</td> <td>  738.014</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CDISC standards</th>                                                  <td>-1.144e+04</td> <td> 6195.451</td> <td>   -1.846</td> <td> 0.066</td> <td>-2.36e+04</td> <td>  738.014</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Microscopy</th>                                                       <td>-1.297e+04</td> <td> 1.73e+04</td> <td>   -0.751</td> <td> 0.453</td> <td>-4.69e+04</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Spectroscopy</th>                                                     <td>-4330.4984</td> <td> 1.31e+04</td> <td>   -0.331</td> <td> 0.741</td> <td>-3.01e+04</td> <td> 2.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>SoC</th>                                                              <td>-3438.5079</td> <td> 1.08e+04</td> <td>   -0.317</td> <td> 0.751</td> <td>-2.47e+04</td> <td> 1.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>GLP</th>                                                              <td> 5068.1305</td> <td> 7459.262</td> <td>    0.679</td> <td> 0.497</td> <td>-9588.711</td> <td> 1.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>CGMP</th>                                                             <td> 5068.1305</td> <td> 7459.262</td> <td>    0.679</td> <td> 0.497</td> <td>-9588.711</td> <td> 1.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Bootstrap</th>                                                        <td> 1.706e+04</td> <td> 1.54e+04</td> <td>    1.105</td> <td> 0.270</td> <td>-1.33e+04</td> <td> 4.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lending</th>                                                          <td> 2.504e+04</td> <td> 2.47e+04</td> <td>    1.014</td> <td> 0.311</td> <td>-2.35e+04</td> <td> 7.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Grant writing</th>                                                    <td>-1.573e+04</td> <td> 1.24e+04</td> <td>   -1.273</td> <td> 0.204</td> <td>   -4e+04</td> <td> 8541.245</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pass polygraph test</th>                                              <td>-1.185e+04</td> <td> 8604.348</td> <td>   -1.377</td> <td> 0.169</td> <td>-2.88e+04</td> <td> 5054.629</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Pivot tables</th>                                                     <td> -1.36e+04</td> <td> 7359.387</td> <td>   -1.847</td> <td> 0.065</td> <td>-2.81e+04</td> <td>  864.448</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Editing</th>                                                          <td>-3331.1732</td> <td> 1.29e+04</td> <td>   -0.259</td> <td> 0.796</td> <td>-2.86e+04</td> <td> 2.19e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Data Analyst</th>                                               <td>-1.336e+04</td> <td> 8174.274</td> <td>   -1.634</td> <td> 0.103</td> <td>-2.94e+04</td> <td> 2706.037</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Data Architect</th>                                             <td>  5.92e+04</td> <td> 1.41e+04</td> <td>    4.199</td> <td> 0.000</td> <td> 3.15e+04</td> <td> 8.69e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Data Engineer</th>                                              <td> 3.297e+04</td> <td> 8256.950</td> <td>    3.994</td> <td> 0.000</td> <td> 1.68e+04</td> <td> 4.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Data Science Manager</th>                                       <td> 4.683e+04</td> <td> 6082.849</td> <td>    7.698</td> <td> 0.000</td> <td> 3.49e+04</td> <td> 5.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Data Scientist</th>                                             <td> 1.981e+04</td> <td> 5216.060</td> <td>    3.798</td> <td> 0.000</td> <td> 9559.705</td> <td> 3.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Director of Data Science</th>                                   <td> 7.062e+04</td> <td> 9501.931</td> <td>    7.432</td> <td> 0.000</td> <td> 5.19e+04</td> <td> 8.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Head of Data Science</th>                                       <td> 3.694e+04</td> <td> 1.18e+04</td> <td>    3.119</td> <td> 0.002</td> <td> 1.37e+04</td> <td> 6.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Machine Learning Engineer</th>                                  <td> 2.455e+04</td> <td> 5643.537</td> <td>    4.350</td> <td> 0.000</td> <td> 1.35e+04</td> <td> 3.56e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Machine Learning Scientist</th>                                 <td> 8155.6580</td> <td> 6109.121</td> <td>    1.335</td> <td> 0.183</td> <td>-3848.266</td> <td> 2.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Software Engineer</th>                                          <td> 3.104e+04</td> <td> 6487.497</td> <td>    4.785</td> <td> 0.000</td> <td> 1.83e+04</td> <td> 4.38e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Statistician</th>                                               <td>-2.757e+04</td> <td> 2.04e+04</td> <td>   -1.352</td> <td> 0.177</td> <td>-6.76e+04</td> <td> 1.25e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Title_Vice President of Data Science</th>                             <td> 4.164e+04</td> <td> 1.41e+04</td> <td>    2.947</td> <td> 0.003</td> <td> 1.39e+04</td> <td> 6.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_3T Biosciences</th>                                           <td>-3.162e+04</td> <td> 2.08e+04</td> <td>   -1.520</td> <td> 0.129</td> <td>-7.25e+04</td> <td> 9255.740</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_6sense</th>                                                   <td>-6.759e+04</td> <td> 2.49e+04</td> <td>   -2.710</td> <td> 0.007</td> <td>-1.17e+05</td> <td>-1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_8th Wall</th>                                                 <td>-4.048e+04</td> <td>  1.3e+04</td> <td>   -3.114</td> <td> 0.002</td> <td> -6.6e+04</td> <td>-1.49e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_99</th>                                                       <td>-2.637e+04</td> <td> 2.24e+04</td> <td>   -1.179</td> <td> 0.239</td> <td>-7.03e+04</td> <td> 1.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ABB</th>                                                      <td>-4.534e+04</td> <td> 1.52e+04</td> <td>   -2.974</td> <td> 0.003</td> <td>-7.53e+04</td> <td>-1.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AE Studio</th>                                                <td>-5752.1427</td> <td> 1.36e+04</td> <td>   -0.423</td> <td> 0.673</td> <td>-3.25e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ASML</th>                                                     <td>-8739.5431</td> <td> 8243.187</td> <td>   -1.060</td> <td> 0.290</td> <td>-2.49e+04</td> <td> 7457.648</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AT&T</th>                                                     <td>-4.778e+04</td> <td> 2.43e+04</td> <td>   -1.966</td> <td> 0.050</td> <td>-9.55e+04</td> <td>  -30.601</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AWM Smart Shelf (Adroit Worldwide Media, Inc.)</th>           <td>-6.136e+04</td> <td> 3.47e+04</td> <td>   -1.769</td> <td> 0.078</td> <td> -1.3e+05</td> <td> 6796.320</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Abacus.ai</th>                                                <td>-6.424e+04</td> <td> 2.39e+04</td> <td>   -2.692</td> <td> 0.007</td> <td>-1.11e+05</td> <td>-1.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Abbott Laboratories</th>                                      <td>-2.145e+04</td> <td> 9909.512</td> <td>   -2.165</td> <td> 0.031</td> <td>-4.09e+04</td> <td>-1982.639</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Abl Schools</th>                                              <td>-5.138e+04</td> <td> 2.33e+04</td> <td>   -2.204</td> <td> 0.028</td> <td>-9.72e+04</td> <td>-5569.933</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Abnormal Security</th>                                        <td>-7.217e+04</td> <td> 2.34e+04</td> <td>   -3.080</td> <td> 0.002</td> <td>-1.18e+05</td> <td>-2.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Accenture</th>                                                <td> 1.322e+04</td> <td> 2.63e+04</td> <td>    0.502</td> <td> 0.616</td> <td>-3.85e+04</td> <td>  6.5e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Accion Opportunity Fund</th>                                  <td>-8.355e+04</td> <td>  2.5e+04</td> <td>   -3.348</td> <td> 0.001</td> <td>-1.33e+05</td> <td>-3.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Activision</th>                                               <td>  -2.4e+04</td> <td> 2.37e+04</td> <td>   -1.013</td> <td> 0.312</td> <td>-7.06e+04</td> <td> 2.26e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Adobe</th>                                                    <td> 1.714e+04</td> <td> 1.55e+04</td> <td>    1.109</td> <td> 0.268</td> <td>-1.32e+04</td> <td> 4.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Afresh</th>                                                   <td> -1.44e+04</td> <td> 1.78e+04</td> <td>   -0.809</td> <td> 0.419</td> <td>-4.94e+04</td> <td> 2.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Afterpay Touch</th>                                           <td>-3.737e+04</td> <td> 2.12e+04</td> <td>   -1.759</td> <td> 0.079</td> <td>-7.91e+04</td> <td> 4362.577</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Agilent Technologies, Inc.</th>                               <td>-4.432e+04</td> <td> 2.57e+04</td> <td>   -1.725</td> <td> 0.085</td> <td>-9.48e+04</td> <td> 6175.062</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AiCard</th>                                                   <td> 1.981e+05</td> <td> 2.25e+04</td> <td>    8.789</td> <td> 0.000</td> <td> 1.54e+05</td> <td> 2.42e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Airtable</th>                                                 <td>-2.838e+04</td> <td> 1.19e+04</td> <td>   -2.387</td> <td> 0.017</td> <td>-5.17e+04</td> <td>-5018.061</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aisera</th>                                                   <td> 9841.5713</td> <td> 1.41e+04</td> <td>    0.697</td> <td> 0.486</td> <td>-1.79e+04</td> <td> 3.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Akamai</th>                                                   <td> -2.55e+04</td> <td> 2.41e+04</td> <td>   -1.057</td> <td> 0.291</td> <td>-7.29e+04</td> <td> 2.19e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Albertsons Companies</th>                                     <td>-7531.8663</td> <td> 2.91e+04</td> <td>   -0.259</td> <td> 0.796</td> <td>-6.48e+04</td> <td> 4.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AlignTech</th>                                                <td>-1.028e+04</td> <td> 2.54e+04</td> <td>   -0.405</td> <td> 0.686</td> <td>-6.02e+04</td> <td> 3.96e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Allbirds</th>                                                 <td>-8.067e+04</td> <td> 2.59e+04</td> <td>   -3.114</td> <td> 0.002</td> <td>-1.32e+05</td> <td>-2.98e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Amazon Dev Center U.S., Inc.</th>                             <td> 2.603e+04</td> <td> 2.62e+04</td> <td>    0.994</td> <td> 0.321</td> <td>-2.54e+04</td> <td> 7.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Amazon Web Services, Inc.</th>                                <td>-6.955e+04</td> <td> 2.28e+04</td> <td>   -3.044</td> <td> 0.002</td> <td>-1.14e+05</td> <td>-2.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Amazon.com Services LLC</th>                                  <td>-1988.5332</td> <td> 2.12e+04</td> <td>   -0.094</td> <td> 0.925</td> <td>-4.36e+04</td> <td> 3.96e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Amgen</th>                                                    <td> 3.022e+04</td> <td> 1.25e+04</td> <td>    2.411</td> <td> 0.016</td> <td> 5589.395</td> <td> 5.49e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Amino, Inc.</th>                                              <td>-2.466e+04</td> <td>  2.4e+04</td> <td>   -1.027</td> <td> 0.305</td> <td>-7.19e+04</td> <td> 2.25e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Anthem</th>                                                   <td>-2.947e+04</td> <td> 2.65e+04</td> <td>   -1.112</td> <td> 0.267</td> <td>-8.16e+04</td> <td> 2.26e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Apartment List</th>                                           <td>-4.566e+04</td> <td> 2.41e+04</td> <td>   -1.893</td> <td> 0.059</td> <td> -9.3e+04</td> <td> 1725.480</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_App Annie</th>                                                <td>-2.965e+04</td> <td> 2.71e+04</td> <td>   -1.096</td> <td> 0.274</td> <td>-8.28e+04</td> <td> 2.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aquabyte</th>                                                 <td>-6.403e+04</td> <td> 2.39e+04</td> <td>   -2.677</td> <td> 0.008</td> <td>-1.11e+05</td> <td> -1.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aquent</th>                                                   <td>-3062.2987</td> <td> 1.34e+04</td> <td>   -0.229</td> <td> 0.819</td> <td>-2.93e+04</td> <td> 2.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Arcules, Inc.</th>                                            <td>-9.803e+04</td> <td> 2.41e+04</td> <td>   -4.072</td> <td> 0.000</td> <td>-1.45e+05</td> <td>-5.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Argo AI</th>                                                  <td>-3.997e+04</td> <td> 2.43e+04</td> <td>   -1.645</td> <td> 0.101</td> <td>-8.77e+04</td> <td> 7784.065</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ariat International</th>                                      <td> 9949.9272</td> <td> 5554.826</td> <td>    1.791</td> <td> 0.074</td> <td> -964.852</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Artizen, Inc.</th>                                            <td>-4.522e+04</td> <td> 2.94e+04</td> <td>   -1.540</td> <td> 0.124</td> <td>-1.03e+05</td> <td> 1.25e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aruba Networks</th>                                           <td>-8481.8936</td> <td> 2.58e+04</td> <td>   -0.329</td> <td> 0.742</td> <td>-5.91e+04</td> <td> 4.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ask Media Group</th>                                          <td>-3.519e+04</td> <td> 1.87e+04</td> <td>   -1.883</td> <td> 0.060</td> <td>-7.19e+04</td> <td> 1536.395</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AstraZeneca</th>                                              <td>-3.306e+04</td> <td> 1.31e+04</td> <td>   -2.517</td> <td> 0.012</td> <td>-5.89e+04</td> <td>-7247.703</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Atlassian</th>                                                <td> 1.083e+04</td> <td> 2.78e+04</td> <td>    0.389</td> <td> 0.697</td> <td>-4.38e+04</td> <td> 6.55e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Atomic AI</th>                                                <td> 3.616e+04</td> <td> 1.28e+04</td> <td>    2.814</td> <td> 0.005</td> <td> 1.09e+04</td> <td> 6.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Atomwise</th>                                                 <td>-4.336e+04</td> <td> 2.42e+04</td> <td>   -1.791</td> <td> 0.074</td> <td>-9.09e+04</td> <td> 4208.889</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Atreca</th>                                                   <td>-5.268e+04</td> <td> 2.11e+04</td> <td>   -2.500</td> <td> 0.013</td> <td>-9.41e+04</td> <td>-1.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aurora</th>                                                   <td>-4.516e+04</td> <td> 2.26e+04</td> <td>   -1.994</td> <td> 0.047</td> <td>-8.97e+04</td> <td> -665.737</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aurora Innovation</th>                                        <td>-7.096e+04</td> <td> 2.04e+04</td> <td>   -3.483</td> <td> 0.001</td> <td>-1.11e+05</td> <td>-3.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Auryc</th>                                                    <td>-1.838e+04</td> <td> 1.43e+04</td> <td>   -1.288</td> <td> 0.198</td> <td>-4.64e+04</td> <td> 9666.262</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_AutoX Inc</th>                                                <td>-2.432e+04</td> <td>  2.5e+04</td> <td>   -0.974</td> <td> 0.331</td> <td>-7.34e+04</td> <td> 2.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Automat Solutions, Inc.</th>                                  <td> 1.211e+04</td> <td>  1.4e+04</td> <td>    0.863</td> <td> 0.388</td> <td>-1.55e+04</td> <td> 3.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Avanade</th>                                                  <td>-2.371e+04</td> <td> 2.84e+04</td> <td>   -0.835</td> <td> 0.404</td> <td>-7.95e+04</td> <td> 3.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aven</th>                                                     <td>-4036.1577</td> <td> 5456.295</td> <td>   -0.740</td> <td> 0.460</td> <td>-1.48e+04</td> <td> 6685.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Aviatrix</th>                                                 <td>-1.783e+04</td> <td> 1.35e+04</td> <td>   -1.324</td> <td> 0.186</td> <td>-4.43e+04</td> <td> 8629.342</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Avila Trading</th>                                            <td>-3.348e+04</td> <td> 2.41e+04</td> <td>   -1.388</td> <td> 0.166</td> <td>-8.09e+04</td> <td> 1.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BBI</th>                                                      <td>-2.147e+04</td> <td> 5056.241</td> <td>   -4.247</td> <td> 0.000</td> <td>-3.14e+04</td> <td>-1.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BICP</th>                                                     <td>-5.143e+04</td> <td> 2.36e+04</td> <td>   -2.180</td> <td> 0.030</td> <td>-9.78e+04</td> <td>-5079.741</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BOEING</th>                                                   <td>-8.475e+04</td> <td> 2.63e+04</td> <td>   -3.226</td> <td> 0.001</td> <td>-1.36e+05</td> <td>-3.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BOLD</th>                                                     <td>-9427.4657</td> <td>    2e+04</td> <td>   -0.471</td> <td> 0.638</td> <td>-4.88e+04</td> <td> 2.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BXGI</th>                                                     <td>-2.379e+04</td> <td> 2.54e+04</td> <td>   -0.935</td> <td> 0.350</td> <td>-7.38e+04</td> <td> 2.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Baidu USA</th>                                                <td>-1.707e+04</td> <td> 2.36e+04</td> <td>   -0.723</td> <td> 0.470</td> <td>-6.34e+04</td> <td> 2.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Bayer</th>                                                    <td>-4.822e+04</td> <td> 2.45e+04</td> <td>   -1.970</td> <td> 0.049</td> <td>-9.63e+04</td> <td> -122.784</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Belcan</th>                                                   <td>-4.111e+04</td> <td> 1.35e+04</td> <td>   -3.039</td> <td> 0.003</td> <td>-6.77e+04</td> <td>-1.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Big Data Federation, Inc.</th>                                <td>  -5.2e+04</td> <td> 2.76e+04</td> <td>   -1.882</td> <td> 0.060</td> <td>-1.06e+05</td> <td> 2291.965</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Black Sesame Technologies Inc</th>                            <td>-5.183e+04</td> <td>  2.4e+04</td> <td>   -2.164</td> <td> 0.031</td> <td>-9.89e+04</td> <td>-4759.651</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BlackBerry</th>                                               <td>-1.119e+04</td> <td> 1.62e+04</td> <td>   -0.690</td> <td> 0.491</td> <td>-4.31e+04</td> <td> 2.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Blink Health</th>                                             <td>-3.705e+04</td> <td> 2.37e+04</td> <td>   -1.566</td> <td> 0.118</td> <td>-8.36e+04</td> <td> 9448.627</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Blockchain.com</th>                                           <td> 3224.5817</td> <td> 2.42e+04</td> <td>    0.133</td> <td> 0.894</td> <td>-4.44e+04</td> <td> 5.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Blue River Technology</th>                                    <td>-3.052e+04</td> <td> 1.82e+04</td> <td>   -1.674</td> <td> 0.095</td> <td>-6.63e+04</td> <td> 5297.584</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Bosch Group</th>                                              <td>-3427.9600</td> <td> 4.16e+04</td> <td>   -0.082</td> <td> 0.934</td> <td>-8.51e+04</td> <td> 7.83e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_BrainChip, Inc.</th>                                          <td>-3438.5079</td> <td> 1.08e+04</td> <td>   -0.317</td> <td> 0.751</td> <td>-2.47e+04</td> <td> 1.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Brambles Group</th>                                           <td>-1.009e+04</td> <td> 2.49e+04</td> <td>   -0.405</td> <td> 0.686</td> <td> -5.9e+04</td> <td> 3.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Brightline</th>                                               <td>-1.164e+04</td> <td> 9732.149</td> <td>   -1.196</td> <td> 0.232</td> <td>-3.08e+04</td> <td> 7482.174</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Bristol Myers Squibb</th>                                     <td> 1.492e+04</td> <td> 1.69e+04</td> <td>    0.880</td> <td> 0.379</td> <td>-1.84e+04</td> <td> 4.82e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ByteDance</th>                                                <td>-3.201e+04</td> <td>    2e+04</td> <td>   -1.599</td> <td> 0.111</td> <td>-7.14e+04</td> <td> 7333.794</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_C3 AI</th>                                                    <td> 2.491e+04</td> <td> 1.36e+04</td> <td>    1.826</td> <td> 0.068</td> <td>-1887.799</td> <td> 5.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CEDENT</th>                                                   <td>-4.821e+04</td> <td> 2.37e+04</td> <td>   -2.034</td> <td> 0.042</td> <td>-9.48e+04</td> <td>-1639.100</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CHEP</th>                                                     <td>-3.355e+04</td> <td> 2.62e+04</td> <td>   -1.283</td> <td> 0.200</td> <td>-8.49e+04</td> <td> 1.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CaaStle</th>                                                  <td>-2.321e+04</td> <td>  2.5e+04</td> <td>   -0.930</td> <td> 0.353</td> <td>-7.23e+04</td> <td> 2.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CalPrivate Bank</th>                                          <td>-3.964e+04</td> <td> 8853.520</td> <td>   -4.478</td> <td> 0.000</td> <td> -5.7e+04</td> <td>-2.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Calico</th>                                                   <td> 1.488e+04</td> <td> 1.23e+04</td> <td>    1.208</td> <td> 0.227</td> <td>-9313.089</td> <td> 3.91e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_California Institute of Technology</th>                       <td>-3.888e+04</td> <td> 4.17e+04</td> <td>   -0.933</td> <td> 0.351</td> <td>-1.21e+05</td> <td>  4.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cameo</th>                                                    <td>-4.536e+04</td> <td> 2.37e+04</td> <td>   -1.915</td> <td> 0.056</td> <td>-9.19e+04</td> <td> 1194.220</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Capella Space</th>                                            <td>-3.011e+04</td> <td> 2.35e+04</td> <td>   -1.282</td> <td> 0.200</td> <td>-7.62e+04</td> <td>  1.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cardlytics</th>                                               <td> 2.033e+04</td> <td> 2.76e+04</td> <td>    0.736</td> <td> 0.462</td> <td>-3.39e+04</td> <td> 7.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CareDx</th>                                                   <td>-3787.7316</td> <td> 9219.559</td> <td>   -0.411</td> <td> 0.681</td> <td>-2.19e+04</td> <td> 1.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cash App</th>                                                 <td>-5.371e+04</td> <td> 2.21e+04</td> <td>   -2.434</td> <td> 0.015</td> <td>-9.71e+04</td> <td>-1.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Centene Corporation</th>                                      <td>-2.201e+04</td> <td> 1.12e+04</td> <td>   -1.970</td> <td> 0.049</td> <td> -4.4e+04</td> <td>  -53.344</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cepheid</th>                                                  <td> 6324.0355</td> <td> 1.28e+04</td> <td>    0.494</td> <td> 0.621</td> <td>-1.88e+04</td> <td> 3.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Chan Zuckerberg Initiative</th>                               <td>-1.648e+04</td> <td> 2.45e+04</td> <td>   -0.673</td> <td> 0.502</td> <td>-6.46e+04</td> <td> 3.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Checkmate Partners</th>                                       <td> 7.157e+04</td> <td> 2.49e+04</td> <td>    2.871</td> <td> 0.004</td> <td> 2.26e+04</td> <td> 1.21e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Chime</th>                                                    <td>-7.563e+04</td> <td> 2.49e+04</td> <td>   -3.033</td> <td> 0.003</td> <td>-1.25e+05</td> <td>-2.66e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Chronus Health, Inc.</th>                                     <td>-1.862e+04</td> <td> 8260.763</td> <td>   -2.254</td> <td> 0.025</td> <td>-3.48e+04</td> <td>-2384.764</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Circle</th>                                                   <td>-1.294e+05</td> <td> 3.09e+04</td> <td>   -4.186</td> <td> 0.000</td> <td> -1.9e+05</td> <td>-6.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cisco Meraki</th>                                             <td>-4.316e+04</td> <td> 2.21e+04</td> <td>   -1.956</td> <td> 0.051</td> <td>-8.65e+04</td> <td>  201.230</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_City of Hope</th>                                             <td>-7.542e+04</td> <td> 2.29e+04</td> <td>   -3.297</td> <td> 0.001</td> <td> -1.2e+05</td> <td>-3.05e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Clarify Health Solutions.</th>                                <td> -7.72e+04</td> <td> 2.74e+04</td> <td>   -2.820</td> <td> 0.005</td> <td>-1.31e+05</td> <td>-2.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Clarivate Analytics</th>                                      <td>-3.083e+04</td> <td> 1.23e+04</td> <td>   -2.511</td> <td> 0.012</td> <td> -5.5e+04</td> <td>-6706.413</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ClassDojo</th>                                                <td>-4.498e+04</td> <td>  2.4e+04</td> <td>   -1.870</td> <td> 0.062</td> <td>-9.22e+04</td> <td> 2272.762</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ClimateAI</th>                                                <td> 4413.6291</td> <td> 9546.053</td> <td>    0.462</td> <td> 0.644</td> <td>-1.43e+04</td> <td> 2.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Clinical Management Consultants</th>                          <td>-1.673e+04</td> <td> 1.22e+04</td> <td>   -1.366</td> <td> 0.173</td> <td>-4.08e+04</td> <td> 7334.022</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cloudleaf</th>                                                <td>-6.025e+04</td> <td> 2.72e+04</td> <td>   -2.216</td> <td> 0.027</td> <td>-1.14e+05</td> <td>-6834.425</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cloudwick</th>                                                <td> -1.83e+04</td> <td> 9614.694</td> <td>   -1.903</td> <td> 0.058</td> <td>-3.72e+04</td> <td>  595.963</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cobalt Robotics</th>                                          <td>-5.044e+04</td> <td> 2.91e+04</td> <td>   -1.731</td> <td> 0.084</td> <td>-1.08e+05</td> <td> 6820.418</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Coda</th>                                                     <td>-2.305e+04</td> <td> 2.53e+04</td> <td>   -0.911</td> <td> 0.363</td> <td>-7.28e+04</td> <td> 2.67e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cogitativo</th>                                               <td>-5.265e+04</td> <td> 1.77e+04</td> <td>   -2.967</td> <td> 0.003</td> <td>-8.75e+04</td> <td>-1.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Colsh Consultants</th>                                        <td>-4.497e+04</td> <td> 2.51e+04</td> <td>   -1.793</td> <td> 0.074</td> <td>-9.43e+04</td> <td> 4302.979</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Convex Tech</th>                                              <td>-1.787e+05</td> <td> 2.35e+04</td> <td>   -7.590</td> <td> 0.000</td> <td>-2.25e+05</td> <td>-1.32e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CooTek</th>                                                   <td>-1.108e+05</td> <td> 2.41e+04</td> <td>   -4.592</td> <td> 0.000</td> <td>-1.58e+05</td> <td>-6.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Course Hero</th>                                              <td>-4.451e+04</td> <td> 1.61e+04</td> <td>   -2.772</td> <td> 0.006</td> <td>-7.61e+04</td> <td> -1.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cowbell Cyber Inc.</th>                                       <td>  -2.3e+04</td> <td> 2.52e+04</td> <td>   -0.914</td> <td> 0.361</td> <td>-7.25e+04</td> <td> 2.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cox Automotive</th>                                           <td>-2.563e+04</td> <td> 1.25e+04</td> <td>   -2.047</td> <td> 0.041</td> <td>-5.02e+04</td> <td>-1032.471</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Cox Communications Inc</th>                                   <td>-2.543e+04</td> <td> 2.71e+04</td> <td>   -0.939</td> <td> 0.348</td> <td>-7.87e+04</td> <td> 2.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Credible</th>                                                 <td>-2.516e+04</td> <td> 1.37e+04</td> <td>   -1.843</td> <td> 0.066</td> <td> -5.2e+04</td> <td> 1665.455</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Crossover Health</th>                                         <td>-3.688e+04</td> <td> 9331.674</td> <td>   -3.952</td> <td> 0.000</td> <td>-5.52e+04</td> <td>-1.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CrowdRise</th>                                                <td>  1.74e+04</td> <td>  1.2e+04</td> <td>    1.454</td> <td> 0.147</td> <td>-6121.283</td> <td> 4.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CyberCoders</th>                                              <td>-3.006e+04</td> <td> 2.23e+04</td> <td>   -1.346</td> <td> 0.179</td> <td> -7.4e+04</td> <td> 1.38e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_CyberCube</th>                                                <td>-7.582e+04</td> <td> 2.44e+04</td> <td>   -3.105</td> <td> 0.002</td> <td>-1.24e+05</td> <td>-2.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DG Savants</th>                                               <td>-6.208e+04</td> <td> 1.87e+04</td> <td>   -3.325</td> <td> 0.001</td> <td>-9.88e+04</td> <td>-2.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Databricks</th>                                               <td>-6.377e+04</td> <td> 2.46e+04</td> <td>   -2.592</td> <td> 0.010</td> <td>-1.12e+05</td> <td>-1.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Datatron Technologies</th>                                    <td>-6.534e+04</td> <td> 2.95e+04</td> <td>   -2.213</td> <td> 0.027</td> <td>-1.23e+05</td> <td>-7316.272</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Decipher Biosciences</th>                                     <td>-3.179e+04</td> <td> 2.61e+04</td> <td>   -1.217</td> <td> 0.224</td> <td>-8.31e+04</td> <td> 1.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DecisionLogic</th>                                            <td>-7750.7256</td> <td>    2e+04</td> <td>   -0.387</td> <td> 0.699</td> <td>-4.71e+04</td> <td> 3.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DeepMap, Inc</th>                                             <td>-2.012e+04</td> <td> 3.04e+04</td> <td>   -0.662</td> <td> 0.508</td> <td>-7.99e+04</td> <td> 3.96e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DeepVu</th>                                                   <td> -6.81e+04</td> <td> 1.86e+04</td> <td>   -3.663</td> <td> 0.000</td> <td>-1.05e+05</td> <td>-3.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Denali Therapeutics</th>                                      <td>-1.144e+04</td> <td> 6195.451</td> <td>   -1.846</td> <td> 0.066</td> <td>-2.36e+04</td> <td>  738.014</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Dermalogica LLC</th>                                          <td> 1173.3650</td> <td> 8888.642</td> <td>    0.132</td> <td> 0.895</td> <td>-1.63e+04</td> <td> 1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Deserve, Inc.</th>                                            <td>-5.504e+04</td> <td> 2.48e+04</td> <td>   -2.219</td> <td> 0.027</td> <td>-1.04e+05</td> <td>-6291.428</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Dexcom</th>                                                   <td> 3.588e+04</td> <td>  3.1e+04</td> <td>    1.156</td> <td> 0.248</td> <td>-2.51e+04</td> <td> 9.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DiDi Labs</th>                                                <td>-5.016e+04</td> <td> 3.08e+04</td> <td>   -1.628</td> <td> 0.104</td> <td>-1.11e+05</td> <td> 1.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Diffbot</th>                                                  <td>-3.057e+04</td> <td> 3.11e+04</td> <td>   -0.982</td> <td> 0.326</td> <td>-9.17e+04</td> <td> 3.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Discord</th>                                                  <td>-3.788e+04</td> <td> 2.22e+04</td> <td>   -1.710</td> <td> 0.088</td> <td>-8.14e+04</td> <td> 5647.257</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Disney Media & Entertainment Distribution</th>                <td>-2961.1954</td> <td> 2.67e+04</td> <td>   -0.111</td> <td> 0.912</td> <td>-5.55e+04</td> <td> 4.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_DocuSign</th>                                                 <td>-2.377e+04</td> <td> 2.24e+04</td> <td>   -1.062</td> <td> 0.289</td> <td>-6.77e+04</td> <td> 2.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Dollar Shave Club</th>                                        <td>  370.1971</td> <td> 9019.919</td> <td>    0.041</td> <td> 0.967</td> <td>-1.74e+04</td> <td> 1.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Doma</th>                                                     <td>-3.653e+04</td> <td>  2.2e+04</td> <td>   -1.663</td> <td> 0.097</td> <td>-7.97e+04</td> <td> 6619.975</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Dropbox</th>                                                  <td>-6.657e+04</td> <td> 2.37e+04</td> <td>   -2.808</td> <td> 0.005</td> <td>-1.13e+05</td> <td>   -2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Dynamic Solutions Technology LLC</th>                         <td> 1.238e+04</td> <td> 2.23e+04</td> <td>    0.554</td> <td> 0.579</td> <td>-3.15e+04</td> <td> 5.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_E. & J. Gallo Winery</th>                                     <td>-5.495e+04</td> <td> 1.23e+04</td> <td>   -4.471</td> <td> 0.000</td> <td>-7.91e+04</td> <td>-3.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_EDO, Inc</th>                                                 <td>   69.4623</td> <td> 1.03e+04</td> <td>    0.007</td> <td> 0.995</td> <td>-2.02e+04</td> <td> 2.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ELT Solutions</th>                                            <td>-4.532e+04</td> <td> 2.51e+04</td> <td>   -1.803</td> <td> 0.072</td> <td>-9.47e+04</td> <td> 4063.063</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ENERGY SOLUTIONS</th>                                         <td>-1.868e+04</td> <td> 8721.855</td> <td>   -2.141</td> <td> 0.033</td> <td>-3.58e+04</td> <td>-1538.888</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_EVB</th>                                                      <td>-4.384e+04</td> <td> 2.89e+04</td> <td>   -1.517</td> <td> 0.130</td> <td>-1.01e+05</td> <td> 1.29e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Earnin</th>                                                   <td> -3.87e+04</td> <td> 2.42e+04</td> <td>   -1.598</td> <td> 0.111</td> <td>-8.63e+04</td> <td> 8890.259</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_EasyPost</th>                                                 <td>-2.582e+04</td> <td> 2.72e+04</td> <td>   -0.949</td> <td> 0.343</td> <td>-7.93e+04</td> <td> 2.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Edmunds.com</th>                                              <td>-4.115e+04</td> <td> 1.28e+04</td> <td>   -3.220</td> <td> 0.001</td> <td>-6.63e+04</td> <td> -1.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Edwards Lifesciences</th>                                     <td> 8700.4958</td> <td> 2.48e+04</td> <td>    0.351</td> <td> 0.726</td> <td>-4.01e+04</td> <td> 5.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Electronic Arts</th>                                          <td>-2.114e+04</td> <td> 1.32e+04</td> <td>   -1.601</td> <td> 0.110</td> <td>-4.71e+04</td> <td> 4809.688</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Empower Retirement</th>                                       <td>-1.562e+04</td> <td> 2.55e+04</td> <td>   -0.612</td> <td> 0.541</td> <td>-6.57e+04</td> <td> 3.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Engage3</th>                                                  <td>-5959.4671</td> <td> 9510.032</td> <td>   -0.627</td> <td> 0.531</td> <td>-2.46e+04</td> <td> 1.27e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Envision</th>                                                 <td>-2.512e+04</td> <td> 1.72e+04</td> <td>   -1.460</td> <td> 0.145</td> <td>-5.89e+04</td> <td> 8692.150</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ericsson</th>                                                 <td>-2.843e+04</td> <td> 2.51e+04</td> <td>   -1.131</td> <td> 0.259</td> <td>-7.78e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Essex Property Trust</th>                                     <td>-4.093e+04</td> <td> 1.96e+04</td> <td>   -2.089</td> <td> 0.037</td> <td>-7.94e+04</td> <td>-2435.173</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ethos Life</th>                                               <td>-5.065e+04</td> <td> 2.35e+04</td> <td>   -2.158</td> <td> 0.031</td> <td>-9.68e+04</td> <td>-4523.464</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Evernote</th>                                                 <td>-7.939e+04</td> <td> 2.46e+04</td> <td>   -3.231</td> <td> 0.001</td> <td>-1.28e+05</td> <td>-3.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Evolver. LLC, a CSS Company</th>                              <td>-7.704e+04</td> <td> 1.61e+04</td> <td>   -4.773</td> <td> 0.000</td> <td>-1.09e+05</td> <td>-4.53e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Exagen, Inc.</th>                                             <td>-1.058e+04</td> <td> 1.34e+04</td> <td>   -0.789</td> <td> 0.431</td> <td>-3.69e+04</td> <td> 1.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Exai Bio Inc</th>                                             <td>-5.639e+04</td> <td> 2.75e+04</td> <td>   -2.052</td> <td> 0.041</td> <td> -1.1e+05</td> <td>-2379.987</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Experian</th>                                                 <td>-1.619e+04</td> <td> 7037.100</td> <td>   -2.301</td> <td> 0.022</td> <td>   -3e+04</td> <td>-2362.505</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Exponent</th>                                                 <td>-8.232e+04</td> <td> 2.97e+04</td> <td>   -2.776</td> <td> 0.006</td> <td>-1.41e+05</td> <td>-2.41e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Extend</th>                                                   <td>-2.997e+04</td> <td> 2.21e+04</td> <td>   -1.356</td> <td> 0.176</td> <td>-7.34e+04</td> <td> 1.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ezoic</th>                                                    <td>-3.028e+04</td> <td> 2.12e+04</td> <td>   -1.427</td> <td> 0.154</td> <td> -7.2e+04</td> <td> 1.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Facebook App</th>                                             <td>-6.493e+04</td> <td> 2.26e+04</td> <td>   -2.870</td> <td> 0.004</td> <td>-1.09e+05</td> <td>-2.05e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Faire</th>                                                    <td>-4.212e+04</td> <td> 2.37e+04</td> <td>   -1.775</td> <td> 0.076</td> <td>-8.87e+04</td> <td> 4495.552</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Farmers Insurance Group</th>                                  <td>-1.024e+05</td> <td> 3.42e+04</td> <td>   -2.993</td> <td> 0.003</td> <td> -1.7e+05</td> <td>-3.52e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_FieldLevel</th>                                               <td>-6.005e+04</td> <td> 2.48e+04</td> <td>   -2.418</td> <td> 0.016</td> <td>-1.09e+05</td> <td>-1.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Figure</th>                                                   <td>-5.119e+04</td> <td> 2.71e+04</td> <td>   -1.888</td> <td> 0.060</td> <td>-1.04e+05</td> <td> 2083.996</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_First American</th>                                           <td> -1.96e+04</td> <td> 7977.487</td> <td>   -2.457</td> <td> 0.014</td> <td>-3.53e+04</td> <td>-3928.491</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_First Republic Bank</th>                                      <td>-3.743e+04</td> <td> 2.45e+04</td> <td>   -1.525</td> <td> 0.128</td> <td>-8.57e+04</td> <td> 1.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Fiserv</th>                                                   <td> 4938.4805</td> <td> 2.47e+04</td> <td>    0.200</td> <td> 0.841</td> <td>-4.35e+04</td> <td> 5.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Fisker Inc</th>                                               <td>-3.906e+04</td> <td> 2.44e+04</td> <td>   -1.598</td> <td> 0.111</td> <td>-8.71e+04</td> <td> 8968.354</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Fitbod</th>                                                   <td> -2.08e+04</td> <td> 1.46e+04</td> <td>   -1.425</td> <td> 0.155</td> <td>-4.95e+04</td> <td> 7890.837</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ford Motor Company</th>                                       <td>-2.766e+04</td> <td> 2.64e+04</td> <td>   -1.048</td> <td> 0.295</td> <td>-7.95e+04</td> <td> 2.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_FortressIQ</th>                                               <td>-9.367e+04</td> <td> 2.68e+04</td> <td>   -3.497</td> <td> 0.001</td> <td>-1.46e+05</td> <td> -4.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Forward</th>                                                  <td>-6.015e+04</td> <td>  2.1e+04</td> <td>   -2.871</td> <td> 0.004</td> <td>-1.01e+05</td> <td> -1.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Forward Slope Inc.</th>                                       <td> 1.511e+04</td> <td> 2.72e+04</td> <td>    0.555</td> <td> 0.579</td> <td>-3.84e+04</td> <td> 6.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Foursquare</th>                                               <td>-7346.2718</td> <td> 2.37e+04</td> <td>   -0.310</td> <td> 0.757</td> <td>-5.39e+04</td> <td> 3.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Fox Corporation</th>                                          <td>-8.855e+04</td> <td> 3.16e+04</td> <td>   -2.800</td> <td> 0.005</td> <td>-1.51e+05</td> <td>-2.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Freedom Financial Network</th>                                <td> -7.16e+04</td> <td> 2.72e+04</td> <td>   -2.628</td> <td> 0.009</td> <td>-1.25e+05</td> <td>-1.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Frequence</th>                                                <td> 5618.2757</td> <td> 2.28e+04</td> <td>    0.247</td> <td> 0.805</td> <td>-3.91e+04</td> <td> 5.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_FriendFinder Networks</th>                                    <td>-1.785e+04</td> <td> 1.29e+04</td> <td>   -1.382</td> <td> 0.168</td> <td>-4.32e+04</td> <td> 7525.820</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_GE Corporate</th>                                             <td> 5453.4585</td> <td> 9116.028</td> <td>    0.598</td> <td> 0.550</td> <td>-1.25e+04</td> <td> 2.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Gap Inc.</th>                                                 <td>-7.187e+04</td> <td>  2.4e+04</td> <td>   -2.994</td> <td> 0.003</td> <td>-1.19e+05</td> <td>-2.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Gayathri's Sandbox</th>                                       <td>-1.191e+05</td> <td> 2.66e+04</td> <td>   -4.487</td> <td> 0.000</td> <td>-1.71e+05</td> <td> -6.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Geli</th>                                                     <td>-6.944e+04</td> <td> 2.34e+04</td> <td>   -2.972</td> <td> 0.003</td> <td>-1.15e+05</td> <td>-2.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Genentech</th>                                                <td>-5.416e+04</td> <td>  2.2e+04</td> <td>   -2.467</td> <td> 0.014</td> <td>-9.73e+04</td> <td> -1.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Getaround</th>                                                <td>  -7.4e+04</td> <td> 2.94e+04</td> <td>   -2.515</td> <td> 0.012</td> <td>-1.32e+05</td> <td>-1.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Getty Images</th>                                             <td>-5.079e+04</td> <td> 2.21e+04</td> <td>   -2.299</td> <td> 0.022</td> <td>-9.42e+04</td> <td>-7390.111</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Gilead Sciences</th>                                          <td>-1.009e+04</td> <td> 1.02e+04</td> <td>   -0.988</td> <td> 0.324</td> <td>-3.02e+04</td> <td> 9976.403</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ginger</th>                                                   <td>  -5.2e+04</td> <td> 2.81e+04</td> <td>   -1.851</td> <td> 0.065</td> <td>-1.07e+05</td> <td> 3188.148</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Glassdoor</th>                                                <td> -6.16e+04</td> <td> 2.23e+04</td> <td>   -2.766</td> <td> 0.006</td> <td>-1.05e+05</td> <td>-1.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_GoFundMe</th>                                                 <td>  1.74e+04</td> <td>  1.2e+04</td> <td>    1.454</td> <td> 0.147</td> <td>-6121.283</td> <td> 4.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Golden State Foods</th>                                       <td>-2.873e+04</td> <td> 1.76e+04</td> <td>   -1.632</td> <td> 0.103</td> <td>-6.33e+04</td> <td> 5852.989</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_GoodRx</th>                                                   <td>  1.28e+04</td> <td> 2.99e+04</td> <td>    0.429</td> <td> 0.668</td> <td>-4.59e+04</td> <td> 7.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Google</th>                                                   <td>-3.299e+04</td> <td> 2.22e+04</td> <td>   -1.483</td> <td> 0.139</td> <td>-7.67e+04</td> <td> 1.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_GotIt!</th>                                                   <td>-7.955e+04</td> <td> 2.91e+04</td> <td>   -2.733</td> <td> 0.007</td> <td>-1.37e+05</td> <td>-2.24e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Grammarly</th>                                                <td> 1.076e+05</td> <td> 2.59e+04</td> <td>    4.148</td> <td> 0.000</td> <td> 5.66e+04</td> <td> 1.59e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Grammarly, Inc.</th>                                          <td>-6.687e+04</td> <td>  2.3e+04</td> <td>   -2.902</td> <td> 0.004</td> <td>-1.12e+05</td> <td>-2.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Groove.co</th>                                                <td>-3.917e+04</td> <td> 2.78e+04</td> <td>   -1.411</td> <td> 0.159</td> <td>-9.37e+04</td> <td> 1.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Groq</th>                                                     <td>-8.425e+04</td> <td> 2.52e+04</td> <td>   -3.347</td> <td> 0.001</td> <td>-1.34e+05</td> <td>-3.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_HANUMAYAMMA INNOVATIONS AND TECHNOLOGIES</th>                 <td>-3.406e+04</td> <td> 9287.167</td> <td>   -3.668</td> <td> 0.000</td> <td>-5.23e+04</td> <td>-1.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_HG Insights</th>                                              <td>-1.273e+05</td> <td> 3.19e+04</td> <td>   -3.988</td> <td> 0.000</td> <td> -1.9e+05</td> <td>-6.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_HRL Laboratories LLC</th>                                     <td> 7484.6881</td> <td> 8513.664</td> <td>    0.879</td> <td> 0.380</td> <td>-9243.967</td> <td> 2.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Happiest Baby, Inc.</th>                                      <td> 9713.6147</td> <td> 2.67e+04</td> <td>    0.364</td> <td> 0.716</td> <td>-4.27e+04</td> <td> 6.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Harnham</th>                                                  <td> -478.2492</td> <td> 2.21e+04</td> <td>   -0.022</td> <td> 0.983</td> <td>-4.39e+04</td> <td> 4.29e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hayden AI Technologies</th>                                   <td>-3.424e+04</td> <td> 3.04e+04</td> <td>   -1.125</td> <td> 0.261</td> <td> -9.4e+04</td> <td> 2.55e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Health Net of California</th>                                 <td>-2.201e+04</td> <td> 1.12e+04</td> <td>   -1.970</td> <td> 0.049</td> <td> -4.4e+04</td> <td>  -53.344</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Healthcare Staffing Professionals, Inc.</th>                  <td>-5.311e+04</td> <td> 3.53e+04</td> <td>   -1.504</td> <td> 0.133</td> <td>-1.22e+05</td> <td> 1.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Heap</th>                                                     <td>-8.447e+04</td> <td> 2.39e+04</td> <td>   -3.537</td> <td> 0.000</td> <td>-1.31e+05</td> <td>-3.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Helio Health Inc.</th>                                        <td> 9814.1883</td> <td> 1.51e+04</td> <td>    0.650</td> <td> 0.516</td> <td>-1.99e+04</td> <td> 3.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Herophilus</th>                                               <td>-6.385e+04</td> <td> 2.29e+04</td> <td>   -2.785</td> <td> 0.006</td> <td>-1.09e+05</td> <td>-1.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hewlett Packard Enterprise</th>                               <td>-3.435e+04</td> <td> 2.72e+04</td> <td>   -1.265</td> <td> 0.206</td> <td>-8.77e+04</td> <td>  1.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hippo Insurance</th>                                          <td>-1.156e+04</td> <td> 2.25e+04</td> <td>   -0.513</td> <td> 0.608</td> <td>-5.58e+04</td> <td> 3.27e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hive</th>                                                     <td>-4.542e+04</td> <td> 2.48e+04</td> <td>   -1.832</td> <td> 0.068</td> <td>-9.41e+04</td> <td> 3301.910</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hulu</th>                                                     <td>-3711.9900</td> <td> 2.29e+04</td> <td>   -0.162</td> <td> 0.871</td> <td>-4.87e+04</td> <td> 4.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hurricane Electric</th>                                       <td>-3.384e+04</td> <td> 6221.590</td> <td>   -5.439</td> <td> 0.000</td> <td>-4.61e+04</td> <td>-2.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Hypersonix Inc.</th>                                          <td>-3.058e+04</td> <td> 3.48e+04</td> <td>   -0.879</td> <td> 0.380</td> <td>-9.89e+04</td> <td> 3.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_IBM</th>                                                      <td>-8272.7557</td> <td> 5538.084</td> <td>   -1.494</td> <td> 0.136</td> <td>-1.92e+04</td> <td> 2609.129</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ICW Group</th>                                                <td> 1.437e+04</td> <td> 2.99e+04</td> <td>    0.481</td> <td> 0.631</td> <td>-4.43e+04</td> <td> 7.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ICW Group Holdings, Inc</th>                                  <td> 1.437e+04</td> <td> 2.99e+04</td> <td>    0.481</td> <td> 0.631</td> <td>-4.43e+04</td> <td> 7.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ISO</th>                                                      <td> -2.85e+04</td> <td> 2.54e+04</td> <td>   -1.122</td> <td> 0.262</td> <td>-7.84e+04</td> <td> 2.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ignitech Solutions LLC</th>                                   <td>-8.926e+04</td> <td> 4.13e+04</td> <td>   -2.161</td> <td> 0.031</td> <td> -1.7e+05</td> <td>-8106.375</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Illumina</th>                                                 <td>-1.298e+04</td> <td> 1.39e+04</td> <td>   -0.932</td> <td> 0.352</td> <td>-4.03e+04</td> <td> 1.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Indeed</th>                                                   <td> 6.911e+04</td> <td> 2.25e+04</td> <td>    3.068</td> <td> 0.002</td> <td> 2.48e+04</td> <td> 1.13e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Infogen Labs</th>                                             <td>-2.533e+04</td> <td> 9225.329</td> <td>   -2.745</td> <td> 0.006</td> <td>-4.35e+04</td> <td>-7200.982</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Inland Empire Health Plans</th>                               <td>-4821.2528</td> <td> 1.19e+04</td> <td>   -0.405</td> <td> 0.686</td> <td>-2.82e+04</td> <td> 1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Inspire</th>                                                  <td>-3.502e+04</td> <td> 2.54e+04</td> <td>   -1.377</td> <td> 0.169</td> <td> -8.5e+04</td> <td>  1.5e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Instacart</th>                                                <td>-3.224e+04</td> <td> 2.26e+04</td> <td>   -1.428</td> <td> 0.154</td> <td>-7.66e+04</td> <td> 1.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Instagram</th>                                                <td>-8.816e+04</td> <td> 2.35e+04</td> <td>   -3.759</td> <td> 0.000</td> <td>-1.34e+05</td> <td>-4.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Intel</th>                                                    <td>-1.484e+04</td> <td> 1.07e+04</td> <td>   -1.392</td> <td> 0.165</td> <td>-3.58e+04</td> <td> 6115.256</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Intellimize</th>                                              <td>-6.025e+04</td> <td> 2.69e+04</td> <td>   -2.236</td> <td> 0.026</td> <td>-1.13e+05</td> <td>-7299.406</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Intuit</th>                                                   <td>-4.001e+04</td> <td> 1.97e+04</td> <td>   -2.028</td> <td> 0.043</td> <td>-7.88e+04</td> <td>-1250.417</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Intuitive</th>                                                <td>-5.455e+04</td> <td> 2.31e+04</td> <td>   -2.365</td> <td> 0.018</td> <td>-9.99e+04</td> <td>-9233.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Invitae</th>                                                  <td>-1.253e+05</td> <td> 2.42e+04</td> <td>   -5.166</td> <td> 0.000</td> <td>-1.73e+05</td> <td>-7.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ipsos North America</th>                                      <td>  100.6002</td> <td> 9870.179</td> <td>    0.010</td> <td> 0.992</td> <td>-1.93e+04</td> <td> 1.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Itron</th>                                                    <td>-1051.6427</td> <td> 3.17e+04</td> <td>   -0.033</td> <td> 0.974</td> <td>-6.34e+04</td> <td> 6.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_J.D. Power</th>                                               <td>-1.311e+04</td> <td> 2.36e+04</td> <td>   -0.556</td> <td> 0.578</td> <td>-5.94e+04</td> <td> 3.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_JD.com</th>                                                   <td>-2.264e+04</td> <td> 2.56e+04</td> <td>   -0.885</td> <td> 0.377</td> <td>-7.29e+04</td> <td> 2.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_JPL/NASA</th>                                                 <td>-1.028e+05</td> <td> 3.23e+04</td> <td>   -3.184</td> <td> 0.002</td> <td>-1.66e+05</td> <td>-3.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Jane Technologies</th>                                        <td>-8.153e+04</td> <td> 2.84e+04</td> <td>   -2.873</td> <td> 0.004</td> <td>-1.37e+05</td> <td>-2.58e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Jazz Pharmaceuticals</th>                                     <td>-4.944e+04</td> <td> 2.48e+04</td> <td>   -1.991</td> <td> 0.047</td> <td>-9.82e+04</td> <td> -644.858</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Jefferies & Company, Inc.</th>                                <td>-2.104e+04</td> <td> 1.17e+04</td> <td>   -1.792</td> <td> 0.074</td> <td>-4.41e+04</td> <td> 2032.222</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Joby Aviation</th>                                            <td> 6606.5647</td> <td> 8700.800</td> <td>    0.759</td> <td> 0.448</td> <td>-1.05e+04</td> <td> 2.37e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_John Deere Intelligent Solutions</th>                         <td>-3.052e+04</td> <td> 2.21e+04</td> <td>   -1.379</td> <td> 0.169</td> <td> -7.4e+04</td> <td>  1.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Johnson & Johnson Family of Companies</th>                    <td>-2.139e+04</td> <td> 2.57e+04</td> <td>   -0.831</td> <td> 0.406</td> <td> -7.2e+04</td> <td> 2.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Keewi</th>                                                    <td>-8.835e+04</td> <td> 3.03e+04</td> <td>   -2.917</td> <td> 0.004</td> <td>-1.48e+05</td> <td>-2.88e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_KelaHealth</th>                                               <td>-1.036e+04</td> <td> 1.19e+04</td> <td>   -0.868</td> <td> 0.386</td> <td>-3.38e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kelvin Inc</th>                                               <td>-4.041e+04</td> <td>  2.9e+04</td> <td>   -1.395</td> <td> 0.164</td> <td>-9.73e+04</td> <td> 1.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kernel</th>                                                   <td>-3.644e+04</td> <td> 1.98e+04</td> <td>   -1.836</td> <td> 0.067</td> <td>-7.54e+04</td> <td> 2555.828</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kett Engineering</th>                                         <td> -5.02e+04</td> <td> 2.92e+04</td> <td>   -1.719</td> <td> 0.086</td> <td>-1.08e+05</td> <td> 7178.496</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Khan Academy</th>                                             <td>-2.996e+04</td> <td> 2.32e+04</td> <td>   -1.291</td> <td> 0.197</td> <td>-7.56e+04</td> <td> 1.56e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kharon</th>                                                   <td>-1.548e+04</td> <td> 2.56e+04</td> <td>   -0.605</td> <td> 0.545</td> <td>-6.57e+04</td> <td> 3.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kite Pharma</th>                                              <td> 3.411e+04</td> <td> 2.27e+04</td> <td>    1.503</td> <td> 0.134</td> <td>-1.05e+04</td> <td> 7.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kodiak Robotics</th>                                          <td>-1238.1573</td> <td> 3.48e+04</td> <td>   -0.036</td> <td> 0.972</td> <td>-6.96e+04</td> <td> 6.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Kyte</th>                                                     <td>-6.145e+04</td> <td> 2.18e+04</td> <td>   -2.814</td> <td> 0.005</td> <td>-1.04e+05</td> <td>-1.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Labcorp</th>                                                  <td>-3.703e+04</td> <td> 2.89e+04</td> <td>   -1.283</td> <td> 0.200</td> <td>-9.37e+04</td> <td> 1.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lark Health</th>                                              <td>-6.542e+04</td> <td> 2.32e+04</td> <td>   -2.825</td> <td> 0.005</td> <td>-1.11e+05</td> <td>-1.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lawrence Berkeley National Laboratory</th>                    <td>-8232.9055</td> <td>  1.1e+04</td> <td>   -0.746</td> <td> 0.456</td> <td>-2.99e+04</td> <td> 1.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Legion</th>                                                   <td>-1.421e+04</td> <td> 2.63e+04</td> <td>   -0.540</td> <td> 0.589</td> <td>-6.59e+04</td> <td> 3.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Leidos</th>                                                   <td> 2.045e+04</td> <td> 1.47e+04</td> <td>    1.392</td> <td> 0.165</td> <td>-8416.965</td> <td> 4.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_LendingClub</th>                                              <td>-3.716e+04</td> <td> 2.31e+04</td> <td>   -1.609</td> <td> 0.108</td> <td>-8.26e+04</td> <td> 8225.595</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_LendingPoint LLC</th>                                         <td> -7.93e+04</td> <td> 3.06e+04</td> <td>   -2.594</td> <td> 0.010</td> <td>-1.39e+05</td> <td>-1.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Levi Strauss & Co.</th>                                       <td>-5.194e+04</td> <td>  2.2e+04</td> <td>   -2.362</td> <td> 0.019</td> <td>-9.51e+04</td> <td>-8736.256</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Liftoff+Vungle</th>                                           <td>-6216.7374</td> <td>  1.3e+04</td> <td>   -0.479</td> <td> 0.632</td> <td>-3.17e+04</td> <td> 1.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lily AI</th>                                                  <td> -4.56e+04</td> <td> 2.29e+04</td> <td>   -1.987</td> <td> 0.048</td> <td>-9.07e+04</td> <td> -502.902</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Linqia</th>                                                   <td>-5.966e+04</td> <td> 2.55e+04</td> <td>   -2.344</td> <td> 0.019</td> <td> -1.1e+05</td> <td>-9642.088</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_LivePerson</th>                                               <td>-1.031e+05</td> <td> 2.32e+04</td> <td>   -4.452</td> <td> 0.000</td> <td>-1.49e+05</td> <td>-5.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_LiveRamp</th>                                                 <td>-2.286e+04</td> <td> 1.15e+04</td> <td>   -1.992</td> <td> 0.047</td> <td>-4.54e+04</td> <td> -312.574</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Loon</th>                                                     <td>-2.964e+04</td> <td> 2.22e+04</td> <td>   -1.338</td> <td> 0.182</td> <td>-7.32e+04</td> <td> 1.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lucid Motors</th>                                             <td> 1.433e+04</td> <td> 9490.403</td> <td>    1.510</td> <td> 0.132</td> <td>-4319.788</td> <td>  3.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lumiata Inc.</th>                                             <td>-1.273e+04</td> <td> 1.54e+04</td> <td>   -0.828</td> <td> 0.408</td> <td>-4.29e+04</td> <td> 1.75e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Lynx Analytics</th>                                           <td>-5.688e+04</td> <td> 2.41e+04</td> <td>   -2.361</td> <td> 0.019</td> <td>-1.04e+05</td> <td>-9536.811</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MCG Health</th>                                               <td>-6.264e+04</td> <td> 2.24e+04</td> <td>   -2.797</td> <td> 0.005</td> <td>-1.07e+05</td> <td>-1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MOLOCO</th>                                                   <td> 5.123e+04</td> <td> 1.36e+04</td> <td>    3.765</td> <td> 0.000</td> <td> 2.45e+04</td> <td>  7.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Manifest Medex</th>                                           <td>-2.563e+04</td> <td> 8542.461</td> <td>   -3.000</td> <td> 0.003</td> <td>-4.24e+04</td> <td>-8843.382</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MariaDB Corporation Ab</th>                                   <td>-1025.1554</td> <td> 2.87e+04</td> <td>   -0.036</td> <td> 0.972</td> <td>-5.75e+04</td> <td> 5.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MasterCard</th>                                               <td>-4.969e+04</td> <td> 2.62e+04</td> <td>   -1.899</td> <td> 0.058</td> <td>-1.01e+05</td> <td> 1717.010</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MasterClass</th>                                              <td>-4.784e+04</td> <td> 2.36e+04</td> <td>   -2.030</td> <td> 0.043</td> <td>-9.42e+04</td> <td>-1525.402</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Matroid</th>                                                  <td> 6401.6773</td> <td> 3.39e+04</td> <td>    0.189</td> <td> 0.850</td> <td>-6.03e+04</td> <td> 7.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MediaAlpha</th>                                               <td> -1.36e+04</td> <td> 7359.387</td> <td>   -1.847</td> <td> 0.065</td> <td>-2.81e+04</td> <td>  864.448</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Medtronic</th>                                                <td>-5619.5032</td> <td> 4727.756</td> <td>   -1.189</td> <td> 0.235</td> <td>-1.49e+04</td> <td> 3670.151</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mercedes-Benz Research & Development North America, Inc.</th> <td>-2.605e+04</td> <td> 1.19e+04</td> <td>   -2.185</td> <td> 0.029</td> <td>-4.95e+04</td> <td>-2628.964</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Meredith Corporation</th>                                     <td>-1.065e+04</td> <td> 2.66e+04</td> <td>   -0.401</td> <td> 0.689</td> <td>-6.28e+04</td> <td> 4.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Microsoft</th>                                                <td>-1.537e+04</td> <td> 2.06e+04</td> <td>   -0.746</td> <td> 0.456</td> <td>-5.59e+04</td> <td> 2.51e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mirati Therapeutics Inc</th>                                  <td> 5068.1305</td> <td> 7459.262</td> <td>    0.679</td> <td> 0.497</td> <td>-9588.711</td> <td> 1.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mission Analytics Group, Inc.</th>                            <td>-3.643e+04</td> <td> 1.49e+04</td> <td>   -2.437</td> <td> 0.015</td> <td>-6.58e+04</td> <td>-7057.174</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mission Support and Test Services, LLC</th>                   <td>-1.185e+04</td> <td> 8604.348</td> <td>   -1.377</td> <td> 0.169</td> <td>-2.88e+04</td> <td> 5054.629</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_MobilityWare</th>                                             <td>-6841.3522</td> <td> 1.34e+04</td> <td>   -0.512</td> <td> 0.609</td> <td>-3.31e+04</td> <td> 1.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Momentive</th>                                                <td>-2.548e+04</td> <td> 1.38e+04</td> <td>   -1.842</td> <td> 0.066</td> <td>-5.27e+04</td> <td> 1702.707</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Motional</th>                                                 <td>-8326.7221</td> <td> 1.22e+04</td> <td>   -0.683</td> <td> 0.495</td> <td>-3.23e+04</td> <td> 1.56e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Moveworks</th>                                                <td>-1.494e+04</td> <td> 2.26e+04</td> <td>   -0.662</td> <td> 0.508</td> <td>-5.93e+04</td> <td> 2.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Movoto</th>                                                   <td>-3.487e+04</td> <td> 1.05e+04</td> <td>   -3.327</td> <td> 0.001</td> <td>-5.55e+04</td> <td>-1.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mulligan Funding</th>                                         <td> 2.709e+04</td> <td> 1.43e+04</td> <td>    1.893</td> <td> 0.059</td> <td>-1034.252</td> <td> 5.52e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Mynurse.ai</th>                                               <td> 9059.3418</td> <td> 1.14e+04</td> <td>    0.793</td> <td> 0.428</td> <td>-1.34e+04</td> <td> 3.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_NBCUniversal</th>                                             <td>-1.535e+04</td> <td> 5449.627</td> <td>   -2.818</td> <td> 0.005</td> <td>-2.61e+04</td> <td>-4646.490</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_NEXT Trucking</th>                                            <td>-4.716e+04</td> <td> 2.95e+04</td> <td>   -1.598</td> <td> 0.111</td> <td>-1.05e+05</td> <td> 1.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_NVIDIA</th>                                                   <td> -4.59e+04</td> <td> 2.25e+04</td> <td>   -2.040</td> <td> 0.042</td> <td>-9.01e+04</td> <td>-1692.186</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Narvar</th>                                                   <td>-6591.7910</td> <td> 1.52e+04</td> <td>   -0.435</td> <td> 0.664</td> <td>-3.64e+04</td> <td> 2.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_National General Insurance</th>                               <td> 3.552e+04</td> <td> 1.79e+04</td> <td>    1.987</td> <td> 0.048</td> <td>  390.345</td> <td> 7.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Nauto</th>                                                    <td>-2.277e+04</td> <td> 2.34e+04</td> <td>   -0.974</td> <td> 0.331</td> <td>-6.87e+04</td> <td> 2.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Neomorph, Inc</th>                                            <td>-2.052e+04</td> <td> 2.09e+04</td> <td>   -0.982</td> <td> 0.327</td> <td>-6.16e+04</td> <td> 2.05e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Netflix</th>                                                  <td>-2.951e+04</td> <td> 2.25e+04</td> <td>   -1.310</td> <td> 0.191</td> <td>-7.38e+04</td> <td> 1.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Next Insurance</th>                                           <td> 6.749e+04</td> <td> 4.18e+04</td> <td>    1.615</td> <td> 0.107</td> <td>-1.46e+04</td> <td>  1.5e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_NextRoll</th>                                                 <td>-1.921e+04</td> <td> 1.31e+04</td> <td>   -1.464</td> <td> 0.144</td> <td> -4.5e+04</td> <td> 6573.110</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Nextdoor</th>                                                 <td>-1.288e+04</td> <td> 2.49e+04</td> <td>   -0.517</td> <td> 0.605</td> <td>-6.18e+04</td> <td>  3.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Niantic</th>                                                  <td>-2.109e+04</td> <td> 2.38e+04</td> <td>   -0.886</td> <td> 0.376</td> <td>-6.79e+04</td> <td> 2.57e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Nordstrom Inc</th>                                            <td> -3.07e+04</td> <td> 2.16e+04</td> <td>   -1.422</td> <td> 0.156</td> <td>-7.31e+04</td> <td> 1.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Northrop Grumman</th>                                         <td> 2023.5615</td> <td> 2.68e+04</td> <td>    0.076</td> <td> 0.940</td> <td>-5.06e+04</td> <td> 5.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Novo Technologies Inc</th>                                    <td> 4.949e+04</td> <td> 1.54e+04</td> <td>    3.221</td> <td> 0.001</td> <td> 1.93e+04</td> <td> 7.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Numerade</th>                                                 <td>-3.522e+04</td> <td> 2.46e+04</td> <td>   -1.433</td> <td> 0.152</td> <td>-8.35e+04</td> <td> 1.31e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Numerdox</th>                                                 <td>-5.113e+04</td> <td> 3.13e+04</td> <td>   -1.635</td> <td> 0.103</td> <td>-1.13e+05</td> <td> 1.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Nuro</th>                                                     <td>-2.765e+04</td> <td> 2.16e+04</td> <td>   -1.283</td> <td> 0.200</td> <td>   -7e+04</td> <td> 1.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_OTTR Chronic Care Solutions</th>                              <td> 6212.2684</td> <td> 9219.559</td> <td>    0.674</td> <td> 0.501</td> <td>-1.19e+04</td> <td> 2.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Oculus Search Partners LLC</th>                               <td>-6.948e+04</td> <td> 2.52e+04</td> <td>   -2.761</td> <td> 0.006</td> <td>-1.19e+05</td> <td>   -2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_One Medical</th>                                              <td>-3.935e+04</td> <td> 1.12e+04</td> <td>   -3.522</td> <td> 0.000</td> <td>-6.13e+04</td> <td>-1.74e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Oneida ESC Group</th>                                         <td>-2.018e+04</td> <td> 9482.579</td> <td>   -2.128</td> <td> 0.034</td> <td>-3.88e+04</td> <td>-1551.097</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Onto Innovation</th>                                          <td>-1.837e+04</td> <td> 1.22e+04</td> <td>   -1.510</td> <td> 0.132</td> <td>-4.23e+04</td> <td> 5538.608</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Opendoor</th>                                                 <td> 1.213e+04</td> <td> 9216.813</td> <td>    1.316</td> <td> 0.189</td> <td>-5981.528</td> <td> 3.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_OpsRamp, Inc.</th>                                            <td>-1.898e+04</td> <td> 2.55e+04</td> <td>   -0.743</td> <td> 0.458</td> <td>-6.92e+04</td> <td> 3.12e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Oracle</th>                                                   <td>-6.696e+04</td> <td> 2.82e+04</td> <td>   -2.374</td> <td> 0.018</td> <td>-1.22e+05</td> <td>-1.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Orbital Sidekick</th>                                         <td>  -61.6976</td> <td>  1.8e+04</td> <td>   -0.003</td> <td> 0.997</td> <td>-3.55e+04</td> <td> 3.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Osair Technologies</th>                                       <td>-8.607e+04</td> <td> 2.33e+04</td> <td>   -3.696</td> <td> 0.000</td> <td>-1.32e+05</td> <td>-4.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Osmo</th>                                                     <td> -4.89e+04</td> <td> 2.54e+04</td> <td>   -1.928</td> <td> 0.054</td> <td>-9.87e+04</td> <td>  924.874</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Otter.ai</th>                                                 <td>-2.345e+04</td> <td> 2.43e+04</td> <td>   -0.964</td> <td> 0.336</td> <td>-7.13e+04</td> <td> 2.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Oura</th>                                                     <td>-4.523e+04</td> <td> 2.43e+04</td> <td>   -1.858</td> <td> 0.064</td> <td>-9.31e+04</td> <td> 2600.070</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PG&E Corporation</th>                                         <td>-7.287e+04</td> <td> 2.58e+04</td> <td>   -2.830</td> <td> 0.005</td> <td>-1.23e+05</td> <td>-2.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Palo Alto Networks</th>                                       <td>-1.189e+05</td> <td> 3.17e+04</td> <td>   -3.752</td> <td> 0.000</td> <td>-1.81e+05</td> <td>-5.66e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Parallel Bio</th>                                             <td> 2.453e+04</td> <td> 3.39e+04</td> <td>    0.724</td> <td> 0.469</td> <td>-4.21e+04</td> <td> 9.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PayPal</th>                                                   <td>-6.231e+04</td> <td> 2.33e+04</td> <td>   -2.672</td> <td> 0.008</td> <td>-1.08e+05</td> <td>-1.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Penfield Search Partners</th>                                 <td>-3.331e+04</td> <td> 1.26e+04</td> <td>   -2.649</td> <td> 0.008</td> <td> -5.8e+04</td> <td>-8603.100</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PennyMac</th>                                                 <td> 9493.0284</td> <td> 1.07e+04</td> <td>    0.884</td> <td> 0.377</td> <td>-1.16e+04</td> <td> 3.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Philo</th>                                                    <td> 8231.2795</td> <td> 8453.893</td> <td>    0.974</td> <td> 0.331</td> <td>-8379.932</td> <td> 2.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Philo Inc.</th>                                               <td>-1768.7205</td> <td> 6923.739</td> <td>   -0.255</td> <td> 0.798</td> <td>-1.54e+04</td> <td> 1.18e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PicnicHealth</th>                                             <td>-3.197e+04</td> <td> 2.39e+04</td> <td>   -1.338</td> <td> 0.182</td> <td>-7.89e+04</td> <td>  1.5e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Pinnacle Group</th>                                           <td>-9.464e+04</td> <td> 2.88e+04</td> <td>   -3.289</td> <td> 0.001</td> <td>-1.51e+05</td> <td>-3.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Pinterest</th>                                                <td>-5.181e+04</td> <td> 2.16e+04</td> <td>   -2.396</td> <td> 0.017</td> <td>-9.43e+04</td> <td>-9316.903</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Plaid</th>                                                    <td>-1.288e+04</td> <td> 2.37e+04</td> <td>   -0.545</td> <td> 0.586</td> <td>-5.94e+04</td> <td> 3.36e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Platform Science</th>                                         <td>-1.787e+04</td> <td> 2.49e+04</td> <td>   -0.718</td> <td> 0.473</td> <td>-6.68e+04</td> <td> 3.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Plato Systems</th>                                            <td>-9071.9648</td> <td> 1.54e+04</td> <td>   -0.591</td> <td> 0.555</td> <td>-3.92e+04</td> <td> 2.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PlayStation Global</th>                                       <td>-5.216e+04</td> <td> 2.57e+04</td> <td>   -2.027</td> <td> 0.043</td> <td>-1.03e+05</td> <td>-1585.425</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Plume</th>                                                    <td> -2.78e+04</td> <td> 2.26e+04</td> <td>   -1.231</td> <td> 0.219</td> <td>-7.21e+04</td> <td> 1.66e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Plus</th>                                                     <td>-4278.3575</td> <td> 1.14e+04</td> <td>   -0.374</td> <td> 0.709</td> <td>-2.68e+04</td> <td> 1.82e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Plus Power</th>                                               <td> 8286.2963</td> <td> 1.43e+04</td> <td>    0.577</td> <td> 0.564</td> <td>-1.99e+04</td> <td> 3.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PocketPills</th>                                              <td>-1.719e+04</td> <td> 2.56e+04</td> <td>   -0.672</td> <td> 0.502</td> <td>-6.74e+04</td> <td>  3.3e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Point Digital Finance</th>                                    <td>-4.039e+04</td> <td> 2.47e+04</td> <td>   -1.637</td> <td> 0.102</td> <td>-8.89e+04</td> <td> 8079.787</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Pollen</th>                                                   <td>-2.072e+04</td> <td> 5861.043</td> <td>   -3.535</td> <td> 0.000</td> <td>-3.22e+04</td> <td>-9200.762</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Postclick</th>                                                <td>-4.451e+04</td> <td> 1.85e+04</td> <td>   -2.402</td> <td> 0.017</td> <td>-8.09e+04</td> <td>-8099.814</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Prealize Health</th>                                          <td>-6.796e+04</td> <td>  2.6e+04</td> <td>   -2.616</td> <td> 0.009</td> <td>-1.19e+05</td> <td>-1.69e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Procore Technologies</th>                                     <td>-2.514e+04</td> <td> 9405.200</td> <td>   -2.673</td> <td> 0.008</td> <td>-4.36e+04</td> <td>-6657.564</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Prosper</th>                                                  <td>-7.831e+04</td> <td> 2.62e+04</td> <td>   -2.985</td> <td> 0.003</td> <td> -1.3e+05</td> <td>-2.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Prove</th>                                                    <td>-4.807e+04</td> <td> 1.42e+04</td> <td>   -3.378</td> <td> 0.001</td> <td> -7.6e+04</td> <td>-2.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_PwC</th>                                                      <td>-3.473e+04</td> <td> 2.58e+04</td> <td>   -1.344</td> <td> 0.180</td> <td>-8.55e+04</td> <td> 1.61e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_QuestBridge</th>                                              <td>-6.059e+04</td> <td> 2.07e+04</td> <td>   -2.922</td> <td> 0.004</td> <td>-1.01e+05</td> <td>-1.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_RAPP</th>                                                     <td>-3.897e+04</td> <td> 2.12e+04</td> <td>   -1.835</td> <td> 0.067</td> <td>-8.07e+04</td> <td> 2766.964</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_REDICA Systems</th>                                           <td>-1.094e+05</td> <td> 3.42e+04</td> <td>   -3.198</td> <td> 0.001</td> <td>-1.77e+05</td> <td>-4.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Recruiting From Scratch</th>                                  <td>-5606.4682</td> <td> 2.44e+04</td> <td>   -0.230</td> <td> 0.818</td> <td>-5.36e+04</td> <td> 4.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Recurly</th>                                                  <td> 8796.2050</td> <td> 2.35e+04</td> <td>    0.374</td> <td> 0.708</td> <td>-3.74e+04</td> <td>  5.5e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Recurrency</th>                                               <td>-1.182e+05</td> <td> 3.07e+04</td> <td>   -3.850</td> <td> 0.000</td> <td>-1.78e+05</td> <td>-5.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Red Bull</th>                                                 <td>-2.524e+04</td> <td> 1.34e+04</td> <td>   -1.885</td> <td> 0.060</td> <td>-5.16e+04</td> <td> 1067.069</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Reddit</th>                                                   <td>-4.099e+04</td> <td> 2.19e+04</td> <td>   -1.870</td> <td> 0.062</td> <td>-8.41e+04</td> <td> 2077.119</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Resiliency LLC</th>                                           <td>-1.176e+05</td> <td>  4.2e+04</td> <td>   -2.803</td> <td> 0.005</td> <td>   -2e+05</td> <td>-3.52e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Resonance AI</th>                                             <td>-4.221e+04</td> <td> 2.56e+04</td> <td>   -1.646</td> <td> 0.100</td> <td>-9.26e+04</td> <td> 8167.952</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Retool</th>                                                   <td>-6.408e+04</td> <td> 2.31e+04</td> <td>   -2.770</td> <td> 0.006</td> <td> -1.1e+05</td> <td>-1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Revenue.io</th>                                               <td>-3.225e+04</td> <td> 1.47e+04</td> <td>   -2.190</td> <td> 0.029</td> <td>-6.12e+04</td> <td>-3310.909</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Rhombus Power</th>                                            <td>-4.688e+04</td> <td> 1.47e+04</td> <td>   -3.190</td> <td> 0.002</td> <td>-7.57e+04</td> <td> -1.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ripple</th>                                                   <td>-4.405e+04</td> <td> 2.08e+04</td> <td>   -2.118</td> <td> 0.035</td> <td>-8.49e+04</td> <td>-3180.490</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Rippling</th>                                                 <td>-8.583e+04</td> <td> 2.42e+04</td> <td>   -3.553</td> <td> 0.000</td> <td>-1.33e+05</td> <td>-3.84e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Riva Health</th>                                              <td>-4.664e+04</td> <td> 3.05e+04</td> <td>   -1.530</td> <td> 0.127</td> <td>-1.07e+05</td> <td> 1.33e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Rivian Automotive</th>                                        <td>-1.071e+04</td> <td> 1.29e+04</td> <td>   -0.827</td> <td> 0.408</td> <td>-3.61e+04</td> <td> 1.47e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Robin Healthcare</th>                                         <td> -4.14e+04</td> <td> 2.68e+04</td> <td>   -1.544</td> <td> 0.123</td> <td>-9.41e+04</td> <td> 1.13e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Robinhood</th>                                                <td> -7.46e+04</td> <td> 2.45e+04</td> <td>   -3.049</td> <td> 0.002</td> <td>-1.23e+05</td> <td>-2.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Roche</th>                                                    <td>-2.721e+04</td> <td> 2.26e+04</td> <td>   -1.202</td> <td> 0.230</td> <td>-7.17e+04</td> <td> 1.73e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Roku</th>                                                     <td>-6.431e+04</td> <td> 2.99e+04</td> <td>   -2.154</td> <td> 0.032</td> <td>-1.23e+05</td> <td>-5650.134</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Roo</th>                                                      <td>-4.984e+04</td> <td> 2.89e+04</td> <td>   -1.726</td> <td> 0.085</td> <td>-1.07e+05</td> <td> 6899.318</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Route</th>                                                    <td>-3.731e+04</td> <td> 2.96e+04</td> <td>   -1.262</td> <td> 0.207</td> <td>-9.54e+04</td> <td> 2.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Rubicon</th>                                                  <td> 3.087e+04</td> <td> 1.75e+04</td> <td>    1.764</td> <td> 0.078</td> <td>-3524.957</td> <td> 6.53e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SAMBA TV</th>                                                 <td> 3.895e+04</td> <td>  3.3e+04</td> <td>    1.181</td> <td> 0.238</td> <td>-2.59e+04</td> <td> 1.04e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SCAN Health Plan</th>                                         <td>-1.729e+04</td> <td> 1.34e+04</td> <td>   -1.292</td> <td> 0.197</td> <td>-4.36e+04</td> <td> 8998.770</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SLAC National Accelerator Laboratory</th>                     <td> -3.16e+04</td> <td> 2.63e+04</td> <td>   -1.200</td> <td> 0.231</td> <td>-8.34e+04</td> <td> 2.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SRI International</th>                                        <td>-2.373e+04</td> <td> 2.62e+04</td> <td>   -0.905</td> <td> 0.366</td> <td>-7.53e+04</td> <td> 2.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_STAR Labs</th>                                                <td>-3.103e+04</td> <td> 2.48e+04</td> <td>   -1.251</td> <td> 0.212</td> <td>-7.98e+04</td> <td> 1.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Salesforce</th>                                               <td>-8.224e+04</td> <td> 2.15e+04</td> <td>   -3.826</td> <td> 0.000</td> <td>-1.24e+05</td> <td>   -4e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ScaleMonk</th>                                                <td>-1.882e+04</td> <td> 2.55e+04</td> <td>   -0.737</td> <td> 0.462</td> <td> -6.9e+04</td> <td> 3.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Scaleapi</th>                                                 <td> 1483.3723</td> <td> 1.17e+04</td> <td>    0.127</td> <td> 0.899</td> <td>-2.15e+04</td> <td> 2.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Seer</th>                                                     <td> 2.837e+04</td> <td> 1.51e+04</td> <td>    1.876</td> <td> 0.061</td> <td>-1346.523</td> <td> 5.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Segula Technologies</th>                                      <td>-2.986e+04</td> <td> 1.77e+04</td> <td>   -1.684</td> <td> 0.093</td> <td>-6.47e+04</td> <td> 4980.143</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sense Talent Labs, Inc.</th>                                  <td>-5.761e+04</td> <td> 2.47e+04</td> <td>   -2.337</td> <td> 0.020</td> <td>-1.06e+05</td> <td>-9164.305</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ServiceNow</th>                                               <td>-3.051e+04</td> <td> 2.47e+04</td> <td>   -1.237</td> <td> 0.217</td> <td> -7.9e+04</td> <td>  1.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SetSail</th>                                                  <td> 2052.5684</td> <td> 1.63e+04</td> <td>    0.126</td> <td> 0.900</td> <td>-2.99e+04</td> <td>  3.4e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Shift</th>                                                    <td>-5.402e+04</td> <td> 3.03e+04</td> <td>   -1.783</td> <td> 0.075</td> <td>-1.14e+05</td> <td> 5513.570</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Shipt</th>                                                    <td> -5.35e+04</td> <td> 2.07e+04</td> <td>   -2.587</td> <td> 0.010</td> <td>-9.41e+04</td> <td>-1.29e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Shopify</th>                                                  <td>-1.013e+05</td> <td> 2.86e+04</td> <td>   -3.540</td> <td> 0.000</td> <td>-1.58e+05</td> <td>-4.51e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Shutterfly</th>                                               <td>-5.268e+04</td> <td> 1.39e+04</td> <td>   -3.800</td> <td> 0.000</td> <td>-7.99e+04</td> <td>-2.54e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sift</th>                                                     <td>-5.448e+04</td> <td> 2.56e+04</td> <td>   -2.124</td> <td> 0.034</td> <td>-1.05e+05</td> <td>-4088.516</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Signifyd</th>                                                 <td>-5.696e+04</td> <td> 2.66e+04</td> <td>   -2.143</td> <td> 0.033</td> <td>-1.09e+05</td> <td>-4733.713</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SimplePractice</th>                                           <td> 2.503e+04</td> <td> 1.88e+04</td> <td>    1.329</td> <td> 0.185</td> <td> -1.2e+04</td> <td> 6.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Singularity 6</th>                                            <td> 5.686e+04</td> <td> 2.25e+04</td> <td>    2.524</td> <td> 0.012</td> <td> 1.26e+04</td> <td> 1.01e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Skai</th>                                                     <td>-6.732e+04</td> <td> 2.47e+04</td> <td>   -2.720</td> <td> 0.007</td> <td>-1.16e+05</td> <td>-1.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Slack</th>                                                    <td> -8.37e+04</td> <td>  2.2e+04</td> <td>   -3.800</td> <td> 0.000</td> <td>-1.27e+05</td> <td>-4.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Slate Technologies</th>                                       <td>-6.048e+04</td> <td> 2.55e+04</td> <td>   -2.367</td> <td> 0.018</td> <td>-1.11e+05</td> <td>-1.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sleep Number</th>                                             <td> 1664.7955</td> <td> 9792.260</td> <td>    0.170</td> <td> 0.865</td> <td>-1.76e+04</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Snapchat</th>                                                 <td>-4.719e+04</td> <td> 2.24e+04</td> <td>   -2.103</td> <td> 0.036</td> <td>-9.13e+04</td> <td>-3095.764</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Snowflake</th>                                                <td>-5.596e+04</td> <td> 2.94e+04</td> <td>   -1.906</td> <td> 0.057</td> <td>-1.14e+05</td> <td> 1734.344</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Socure</th>                                                   <td>-8.927e+04</td> <td> 2.39e+04</td> <td>   -3.727</td> <td> 0.000</td> <td>-1.36e+05</td> <td>-4.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sofar Ocean</th>                                              <td>-5.968e+04</td> <td> 2.41e+04</td> <td>   -2.471</td> <td> 0.014</td> <td>-1.07e+05</td> <td>-1.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sojern</th>                                                   <td>-1.094e+05</td> <td> 1.78e+04</td> <td>   -6.129</td> <td> 0.000</td> <td>-1.44e+05</td> <td>-7.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SpanIdea Systems</th>                                         <td>-1.301e+04</td> <td> 6359.840</td> <td>   -2.046</td> <td> 0.041</td> <td>-2.55e+04</td> <td> -512.834</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Spanidea Systemms</th>                                        <td>-9.692e+04</td> <td> 2.86e+04</td> <td>   -3.384</td> <td> 0.001</td> <td>-1.53e+05</td> <td>-4.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Specific Diagnostics</th>                                     <td> 1.426e+04</td> <td> 1.21e+04</td> <td>    1.180</td> <td> 0.238</td> <td>-9475.503</td> <td>  3.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Spin</th>                                                     <td> -5.99e+04</td> <td> 2.46e+04</td> <td>   -2.436</td> <td> 0.015</td> <td>-1.08e+05</td> <td>-1.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Spotline Inc</th>                                             <td> 4.296e+04</td> <td> 8953.331</td> <td>    4.798</td> <td> 0.000</td> <td> 2.54e+04</td> <td> 6.06e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Spring Discovery</th>                                         <td>  1.22e+04</td> <td>  1.4e+04</td> <td>    0.870</td> <td> 0.385</td> <td>-1.53e+04</td> <td> 3.97e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Standard Cognition</th>                                       <td>-3.694e+04</td> <td> 2.87e+04</td> <td>   -1.288</td> <td> 0.199</td> <td>-9.33e+04</td> <td> 1.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Stanford Health Care</th>                                     <td>-5.511e+04</td> <td> 1.71e+04</td> <td>   -3.216</td> <td> 0.001</td> <td>-8.88e+04</td> <td>-2.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Stanford University</th>                                      <td> 1.089e+04</td> <td> 9222.661</td> <td>    1.180</td> <td> 0.238</td> <td>-7235.745</td> <td>  2.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Steady Platform</th>                                          <td>-1.641e+04</td> <td> 2.43e+04</td> <td>   -0.674</td> <td> 0.501</td> <td>-6.43e+04</td> <td> 3.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Step</th>                                                     <td>-6544.7235</td> <td> 3.29e+04</td> <td>   -0.199</td> <td> 0.842</td> <td>-7.12e+04</td> <td> 5.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Step Mobile</th>                                              <td> 2.242e+04</td> <td> 3.36e+04</td> <td>    0.668</td> <td> 0.504</td> <td>-4.35e+04</td> <td> 8.84e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_StreetLight Data</th>                                         <td>-4.296e+04</td> <td> 3.91e+04</td> <td>   -1.098</td> <td> 0.273</td> <td> -1.2e+05</td> <td> 3.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Suki.ai</th>                                                  <td> 4.632e+04</td> <td> 1.79e+04</td> <td>    2.587</td> <td> 0.010</td> <td> 1.11e+04</td> <td> 8.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Surya Systems</th>                                            <td>-2.318e+04</td> <td> 2.55e+04</td> <td>   -0.908</td> <td> 0.364</td> <td>-7.33e+04</td> <td>  2.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Susquehanna International Group</th>                          <td> 1.145e+04</td> <td> 1.62e+04</td> <td>    0.707</td> <td> 0.480</td> <td>-2.04e+04</td> <td> 4.33e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Sutter Health</th>                                            <td> 7863.8910</td> <td> 1.06e+04</td> <td>    0.742</td> <td> 0.459</td> <td> -1.3e+04</td> <td> 2.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_SynTouch Inc.</th>                                            <td>-1.385e+04</td> <td> 7855.706</td> <td>   -1.763</td> <td> 0.078</td> <td>-2.93e+04</td> <td> 1583.372</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Synergy Solutions</th>                                        <td>-5.139e+04</td> <td> 2.72e+04</td> <td>   -1.891</td> <td> 0.059</td> <td>-1.05e+05</td> <td> 2018.677</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Synopsys</th>                                                 <td>-3.361e+04</td> <td>  2.5e+04</td> <td>   -1.344</td> <td> 0.180</td> <td>-8.27e+04</td> <td> 1.55e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TMC Software</th>                                             <td> 6110.0938</td> <td> 1.33e+04</td> <td>    0.458</td> <td> 0.647</td> <td>-2.01e+04</td> <td> 3.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Taboola</th>                                                  <td>-4.901e+04</td> <td> 2.56e+04</td> <td>   -1.912</td> <td> 0.057</td> <td>-9.94e+04</td> <td> 1364.830</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Talent Search PRO</th>                                        <td>-7.926e+04</td> <td> 4.01e+04</td> <td>   -1.975</td> <td> 0.049</td> <td>-1.58e+05</td> <td> -387.684</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Talkdesk</th>                                                 <td>-2.573e+04</td> <td>  1.4e+04</td> <td>   -1.838</td> <td> 0.067</td> <td>-5.32e+04</td> <td> 1771.521</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TalkingPoints</th>                                            <td>-5.848e+04</td> <td>  2.7e+04</td> <td>   -2.168</td> <td> 0.031</td> <td>-1.11e+05</td> <td>-5482.092</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tapcart</th>                                                  <td>-3.465e+04</td> <td> 2.62e+04</td> <td>   -1.325</td> <td> 0.186</td> <td> -8.6e+04</td> <td> 1.67e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Target</th>                                                   <td> -3.56e+04</td> <td> 1.65e+04</td> <td>   -2.158</td> <td> 0.031</td> <td> -6.8e+04</td> <td>-3190.140</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TargetCW</th>                                                 <td>-1.228e+05</td> <td> 1.57e+04</td> <td>   -7.827</td> <td> 0.000</td> <td>-1.54e+05</td> <td> -9.2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Teknatio</th>                                                 <td>-1.766e+05</td> <td> 3.35e+04</td> <td>   -5.278</td> <td> 0.000</td> <td>-2.42e+05</td> <td>-1.11e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tempus</th>                                                   <td>-2.021e+04</td> <td>  1.9e+04</td> <td>   -1.063</td> <td> 0.288</td> <td>-5.76e+04</td> <td> 1.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TeraWatt Infrastructure</th>                                  <td>-4.817e+04</td> <td> 1.31e+04</td> <td>   -3.675</td> <td> 0.000</td> <td>-7.39e+04</td> <td>-2.24e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Terrafuse AI</th>                                             <td>-2.296e+04</td> <td> 3.46e+04</td> <td>   -0.664</td> <td> 0.507</td> <td>-9.09e+04</td> <td> 4.49e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Terray Therapeutics</th>                                      <td> 6.042e+04</td> <td> 2.19e+04</td> <td>    2.763</td> <td> 0.006</td> <td> 1.74e+04</td> <td> 1.03e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tesla</th>                                                    <td> 2639.7967</td> <td> 8083.052</td> <td>    0.327</td> <td> 0.744</td> <td>-1.32e+04</td> <td> 1.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tesseract</th>                                                <td>-4330.4984</td> <td> 1.31e+04</td> <td>   -0.331</td> <td> 0.741</td> <td>-3.01e+04</td> <td> 2.14e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_The Aerospace Corporation</th>                                <td>-7.086e+04</td> <td> 3.06e+04</td> <td>   -2.318</td> <td> 0.021</td> <td>-1.31e+05</td> <td>-1.08e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_The Clorox Company</th>                                       <td>-1740.1729</td> <td> 3.02e+04</td> <td>   -0.058</td> <td> 0.954</td> <td>-6.12e+04</td> <td> 5.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_The Patrick J. McGovern Foundation</th>                       <td> 3.436e+04</td> <td>  1.2e+04</td> <td>    2.865</td> <td> 0.004</td> <td> 1.08e+04</td> <td> 5.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_The Walt Disney Studios</th>                                  <td> 1.462e+04</td> <td> 3.06e+04</td> <td>    0.478</td> <td> 0.633</td> <td>-4.55e+04</td> <td> 7.48e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_The Yes</th>                                                  <td> -6.17e+04</td> <td>  2.2e+04</td> <td>   -2.800</td> <td> 0.005</td> <td>-1.05e+05</td> <td>-1.84e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Thermo Fisher Scientific</th>                                 <td>  1.47e+04</td> <td> 1.37e+04</td> <td>    1.071</td> <td> 0.285</td> <td>-1.23e+04</td> <td> 4.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Thorn</th>                                                    <td>-6.536e+04</td> <td> 2.39e+04</td> <td>   -2.729</td> <td> 0.007</td> <td>-1.12e+05</td> <td>-1.83e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Thumbtack</th>                                                <td>-2.562e+04</td> <td> 1.29e+04</td> <td>   -1.981</td> <td> 0.048</td> <td> -5.1e+04</td> <td> -201.914</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TikTok</th>                                                   <td>  -3.3e+04</td> <td> 1.97e+04</td> <td>   -1.672</td> <td> 0.095</td> <td>-7.18e+04</td> <td> 5783.390</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tiktok Pte. Ltd.</th>                                         <td>-3.874e+04</td> <td> 2.23e+04</td> <td>   -1.739</td> <td> 0.083</td> <td>-8.25e+04</td> <td> 5040.898</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tinder</th>                                                   <td>-2.199e+04</td> <td> 1.22e+04</td> <td>   -1.802</td> <td> 0.072</td> <td> -4.6e+04</td> <td> 1990.026</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Together Labs</th>                                            <td>-3.264e+04</td> <td> 1.85e+04</td> <td>   -1.760</td> <td> 0.079</td> <td>-6.91e+04</td> <td> 3791.732</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tonal</th>                                                    <td> -7.89e+04</td> <td> 2.27e+04</td> <td>   -3.471</td> <td> 0.001</td> <td>-1.24e+05</td> <td>-3.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Totus Medicines</th>                                          <td>-7.909e+04</td> <td> 2.49e+04</td> <td>   -3.178</td> <td> 0.002</td> <td>-1.28e+05</td> <td>-3.02e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Toyota Research Institute</th>                                <td>-5165.8601</td> <td> 1.11e+04</td> <td>   -0.467</td> <td> 0.641</td> <td>-2.69e+04</td> <td> 1.66e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Transcarent</th>                                              <td>-1.674e+04</td> <td> 2.61e+04</td> <td>   -0.640</td> <td> 0.522</td> <td>-6.81e+04</td> <td> 3.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Transform Data</th>                                           <td>-2.221e+04</td> <td> 2.56e+04</td> <td>   -0.866</td> <td> 0.387</td> <td>-7.26e+04</td> <td> 2.82e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Trusaic</th>                                                  <td>-1.413e+04</td> <td> 2.21e+04</td> <td>   -0.640</td> <td> 0.523</td> <td>-5.75e+04</td> <td> 2.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TuSimple</th>                                                 <td>-1.143e+04</td> <td>  2.5e+04</td> <td>   -0.457</td> <td> 0.648</td> <td>-6.06e+04</td> <td> 3.77e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_TuSimple, Inc.</th>                                           <td> -4.79e+04</td> <td> 2.14e+04</td> <td>   -2.243</td> <td> 0.025</td> <td>-8.99e+04</td> <td>-5933.890</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Tubi</th>                                                     <td>-7.192e+04</td> <td> 2.53e+04</td> <td>   -2.841</td> <td> 0.005</td> <td>-1.22e+05</td> <td>-2.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Turntide Technologies</th>                                    <td>-7.555e+04</td> <td> 2.85e+04</td> <td>   -2.651</td> <td> 0.008</td> <td>-1.32e+05</td> <td>-1.95e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Twin Health</th>                                              <td>-8919.0819</td> <td> 1.19e+04</td> <td>   -0.748</td> <td> 0.455</td> <td>-3.24e+04</td> <td> 1.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Twitch</th>                                                   <td>-3.035e+04</td> <td>  2.1e+04</td> <td>   -1.445</td> <td> 0.149</td> <td>-7.16e+04</td> <td> 1.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Twitch Interactive, Inc.</th>                                 <td>-4.294e+04</td> <td> 2.12e+04</td> <td>   -2.022</td> <td> 0.044</td> <td>-8.47e+04</td> <td>-1207.266</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_U.S. Bank</th>                                                <td> 2.254e+04</td> <td> 1.72e+04</td> <td>    1.307</td> <td> 0.192</td> <td>-1.13e+04</td> <td> 5.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_UC San Diego</th>                                             <td> -445.8536</td> <td> 1.57e+04</td> <td>   -0.028</td> <td> 0.977</td> <td>-3.13e+04</td> <td> 3.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_UCLA</th>                                                     <td> -3.08e+04</td> <td> 2.52e+04</td> <td>   -1.222</td> <td> 0.222</td> <td>-8.03e+04</td> <td> 1.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_UCLA Health</th>                                              <td> -1.26e+04</td> <td> 2.07e+04</td> <td>   -0.610</td> <td> 0.542</td> <td>-5.32e+04</td> <td>  2.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_UKG (Ultimate Kronos Group)</th>                              <td>-2.361e+04</td> <td> 2.78e+04</td> <td>   -0.849</td> <td> 0.397</td> <td>-7.83e+04</td> <td> 3.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Uber</th>                                                     <td>-4.157e+04</td> <td> 2.12e+04</td> <td>   -1.957</td> <td> 0.051</td> <td>-8.33e+04</td> <td>  173.951</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ubisoft</th>                                                  <td>-6.387e+04</td> <td> 1.76e+04</td> <td>   -3.636</td> <td> 0.000</td> <td>-9.84e+04</td> <td>-2.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_UnitedHealth Group</th>                                       <td>  3.97e+04</td> <td> 9764.716</td> <td>    4.065</td> <td> 0.000</td> <td> 2.05e+04</td> <td> 5.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Universal Music Group</th>                                    <td> 4.146e+04</td> <td> 3.21e+04</td> <td>    1.291</td> <td> 0.197</td> <td>-2.16e+04</td> <td> 1.05e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Universal Orlando</th>                                        <td>-1.535e+04</td> <td> 5449.627</td> <td>   -2.818</td> <td> 0.005</td> <td>-2.61e+04</td> <td>-4646.490</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_University of California San Francisco</th>                   <td>-2.076e+04</td> <td> 1.04e+04</td> <td>   -1.991</td> <td> 0.047</td> <td>-4.13e+04</td> <td> -270.476</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Upgrade</th>                                                  <td>-3.021e+04</td> <td> 1.17e+04</td> <td>   -2.574</td> <td> 0.010</td> <td>-5.33e+04</td> <td>-7152.119</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Ursus</th>                                                    <td>-2.527e+04</td> <td> 2.16e+04</td> <td>   -1.171</td> <td> 0.242</td> <td>-6.77e+04</td> <td> 1.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Varo Money</th>                                               <td>-5.386e+04</td> <td> 2.67e+04</td> <td>   -2.014</td> <td> 0.045</td> <td>-1.06e+05</td> <td>-1315.877</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Velodyne</th>                                                 <td>-5286.5201</td> <td> 1.22e+04</td> <td>   -0.433</td> <td> 0.665</td> <td>-2.92e+04</td> <td> 1.87e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Verana Health</th>                                            <td> 4135.3636</td> <td> 2.69e+04</td> <td>    0.154</td> <td> 0.878</td> <td>-4.87e+04</td> <td>  5.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Verizon</th>                                                  <td> 1.361e+04</td> <td> 1.15e+04</td> <td>    1.184</td> <td> 0.237</td> <td>-8988.941</td> <td> 3.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Vertex Pharmaceuticals</th>                                   <td> 9.964e+04</td> <td> 4.56e+04</td> <td>    2.187</td> <td> 0.029</td> <td> 1.01e+04</td> <td> 1.89e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ViaSat</th>                                                   <td>-1.829e+04</td> <td> 1.33e+04</td> <td>   -1.379</td> <td> 0.169</td> <td>-4.44e+04</td> <td> 7776.395</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_VideoAmp Careers Website</th>                                 <td>-2.926e+04</td> <td> 1.19e+04</td> <td>   -2.460</td> <td> 0.014</td> <td>-5.26e+04</td> <td>-5884.259</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_View, Inc.</th>                                               <td>-4318.3913</td> <td> 2.05e+04</td> <td>   -0.211</td> <td> 0.833</td> <td>-4.45e+04</td> <td> 3.59e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Virtualitics</th>                                             <td>-1.092e+05</td> <td> 3.41e+04</td> <td>   -3.199</td> <td> 0.001</td> <td>-1.76e+05</td> <td>-4.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Visa</th>                                                     <td>-2059.6868</td> <td> 1.18e+04</td> <td>   -0.174</td> <td> 0.862</td> <td>-2.53e+04</td> <td> 2.12e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Vitria Technology</th>                                        <td>-5.979e+04</td> <td> 2.76e+04</td> <td>   -2.167</td> <td> 0.031</td> <td>-1.14e+05</td> <td>-5574.823</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Vivun</th>                                                    <td>-7.355e+04</td> <td> 1.69e+04</td> <td>   -4.355</td> <td> 0.000</td> <td>-1.07e+05</td> <td>-4.04e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Volt Workforce Solutions</th>                                 <td>-5.506e+04</td> <td> 1.39e+04</td> <td>   -3.963</td> <td> 0.000</td> <td>-8.24e+04</td> <td>-2.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Warman O'Brien</th>                                           <td>-1.872e+05</td> <td> 3.16e+04</td> <td>   -5.928</td> <td> 0.000</td> <td>-2.49e+05</td> <td>-1.25e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_WarnerMedia</th>                                              <td>-2.743e+04</td> <td> 2.52e+04</td> <td>   -1.089</td> <td> 0.277</td> <td>-7.69e+04</td> <td> 2.21e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Wayfair</th>                                                  <td>-4.519e+04</td> <td> 2.13e+04</td> <td>   -2.123</td> <td> 0.034</td> <td> -8.7e+04</td> <td>-3358.198</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Weee! Inc</th>                                                <td> 9483.3192</td> <td> 1.22e+04</td> <td>    0.779</td> <td> 0.437</td> <td>-1.45e+04</td> <td> 3.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Wells Fargo</th>                                              <td> 6744.6614</td> <td> 9960.273</td> <td>    0.677</td> <td> 0.499</td> <td>-1.28e+04</td> <td> 2.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Whip Media</th>                                               <td> 1.928e+04</td> <td> 2.64e+04</td> <td>    0.732</td> <td> 0.465</td> <td>-3.25e+04</td> <td> 7.11e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Williams Sonoma</th>                                          <td> -3.28e+04</td> <td> 2.27e+04</td> <td>   -1.447</td> <td> 0.149</td> <td>-7.73e+04</td> <td> 1.17e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Wish</th>                                                     <td>-4.282e+04</td> <td> 2.32e+04</td> <td>   -1.842</td> <td> 0.066</td> <td>-8.85e+04</td> <td> 2854.996</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Woebot Health</th>                                            <td>-4.927e+04</td> <td> 2.35e+04</td> <td>   -2.100</td> <td> 0.036</td> <td>-9.54e+04</td> <td>-3178.523</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Woodruff Sawyer</th>                                          <td>-3.144e+04</td> <td> 4.31e+04</td> <td>   -0.730</td> <td> 0.466</td> <td>-1.16e+05</td> <td> 5.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Workato</th>                                                  <td>-2.951e+04</td> <td> 2.74e+04</td> <td>   -1.075</td> <td> 0.283</td> <td>-8.34e+04</td> <td> 2.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Woven Planet Level 5</th>                                     <td>-4.124e+04</td> <td> 2.46e+04</td> <td>   -1.679</td> <td> 0.094</td> <td>-8.95e+04</td> <td> 7031.465</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_XL Data Corp</th>                                             <td> 4051.3927</td> <td> 1.05e+04</td> <td>    0.387</td> <td> 0.699</td> <td>-1.65e+04</td> <td> 2.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_XPeng Motors</th>                                             <td>-2.515e+04</td> <td> 2.01e+04</td> <td>   -1.253</td> <td> 0.211</td> <td>-6.46e+04</td> <td> 1.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Xerox</th>                                                    <td>-1.573e+04</td> <td> 1.24e+04</td> <td>   -1.273</td> <td> 0.204</td> <td>   -4e+04</td> <td> 8541.245</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ZL Technologies</th>                                          <td> 9501.8866</td> <td> 1.66e+04</td> <td>    0.572</td> <td> 0.568</td> <td>-2.32e+04</td> <td> 4.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Zenith Electronics, LLC</th>                                  <td>-4686.3133</td> <td> 1.56e+04</td> <td>   -0.300</td> <td> 0.764</td> <td>-3.54e+04</td> <td>  2.6e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Zest AI</th>                                                  <td> 9468.3453</td> <td> 2.97e+04</td> <td>    0.319</td> <td> 0.750</td> <td>-4.89e+04</td> <td> 6.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_ZineOne</th>                                                  <td>-4959.1168</td> <td> 1.27e+04</td> <td>   -0.390</td> <td> 0.697</td> <td>-2.99e+04</td> <td>    2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Zippin</th>                                                   <td> 9928.5567</td> <td> 1.96e+04</td> <td>    0.506</td> <td> 0.613</td> <td>-2.86e+04</td> <td> 4.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Zscaler</th>                                                  <td>-2.988e+04</td> <td> 1.29e+04</td> <td>   -2.317</td> <td> 0.021</td> <td>-5.52e+04</td> <td>-4545.624</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_Zuora</th>                                                    <td>-1.986e+04</td> <td> 2.35e+04</td> <td>   -0.844</td> <td> 0.399</td> <td>-6.61e+04</td> <td> 2.64e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_aiXplain</th>                                                 <td> 4799.7193</td> <td>  2.7e+04</td> <td>    0.178</td> <td> 0.859</td> <td>-4.82e+04</td> <td> 5.78e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_eHealth</th>                                                  <td> -5.49e+04</td> <td> 2.51e+04</td> <td>   -2.190</td> <td> 0.029</td> <td>-1.04e+05</td> <td>-5642.368</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_f5</th>                                                       <td>-3.876e+04</td> <td> 2.29e+04</td> <td>   -1.695</td> <td> 0.091</td> <td>-8.37e+04</td> <td> 6172.897</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_firstlight.ai</th>                                            <td> 2.997e+04</td> <td> 2.86e+04</td> <td>    1.047</td> <td> 0.296</td> <td>-2.63e+04</td> <td> 8.62e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_hims & hers</th>                                              <td>-4.401e+04</td> <td> 1.59e+04</td> <td>   -2.766</td> <td> 0.006</td> <td>-7.53e+04</td> <td>-1.27e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_iMerit</th>                                                   <td>-1.398e+05</td> <td> 2.42e+04</td> <td>   -5.768</td> <td> 0.000</td> <td>-1.87e+05</td> <td>-9.22e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_iRhythm Technologies</th>                                     <td>-8.108e+04</td> <td> 2.63e+04</td> <td>   -3.084</td> <td> 0.002</td> <td>-1.33e+05</td> <td>-2.94e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_largeton,inc</th>                                             <td>-2.531e+04</td> <td> 1.38e+04</td> <td>   -1.835</td> <td> 0.067</td> <td>-5.24e+04</td> <td> 1786.625</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_opentext</th>                                                 <td>-2.187e+04</td> <td> 3.14e+04</td> <td>   -0.696</td> <td> 0.487</td> <td>-8.36e+04</td> <td> 3.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Company_sharethrough</th>                                             <td> 2705.4785</td> <td> 1.47e+04</td> <td>    0.184</td> <td> 0.854</td> <td>-2.61e+04</td> <td> 3.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Aliso Viejo, CA</th>                                         <td> 3.178e+04</td> <td> 2.41e+04</td> <td>    1.317</td> <td> 0.188</td> <td>-1.56e+04</td> <td> 7.92e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Berkeley, CA</th>                                            <td> 1.683e+04</td> <td> 8574.855</td> <td>    1.962</td> <td> 0.050</td> <td>  -23.561</td> <td> 3.37e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Brisbane, CA</th>                                            <td> 2424.5368</td> <td> 1.06e+04</td> <td>    0.228</td> <td> 0.820</td> <td>-1.85e+04</td> <td> 2.33e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Burbank, CA</th>                                             <td>-1.377e+04</td> <td>  1.9e+04</td> <td>   -0.726</td> <td> 0.468</td> <td> -5.1e+04</td> <td> 2.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Burlingame, CA</th>                                          <td> 8.452e+04</td> <td> 1.91e+04</td> <td>    4.428</td> <td> 0.000</td> <td>  4.7e+04</td> <td> 1.22e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_California City, CA</th>                                     <td> 4051.3927</td> <td> 1.05e+04</td> <td>    0.387</td> <td> 0.699</td> <td>-1.65e+04</td> <td> 2.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Carlsbad, CA</th>                                            <td>-3.387e+04</td> <td> 1.21e+04</td> <td>   -2.801</td> <td> 0.005</td> <td>-5.76e+04</td> <td>-1.01e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Carpinteria, CA</th>                                         <td>-2.587e+04</td> <td> 8668.328</td> <td>   -2.984</td> <td> 0.003</td> <td>-4.29e+04</td> <td>-8832.491</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Carson, CA</th>                                              <td> 1173.3650</td> <td> 8888.642</td> <td>    0.132</td> <td> 0.895</td> <td>-1.63e+04</td> <td> 1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Concord, CA</th>                                             <td> 4.701e+04</td> <td> 1.44e+04</td> <td>    3.272</td> <td> 0.001</td> <td> 1.88e+04</td> <td> 7.52e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Costa Mesa, CA</th>                                          <td>-1.619e+04</td> <td> 7037.100</td> <td>   -2.301</td> <td> 0.022</td> <td>   -3e+04</td> <td>-2362.505</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Culver City, CA</th>                                         <td> 8186.5391</td> <td>  1.5e+04</td> <td>    0.547</td> <td> 0.585</td> <td>-2.12e+04</td> <td> 3.76e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Cupertino, CA</th>                                           <td> 1429.0815</td> <td> 1.27e+04</td> <td>    0.113</td> <td> 0.910</td> <td>-2.34e+04</td> <td> 2.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Davis, CA</th>                                               <td>-5959.4671</td> <td> 9510.032</td> <td>   -0.627</td> <td> 0.531</td> <td>-2.46e+04</td> <td> 1.27e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Duarte, CA</th>                                              <td> 2.664e+04</td> <td> 1.65e+04</td> <td>    1.618</td> <td> 0.106</td> <td>-5710.174</td> <td>  5.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_East Palo Alto, CA</th>                                      <td> 4.859e+04</td> <td> 1.49e+04</td> <td>    3.258</td> <td> 0.001</td> <td> 1.93e+04</td> <td> 7.79e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_El Segundo, CA</th>                                          <td> 3.283e+04</td> <td> 1.62e+04</td> <td>    2.030</td> <td> 0.043</td> <td> 1053.136</td> <td> 6.46e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Emeryville, CA</th>                                          <td>-1.657e+04</td> <td> 8813.081</td> <td>   -1.880</td> <td> 0.061</td> <td>-3.39e+04</td> <td>  747.705</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Folsom, CA</th>                                              <td>-1.484e+04</td> <td> 1.07e+04</td> <td>   -1.392</td> <td> 0.165</td> <td>-3.58e+04</td> <td> 6115.256</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Foster City, CA</th>                                         <td>-1.215e+04</td> <td> 1.01e+04</td> <td>   -1.206</td> <td> 0.229</td> <td> -3.2e+04</td> <td> 7652.234</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Fountain Valley, CA</th>                                     <td>-2.644e+04</td> <td> 1.73e+04</td> <td>   -1.532</td> <td> 0.126</td> <td>-6.03e+04</td> <td> 7470.138</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Fremont, CA</th>                                             <td>-9605.3302</td> <td> 8848.122</td> <td>   -1.086</td> <td> 0.278</td> <td> -2.7e+04</td> <td> 7780.508</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Fresno, CA</th>                                              <td> 9.021e+04</td> <td> 2.27e+04</td> <td>    3.980</td> <td> 0.000</td> <td> 4.57e+04</td> <td> 1.35e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Glendale, CA</th>                                            <td>-1.385e+04</td> <td> 7855.706</td> <td>   -1.763</td> <td> 0.078</td> <td>-2.93e+04</td> <td> 1583.372</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Hollywood, CA</th>                                           <td>-1.535e+04</td> <td> 5449.627</td> <td>   -2.818</td> <td> 0.005</td> <td>-2.61e+04</td> <td>-4646.490</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Irvine, CA</th>                                              <td>-1.114e+04</td> <td> 9530.882</td> <td>   -1.168</td> <td> 0.243</td> <td>-2.99e+04</td> <td> 7591.792</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Irwindale, CA</th>                                           <td> 1.377e+04</td> <td> 1.68e+04</td> <td>    0.819</td> <td> 0.413</td> <td>-1.93e+04</td> <td> 4.68e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Laguna Niguel, CA</th>                                       <td> -2.18e+04</td> <td> 1.18e+04</td> <td>   -1.842</td> <td> 0.066</td> <td>-4.51e+04</td> <td> 1459.446</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Lake Forest, CA</th>                                         <td> 3791.8554</td> <td> 1.63e+04</td> <td>    0.233</td> <td> 0.816</td> <td>-2.82e+04</td> <td> 3.57e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Lodi, CA</th>                                                <td> 3.509e+04</td> <td> 1.83e+04</td> <td>    1.920</td> <td> 0.055</td> <td> -825.233</td> <td>  7.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Long Beach, CA</th>                                          <td> 3.021e+04</td> <td> 1.72e+04</td> <td>    1.760</td> <td> 0.079</td> <td>-3512.466</td> <td> 6.39e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Los Altos, CA</th>                                           <td>-2.355e+04</td> <td> 1.12e+04</td> <td>   -2.112</td> <td> 0.035</td> <td>-4.55e+04</td> <td>-1637.087</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Los Angeles, CA</th>                                         <td> 1.011e+04</td> <td> 1.05e+04</td> <td>    0.965</td> <td> 0.335</td> <td>-1.05e+04</td> <td> 3.07e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Los Gatos, CA</th>                                           <td> 2.103e+04</td> <td> 1.57e+04</td> <td>    1.337</td> <td> 0.182</td> <td>-9887.326</td> <td>  5.2e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Malibu, CA</th>                                              <td> 7484.6881</td> <td> 8513.664</td> <td>    0.879</td> <td> 0.380</td> <td>-9243.967</td> <td> 2.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Marina del Rey, CA</th>                                      <td>  370.1971</td> <td> 9019.919</td> <td>    0.041</td> <td> 0.967</td> <td>-1.74e+04</td> <td> 1.81e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Menlo Park, CA</th>                                          <td> 5.201e+04</td> <td> 1.42e+04</td> <td>    3.669</td> <td> 0.000</td> <td> 2.42e+04</td> <td> 7.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Milpitas, CA</th>                                            <td>-1.815e+04</td> <td> 1.06e+04</td> <td>   -1.706</td> <td> 0.089</td> <td>-3.91e+04</td> <td> 2753.067</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Modesto, CA</th>                                             <td>-5466.7098</td> <td> 1.13e+04</td> <td>   -0.484</td> <td> 0.629</td> <td>-2.77e+04</td> <td> 1.67e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Mountain View, CA</th>                                       <td>  1.89e+04</td> <td> 9223.099</td> <td>    2.049</td> <td> 0.041</td> <td>  777.994</td> <td>  3.7e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Newark, CA</th>                                              <td>-3968.0461</td> <td> 9239.237</td> <td>   -0.429</td> <td> 0.668</td> <td>-2.21e+04</td> <td> 1.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Northridge, CA</th>                                          <td>-5619.5032</td> <td> 4727.756</td> <td>   -1.189</td> <td> 0.235</td> <td>-1.49e+04</td> <td> 3670.151</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Oakland, CA</th>                                             <td>-4.927e+04</td> <td> 1.13e+04</td> <td>   -4.378</td> <td> 0.000</td> <td>-7.14e+04</td> <td>-2.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Ontario, CA</th>                                             <td>-2.836e+04</td> <td>  1.3e+04</td> <td>   -2.173</td> <td> 0.030</td> <td> -5.4e+04</td> <td>-2717.292</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Palo Alto, CA</th>                                           <td> 1.124e+04</td> <td> 1.12e+04</td> <td>    1.006</td> <td> 0.315</td> <td>-1.07e+04</td> <td> 3.32e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Pasadena, CA</th>                                            <td> 5.582e+04</td> <td> 2.34e+04</td> <td>    2.388</td> <td> 0.017</td> <td> 9885.413</td> <td> 1.02e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Pittsburg, CA</th>                                           <td>-2.147e+04</td> <td> 5056.241</td> <td>   -4.247</td> <td> 0.000</td> <td>-3.14e+04</td> <td>-1.15e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Pleasanton, CA</th>                                          <td> 5093.6389</td> <td> 1.96e+04</td> <td>    0.260</td> <td> 0.795</td> <td>-3.34e+04</td> <td> 4.36e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Rancho Cucamonga, CA</th>                                    <td>-4821.2528</td> <td> 1.19e+04</td> <td>   -0.405</td> <td> 0.686</td> <td>-2.82e+04</td> <td> 1.86e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Redwood City, CA</th>                                        <td> 6738.3197</td> <td> 6180.398</td> <td>    1.090</td> <td> 0.276</td> <td>-5405.658</td> <td> 1.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Sacramento, CA</th>                                          <td>-9631.6834</td> <td> 2.19e+04</td> <td>   -0.439</td> <td> 0.661</td> <td>-5.27e+04</td> <td> 3.35e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Carlos, CA</th>                                          <td>-3.176e+04</td> <td> 1.12e+04</td> <td>   -2.845</td> <td> 0.005</td> <td>-5.37e+04</td> <td>-9822.520</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Clemente, CA</th>                                        <td>-3.688e+04</td> <td> 9331.674</td> <td>   -3.952</td> <td> 0.000</td> <td>-5.52e+04</td> <td>-1.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Diego, CA</th>                                           <td>-2.204e+04</td> <td> 1.51e+04</td> <td>   -1.459</td> <td> 0.145</td> <td>-5.17e+04</td> <td> 7634.751</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Francisco Bay Area, CA</th>                              <td>-3.604e+04</td> <td> 9583.441</td> <td>   -3.761</td> <td> 0.000</td> <td>-5.49e+04</td> <td>-1.72e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Francisco, CA</th>                                       <td> 3.021e+04</td> <td> 9143.241</td> <td>    3.304</td> <td> 0.001</td> <td> 1.22e+04</td> <td> 4.82e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Jose, CA</th>                                            <td> 1.022e+04</td> <td> 1.13e+04</td> <td>    0.900</td> <td> 0.368</td> <td>-1.21e+04</td> <td> 3.25e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Mateo, CA</th>                                           <td> 1.963e+04</td> <td> 1.88e+04</td> <td>    1.044</td> <td> 0.297</td> <td>-1.73e+04</td> <td> 5.66e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_San Ramon, CA</th>                                           <td> 5453.4585</td> <td> 9116.028</td> <td>    0.598</td> <td> 0.550</td> <td>-1.25e+04</td> <td> 2.34e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Santa Ana, CA</th>                                           <td> -1.96e+04</td> <td> 7977.487</td> <td>   -2.457</td> <td> 0.014</td> <td>-3.53e+04</td> <td>-3928.491</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Santa Barbara, CA</th>                                       <td>-1850.0570</td> <td> 1.57e+04</td> <td>   -0.118</td> <td> 0.906</td> <td>-3.27e+04</td> <td>  2.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Santa Clara, CA</th>                                         <td> 3039.4481</td> <td>  1.3e+04</td> <td>    0.234</td> <td> 0.815</td> <td>-2.25e+04</td> <td> 2.85e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Santa Cruz, CA</th>                                          <td> 6606.5647</td> <td> 8700.800</td> <td>    0.759</td> <td> 0.448</td> <td>-1.05e+04</td> <td> 2.37e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Santa Monica, CA</th>                                        <td>-9650.9391</td> <td> 1.23e+04</td> <td>   -0.784</td> <td> 0.434</td> <td>-3.39e+04</td> <td> 1.45e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Silicon Valley, CA</th>                                      <td> 1.988e+04</td> <td> 1.43e+04</td> <td>    1.387</td> <td> 0.166</td> <td>-8281.597</td> <td>  4.8e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_South San Francisco, CA</th>                                 <td>-1.933e+04</td> <td> 1.15e+04</td> <td>   -1.675</td> <td> 0.095</td> <td> -4.2e+04</td> <td> 3347.546</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Stanford, CA</th>                                            <td> 1.089e+04</td> <td> 9222.661</td> <td>    1.180</td> <td> 0.238</td> <td>-7235.745</td> <td>  2.9e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Sunnyvale, CA</th>                                           <td> 1.839e+04</td> <td> 9137.002</td> <td>    2.013</td> <td> 0.045</td> <td>  436.174</td> <td> 3.63e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Sylmar, CA</th>                                              <td>-2.145e+04</td> <td> 9909.512</td> <td>   -2.165</td> <td> 0.031</td> <td>-4.09e+04</td> <td>-1982.639</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Thousand Oaks, CA</th>                                       <td> 3.022e+04</td> <td> 1.25e+04</td> <td>    2.411</td> <td> 0.016</td> <td> 5589.395</td> <td> 5.49e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Union City, CA</th>                                          <td> 9949.9272</td> <td> 5554.826</td> <td>    1.791</td> <td> 0.074</td> <td> -964.852</td> <td> 2.09e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Universal City, CA</th>                                      <td>-1.535e+04</td> <td> 5449.627</td> <td>   -2.818</td> <td> 0.005</td> <td>-2.61e+04</td> <td>-4646.490</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Valencia, CA</th>                                            <td>-2.533e+04</td> <td> 9225.329</td> <td>   -2.745</td> <td> 0.006</td> <td>-4.35e+04</td> <td>-7200.982</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Venice, CA</th>                                              <td>-5752.1427</td> <td> 1.36e+04</td> <td>   -0.423</td> <td> 0.673</td> <td>-3.25e+04</td> <td>  2.1e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Ventura, CA</th>                                             <td>-2.018e+04</td> <td> 9482.579</td> <td>   -2.128</td> <td> 0.034</td> <td>-3.88e+04</td> <td>-1551.097</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Vista, CA</th>                                               <td> 9875.4540</td> <td> 1.02e+04</td> <td>    0.970</td> <td> 0.332</td> <td>-1.01e+04</td> <td> 2.99e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_West Hollywood, CA</th>                                      <td>-4003.0790</td> <td> 1.17e+04</td> <td>   -0.343</td> <td> 0.732</td> <td>-2.69e+04</td> <td> 1.89e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_West Sacramento, CA</th>                                     <td>-4779.8995</td> <td> 1.38e+04</td> <td>   -0.347</td> <td> 0.728</td> <td>-3.18e+04</td> <td> 2.23e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Westlake Village, CA</th>                                    <td>-2.957e+04</td> <td> 1.52e+04</td> <td>   -1.944</td> <td> 0.052</td> <td>-5.95e+04</td> <td>  313.485</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Location_Woodland Hills, CA</th>                                      <td> 3.021e+04</td> <td> 1.74e+04</td> <td>    1.734</td> <td> 0.084</td> <td>-4026.642</td> <td> 6.44e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Jr.</th>                                                       <td>-2.435e+04</td> <td> 2.27e+04</td> <td>   -1.071</td> <td> 0.285</td> <td> -6.9e+04</td> <td> 2.03e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Lead</th>                                                      <td>-8533.7567</td> <td> 2.32e+04</td> <td>   -0.367</td> <td> 0.714</td> <td>-5.42e+04</td> <td> 3.71e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Principal</th>                                                 <td>-2937.4538</td> <td> 2.32e+04</td> <td>   -0.127</td> <td> 0.899</td> <td>-4.85e+04</td> <td> 4.26e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Sr.</th>                                                       <td>-5654.1669</td> <td> 2.29e+04</td> <td>   -0.247</td> <td> 0.805</td> <td>-5.06e+04</td> <td> 3.93e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Staff</th>                                                     <td>-2.101e+04</td> <td> 2.31e+04</td> <td>   -0.910</td> <td> 0.363</td> <td>-6.64e+04</td> <td> 2.43e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Levels_Unknown</th>                                                   <td>-3.017e+04</td> <td>  2.3e+04</td> <td>   -1.314</td> <td> 0.189</td> <td>-7.53e+04</td> <td> 1.49e+04</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>230.753</td> <th>  Durbin-Watson:     </th> <td>   1.887</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>4342.294</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td>-0.204</td>  <th>  Prob(JB):          </th> <td>    0.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td>11.989</td>  <th>  Cond. No.          </th> <td>1.54e+17</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The smallest eigenvalue is 2.09e-31. This might indicate that there are<br/>strong multicollinearity problems or that the design matrix is singular."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                 Salary   R-squared:                       0.960\n",
       "Model:                            OLS   Adj. R-squared:                  0.894\n",
       "Method:                 Least Squares   F-statistic:                     14.44\n",
       "Date:                Wed, 29 Dec 2021   Prob (F-statistic):          1.63e-161\n",
       "Time:                        19:28:06   Log-Likelihood:                -13127.\n",
       "No. Observations:                1287   AIC:                         2.787e+04\n",
       "Df Residuals:                     480   BIC:                         3.203e+04\n",
       "Df Model:                         806                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "====================================================================================================================================\n",
       "                                                                       coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------------------------------------------------------------\n",
       "const                                                             1.721e+05   2.59e+04      6.650      0.000    1.21e+05    2.23e+05\n",
       "Analysis skills                                                   1568.1528   3150.382      0.498      0.619   -4622.092    7758.397\n",
       "Communication skills                                              1687.3015   4193.280      0.402      0.688   -6552.152    9926.755\n",
       "Research                                                         -7264.7381   4040.328     -1.798      0.073   -1.52e+04     674.177\n",
       "R                                                                -1115.9204   2956.543     -0.377      0.706   -6925.286    4693.445\n",
       "Machine learning                                                 -1701.4333   2942.585     -0.578      0.563   -7483.372    4080.506\n",
       "Bachelor's degree                                                -4203.0410   2530.474     -1.661      0.097   -9175.217     769.135\n",
       "Master's degree                                                   5423.6759   2445.846      2.218      0.027     617.788    1.02e+04\n",
       "Doctoral degree                                                  -1.154e+04   6766.282     -1.706      0.089   -2.48e+04    1752.196\n",
       "Doctor of Philosophy                                              2.452e+04   7368.802      3.327      0.001       1e+04     3.9e+04\n",
       "Power BI                                                          3147.2365   6989.562      0.450      0.653   -1.06e+04    1.69e+04\n",
       "Relational databases                                             -1.093e+04   6961.624     -1.570      0.117   -2.46e+04    2750.452\n",
       "Manufacturing                                                     4663.0619   8290.597      0.562      0.574   -1.16e+04     2.1e+04\n",
       "Microsoft Excel                                                  -8833.6073   6155.664     -1.435      0.152   -2.09e+04    3261.770\n",
       "Molecular biology                                                -4.811e+04   2.37e+04     -2.032      0.043   -9.46e+04   -1585.793\n",
       "Product management                                               -1376.1135   5101.609     -0.270      0.787   -1.14e+04    8648.133\n",
       "Usability                                                        -2.876e+04   1.74e+04     -1.656      0.098   -6.29e+04    5356.171\n",
       "Natural language processing                                      -5739.1037   3278.657     -1.750      0.081   -1.22e+04     703.191\n",
       "Python                                                            2326.1333   2833.827      0.821      0.412   -3242.106    7894.373\n",
       "SQL                                                              -4983.2880   3546.286     -1.405      0.161    -1.2e+04    1984.874\n",
       "ICD coding                                                       -4.526e+04   2.06e+04     -2.195      0.029   -8.58e+04   -4735.104\n",
       "Statistical analysis                                             -2.916e+04   6616.826     -4.407      0.000   -4.22e+04   -1.62e+04\n",
       "Tableau                                                          -2099.8870   3439.030     -0.611      0.542   -8857.302    4657.528\n",
       "Data visualization                                                1840.2062   4179.410      0.440      0.660   -6371.993    1.01e+04\n",
       "Yoga                                                             -1.799e+04   1.23e+04     -1.465      0.144   -4.21e+04    6142.720\n",
       "Writing skills                                                   -2.977e+04   5591.280     -5.325      0.000   -4.08e+04   -1.88e+04\n",
       "C++                                                              -1.017e+04   3817.192     -2.665      0.008   -1.77e+04   -2673.124\n",
       "Leadership                                                        1.668e+04   4801.977      3.473      0.001    7240.491    2.61e+04\n",
       "Computer vision                                                   2.132e+04   6196.791      3.441      0.001    9148.361    3.35e+04\n",
       "C                                                                -4131.5882   4388.373     -0.941      0.347   -1.28e+04    4491.208\n",
       "Haskell                                                          -8272.7557   5538.084     -1.494      0.136   -1.92e+04    2609.129\n",
       "Objective-C                                                      -8272.7557   5538.084     -1.494      0.136   -1.92e+04    2609.129\n",
       "Clojure                                                          -1.449e+04   1.36e+04     -1.063      0.288   -4.13e+04    1.23e+04\n",
       "MATLAB                                                           -2.115e+04   9501.189     -2.226      0.026   -3.98e+04   -2479.283\n",
       "Scala                                                            -6461.0809   5062.653     -1.276      0.202   -1.64e+04    3486.620\n",
       "Hadoop                                                           -6249.1807   4820.980     -1.296      0.196   -1.57e+04    3223.651\n",
       "Bachelor of Science                                               4197.3844   3347.418      1.254      0.210   -2380.020    1.08e+04\n",
       "Web development                                                  -7526.8776   2.64e+04     -0.285      0.776   -5.95e+04    4.44e+04\n",
       "CSS                                                               1.196e+04   1.84e+04      0.650      0.516   -2.42e+04    4.81e+04\n",
       "PyTorch                                                           1.105e+04    2.6e+04      0.425      0.671      -4e+04    6.21e+04\n",
       "TensorFlow                                                         766.5459   4063.853      0.189      0.850   -7218.594    8751.686\n",
       "Microsoft Powerpoint                                              3.288e+04   1.23e+04      2.677      0.008    8750.809     5.7e+04\n",
       "Experimental design                                               -2.69e+04   1.47e+04     -1.830      0.068   -5.58e+04    1977.393\n",
       "Statistics                                                       -2863.1648   8322.545     -0.344      0.731   -1.92e+04    1.35e+04\n",
       "Data collection                                                  -7007.3344   4517.241     -1.551      0.122   -1.59e+04    1868.676\n",
       "Data analytics                                                   -1.391e+04   5410.872     -2.570      0.010   -2.45e+04   -3275.334\n",
       "iOS                                                              -1.139e+04   9964.307     -1.143      0.254    -3.1e+04    8193.633\n",
       "Cooking                                                           6462.5589   1.01e+04      0.638      0.524   -1.34e+04    2.64e+04\n",
       "Attribution modeling                                             -2.406e+04   1.34e+04     -1.793      0.074   -5.04e+04    2303.602\n",
       "Project management                                               -4428.8051   5817.213     -0.761      0.447   -1.59e+04    7001.545\n",
       "Customer service                                                  1.088e+04   2.01e+04      0.542      0.588   -2.85e+04    5.03e+04\n",
       "Statistical software                                             -1.249e+04   1.02e+04     -1.226      0.221   -3.25e+04    7529.244\n",
       "Analytics                                                         9139.2212   4075.020      2.243      0.025    1132.139    1.71e+04\n",
       "Workday                                                           5.236e+04   2.47e+04      2.120      0.034    3840.271    1.01e+05\n",
       "SAS                                                                -65.7898   7016.128     -0.009      0.993   -1.39e+04    1.37e+04\n",
       "Supply chain                                                     -3.296e+04    1.2e+04     -2.751      0.006   -5.65e+04   -9423.015\n",
       "Spark                                                            -2017.5278   3967.438     -0.509      0.611   -9813.219    5778.164\n",
       "Shell Scripting                                                   6.461e+04   1.03e+04      6.286      0.000    4.44e+04    8.48e+04\n",
       "Data management                                                  -1.288e+04   8472.422     -1.520      0.129   -2.95e+04    3766.770\n",
       "AI                                                                1.404e+04   7672.075      1.829      0.068   -1039.510    2.91e+04\n",
       "Apache Hive                                                      -4736.4867   1.48e+04     -0.319      0.750   -3.39e+04    2.44e+04\n",
       "MapReduce                                                        -3903.5203   9502.438     -0.411      0.681   -2.26e+04    1.48e+04\n",
       "Go                                                                1.669e+04   4650.256      3.589      0.000    7552.769    2.58e+04\n",
       "Data analysis skills                                             -1.981e+04   7603.759     -2.605      0.009   -3.47e+04   -4867.552\n",
       "Database design                                                   -3.13e+04   1.14e+04     -2.737      0.006   -5.38e+04   -8828.415\n",
       "Java                                                              5786.3383   8383.273      0.690      0.490   -1.07e+04    2.23e+04\n",
       "US work authorization                                            -5540.3917   5632.850     -0.984      0.326   -1.66e+04    5527.700\n",
       "Software deployment                                              -2.412e+04   7881.543     -3.060      0.002   -3.96e+04   -8633.704\n",
       "Signal processing                                                 8439.7086   6884.123      1.226      0.221   -5087.033     2.2e+04\n",
       "Agile                                                            -1.552e+04   9209.552     -1.686      0.093   -3.36e+04    2573.281\n",
       "APIs                                                              2.374e+04   1.15e+04      2.063      0.040    1132.783    4.64e+04\n",
       "Organizational skills                                             5.895e+04   1.89e+04      3.115      0.002    2.18e+04    9.61e+04\n",
       "Cassandra                                                         1.144e+04   1.14e+04      1.006      0.315   -1.09e+04    3.38e+04\n",
       "Predictive analytics                                              1270.8500   5878.287      0.216      0.829   -1.03e+04    1.28e+04\n",
       "Deep learning                                                     -293.2060   2939.024     -0.100      0.921   -6068.149    5481.737\n",
       "Marketing automation                                               155.8872   1.43e+04      0.011      0.991   -2.78e+04    2.82e+04\n",
       "SDKs                                                             -1.889e+04   5516.846     -3.423      0.001   -2.97e+04   -8046.089\n",
       "Maven                                                            -1.889e+04   5516.846     -3.423      0.001   -2.97e+04   -8046.089\n",
       "Database management                                                858.3181   1.09e+04      0.079      0.937   -2.06e+04    2.23e+04\n",
       "Laboratory information management systems                         4.774e+04    1.4e+04      3.398      0.001    2.01e+04    7.53e+04\n",
       "REST                                                             -1.555e+04   1.23e+04     -1.265      0.206   -3.97e+04    8602.744\n",
       "System design                                                    -3023.1080   1.15e+04     -0.264      0.792   -2.56e+04    1.95e+04\n",
       "Distributed systems                                              -4525.4353   6002.717     -0.754      0.451   -1.63e+04    7269.414\n",
       "E-commerce                                                          96.5088   5241.925      0.018      0.985   -1.02e+04    1.04e+04\n",
       "NumPy                                                            -5682.0849   6220.954     -0.913      0.362   -1.79e+04    6541.582\n",
       "SciPy                                                            -6258.8624   5760.474     -1.087      0.278   -1.76e+04    5059.999\n",
       "Elasticsearch                                                     5290.5526   8419.228      0.628      0.530   -1.13e+04    2.18e+04\n",
       "Clinical Laboratory Scientist License                            -1.673e+04   1.22e+04     -1.366      0.173   -4.08e+04    7334.022\n",
       "Master of Business Administration                                -3.015e+04   1.26e+04     -2.395      0.017   -5.49e+04   -5419.565\n",
       "Business analysis                                                -2.885e+04   9903.775     -2.914      0.004   -4.83e+04   -9394.847\n",
       "Data modeling                                                     6196.4105   5779.885      1.072      0.284   -5160.592    1.76e+04\n",
       "Root cause analysis                                               2.541e+04   1.03e+04      2.468      0.014    5182.368    4.56e+04\n",
       "Software architecture                                              -3.1e+04   1.14e+04     -2.721      0.007   -5.34e+04   -8610.570\n",
       "OS Kernels                                                        1.897e+04   9055.197      2.095      0.037    1180.299    3.68e+04\n",
       "MySQL                                                            -2758.7494   1.25e+04     -0.220      0.826   -2.74e+04    2.18e+04\n",
       "Quantitative research                                            -7624.4875   8833.899     -0.863      0.389    -2.5e+04    9733.405\n",
       "PostgreSQL                                                        3574.1017   1.15e+04      0.311      0.756    -1.9e+04    2.62e+04\n",
       "Digital marketing                                                 3526.6312   9411.775      0.375      0.708    -1.5e+04     2.2e+04\n",
       "A/B testing                                                      -8081.3349   4934.542     -1.638      0.102   -1.78e+04    1614.638\n",
       "Big data                                                         -4.466e+04    1.4e+04     -3.201      0.001   -7.21e+04   -1.72e+04\n",
       "Pandas                                                            1.447e+04   6325.775      2.287      0.023    2038.709    2.69e+04\n",
       "Management                                                        2.785e+04   1.09e+04      2.547      0.011    6360.890    4.93e+04\n",
       "ETL                                                              -1.145e+04   1.25e+04     -0.916      0.360    -3.6e+04    1.31e+04\n",
       "Unit testing                                                     -7.975e+04    1.5e+04     -5.305      0.000   -1.09e+05   -5.02e+04\n",
       "Military                                                         -3.774e+04    1.7e+04     -2.220      0.027   -7.11e+04   -4338.045\n",
       "UNIX                                                              3.083e+04   1.04e+04      2.957      0.003    1.03e+04    5.13e+04\n",
       "Criminal background check                                        -1451.9179    1.3e+04     -0.111      0.911    -2.7e+04    2.41e+04\n",
       "Test automation                                                  -1.301e+04   6359.840     -2.046      0.041   -2.55e+04    -512.834\n",
       "Quality assurance                                                -1.301e+04   6359.840     -2.046      0.041   -2.55e+04    -512.834\n",
       "Test cases                                                       -1.301e+04   6359.840     -2.046      0.041   -2.55e+04    -512.834\n",
       "Ab Initio                                                        -4.026e+04   9941.372     -4.050      0.000   -5.98e+04   -2.07e+04\n",
       "Library services                                                 -4.026e+04   9941.372     -4.050      0.000   -5.98e+04   -2.07e+04\n",
       "Keras                                                            -2.128e+04   5143.921     -4.137      0.000   -3.14e+04   -1.12e+04\n",
       "Flow cytometry                                                   -3875.1202   1.01e+04     -0.385      0.700   -2.36e+04    1.59e+04\n",
       "Assays                                                           -3875.1202   1.01e+04     -0.385      0.700   -2.36e+04    1.59e+04\n",
       "Sage                                                              8897.0666   8747.332      1.017      0.310   -8290.727    2.61e+04\n",
       "Data mining                                                      -1.692e+04   4899.721     -3.453      0.001   -2.65e+04   -7289.318\n",
       "Bioinformatics                                                   -2730.4071   1.22e+04     -0.224      0.823   -2.67e+04    2.13e+04\n",
       "Laboratory experience                                            -5.461e+04   1.55e+04     -3.517      0.000   -8.51e+04   -2.41e+04\n",
       "Teaching                                                          6655.7545   1.66e+04      0.400      0.689    -2.6e+04    3.94e+04\n",
       "Stata                                                             1.816e+04   1.27e+04      1.433      0.152   -6732.295    4.31e+04\n",
       "Pre-employment physical examination                              -6.561e+04    1.4e+04     -4.688      0.000   -9.31e+04   -3.81e+04\n",
       "GIS                                                              -6569.6958   1.16e+04     -0.566      0.571   -2.94e+04    1.62e+04\n",
       "Apache                                                            3330.8810   1.46e+04      0.228      0.820   -2.54e+04    3.21e+04\n",
       "Adobe Photoshop                                                   5.594e+04   1.17e+04      4.765      0.000    3.29e+04     7.9e+04\n",
       "Fraud                                                            -9529.6522   3924.065     -2.429      0.016   -1.72e+04   -1819.184\n",
       "Math                                                              3742.4855   1.12e+04      0.335      0.738   -1.82e+04    2.57e+04\n",
       "Clinical trials                                                   -581.9703   1.02e+04     -0.057      0.954   -2.06e+04    1.94e+04\n",
       "Presentation skills                                                1.83e+04   1.04e+04      1.766      0.078   -2063.227    3.87e+04\n",
       "Live chat                                                        -3.458e+04    1.7e+04     -2.033      0.043    -6.8e+04   -1154.262\n",
       "Algorithm design                                                 -1452.9775   1.17e+04     -0.124      0.901   -2.44e+04    2.15e+04\n",
       "Senior leadership                                                 1664.7955   9792.260      0.170      0.865   -1.76e+04    2.09e+04\n",
       "LabView                                                          -3621.7247   1.45e+04     -0.250      0.803   -3.21e+04    2.48e+04\n",
       "Product development                                              -3.004e+04   1.37e+04     -2.197      0.029   -5.69e+04   -3169.504\n",
       "Git                                                              -1.875e+04   9279.942     -2.020      0.044    -3.7e+04    -512.899\n",
       "Recruiting                                                        -565.4436   3473.204     -0.163      0.871   -7390.006    6259.118\n",
       "IT sourcing                                                       -565.4436   3473.204     -0.163      0.871   -7390.006    6259.118\n",
       "Sourcing                                                          -565.4436   3473.204     -0.163      0.871   -7390.006    6259.118\n",
       "HR sourcing                                                       -565.4436   3473.204     -0.163      0.871   -7390.006    6259.118\n",
       "Torch                                                            -2612.1471   2.61e+04     -0.100      0.920   -5.39e+04    4.87e+04\n",
       "JavaScript                                                       -2.912e+04   2.15e+04     -1.354      0.176   -7.14e+04    1.31e+04\n",
       "GitHub                                                           -2.959e+04   1.15e+04     -2.571      0.010   -5.22e+04   -6975.065\n",
       "Intellectual property law                                         1557.2427   1.31e+04      0.119      0.905   -2.41e+04    2.72e+04\n",
       "Conversion optimization                                           4.696e+04   1.99e+04      2.358      0.019    7822.573    8.61e+04\n",
       "Jenkins                                                           5.087e+04   2.47e+04      2.055      0.040    2240.904    9.95e+04\n",
       "Azure                                                             3079.5824   7370.612      0.418      0.676   -1.14e+04    1.76e+04\n",
       "Node.js                                                          -3.817e+04   3.34e+04     -1.143      0.253   -1.04e+05    2.74e+04\n",
       "Business development                                                  1e+04   2.01e+04      0.498      0.619   -2.95e+04    4.95e+04\n",
       "Apache Pig                                                         2.46e+04   1.39e+04      1.772      0.077   -2676.008    5.19e+04\n",
       "Teradata                                                         -6552.3291   1.12e+04     -0.587      0.558   -2.85e+04    1.54e+04\n",
       "Google Analytics                                                  -3.56e+04   1.54e+04     -2.305      0.022   -6.59e+04   -5249.165\n",
       "Sentiment analytics                                              -2.825e+04   1.57e+04     -1.804      0.072    -5.9e+04    2511.854\n",
       "Industrial equipment                                             -8739.5431   8243.187     -1.060      0.290   -2.49e+04    7457.648\n",
       "Mechanical knowledge                                             -8739.5431   8243.187     -1.060      0.290   -2.49e+04    7457.648\n",
       "Ansible                                                          -3.261e+04   3.69e+04     -0.883      0.377   -1.05e+05    3.99e+04\n",
       "Cloud architecture                                                1.366e+04    1.4e+04      0.978      0.329   -1.38e+04    4.11e+04\n",
       "Linux                                                             1.091e+05   1.89e+04      5.767      0.000    7.19e+04    1.46e+05\n",
       "Cleaning                                                         -8.235e+04   1.95e+04     -4.216      0.000   -1.21e+05    -4.4e+04\n",
       "Computer skills                                                  -3.159e+04   2.87e+04     -1.100      0.272    -8.8e+04    2.48e+04\n",
       "JSON                                                              3.326e+04   1.45e+04      2.295      0.022    4781.770    6.17e+04\n",
       "High school diploma or GED                                       -1.546e+04   1.46e+04     -1.061      0.289   -4.41e+04    1.32e+04\n",
       "Microservices                                                    -1.307e+04   1.28e+04     -1.023      0.307   -3.82e+04     1.2e+04\n",
       "NoSQL                                                            -2842.8863   8159.515     -0.348      0.728   -1.89e+04    1.32e+04\n",
       "21 years or older                                                -1.785e+04   1.29e+04     -1.382      0.168   -4.32e+04    7525.820\n",
       "Drug discovery                                                   -2.804e+04    2.1e+04     -1.337      0.182   -6.93e+04    1.32e+04\n",
       "Supply chain management                                           2639.7967   8083.052      0.327      0.744   -1.32e+04    1.85e+04\n",
       ".NET                                                             -4341.4630   1.85e+04     -0.235      0.814   -4.06e+04    3.19e+04\n",
       "Kubernetes                                                         693.7107   1.12e+04      0.062      0.951   -2.13e+04    2.27e+04\n",
       "ADAS                                                             -8124.8212   1.28e+04     -0.636      0.525   -3.32e+04     1.7e+04\n",
       "Master of Science                                                -1.083e+04   5503.301     -1.967      0.050   -2.16e+04     -11.715\n",
       "Microsoft Access                                                   159.8419   1.43e+04      0.011      0.991   -2.79e+04    2.83e+04\n",
       "Lean                                                             -7305.1188   7294.369     -1.001      0.317   -2.16e+04    7027.721\n",
       "Perl                                                             -3.272e+04   1.21e+04     -2.709      0.007   -5.64e+04   -8985.028\n",
       "PHP                                                               7748.4529   1.84e+04      0.421      0.674   -2.84e+04    4.39e+04\n",
       "OOP                                                              -1.194e+04   1.48e+04     -0.810      0.418   -4.09e+04     1.7e+04\n",
       "D3.js                                                             2.438e+04   1.37e+04      1.777      0.076   -2575.187    5.13e+04\n",
       "Software development                                             -2.045e+04   6713.579     -3.045      0.002   -3.36e+04   -7253.506\n",
       "Mentoring                                                         1.482e+04   6321.205      2.344      0.019    2397.913    2.72e+04\n",
       "Lucene                                                            4.343e+04   2.01e+04      2.163      0.031    3983.847    8.29e+04\n",
       "Data structures                                                   -2.18e+04   7959.027     -2.739      0.006   -3.74e+04   -6164.042\n",
       "Jira                                                             -2.604e+04   2.07e+04     -1.257      0.209   -6.68e+04    1.47e+04\n",
       "Master of Engineering                                             3.616e+04   1.28e+04      2.814      0.005    1.09e+04    6.14e+04\n",
       "Confluence                                                       -2.302e+04   2.73e+04     -0.843      0.399   -7.66e+04    3.06e+04\n",
       "Employee evaluation                                              -1.273e+04   2.01e+04     -0.633      0.527   -5.22e+04    2.68e+04\n",
       "Auto estimating                                                  -9126.2096   1.35e+04     -0.675      0.500   -3.57e+04    1.74e+04\n",
       "Construction estimating                                          -1.572e+04   5147.651     -3.053      0.002   -2.58e+04   -5603.286\n",
       "Banking                                                          -4330.7072   2.19e+04     -0.198      0.844   -4.74e+04    3.88e+04\n",
       "Martech                                                          -5.547e+04   1.42e+04     -3.916      0.000   -8.33e+04   -2.76e+04\n",
       "Docker                                                            9.735e+04   1.85e+04      5.252      0.000    6.09e+04    1.34e+05\n",
       "Bachelor of Arts                                                 -2.137e+04   1.55e+04     -1.376      0.169   -5.19e+04    9143.183\n",
       "Business intelligence                                             5883.6711   1.55e+04      0.379      0.705   -2.46e+04    3.64e+04\n",
       "Ontology                                                          1.469e+05   1.64e+04      8.975      0.000    1.15e+05    1.79e+05\n",
       "Neo4j                                                            -3.804e+04   1.04e+04     -3.655      0.000   -5.85e+04   -1.76e+04\n",
       "Market research                                                    100.6002   9870.179      0.010      0.992   -1.93e+04    1.95e+04\n",
       "Windows                                                          -2.231e+04    1.8e+04     -1.236      0.217   -5.78e+04    1.32e+04\n",
       "SPSS                                                             -1960.1768   2.83e+04     -0.069      0.945   -5.76e+04    5.36e+04\n",
       "Social media management                                            945.3113   7738.656      0.122      0.903   -1.43e+04    1.62e+04\n",
       "Time management                                                    3.06e+04   1.44e+04      2.128      0.034    2339.974    5.89e+04\n",
       "Forecasting                                                      -9539.5949   1.55e+04     -0.614      0.540   -4.01e+04     2.1e+04\n",
       "Financial modeling                                               -2.104e+04   1.17e+04     -1.792      0.074   -4.41e+04    2032.222\n",
       "Internet of things                                               -8919.0819   1.19e+04     -0.748      0.455   -3.24e+04    1.45e+04\n",
       "CI/CD                                                            -8742.6270   2.57e+04     -0.340      0.734   -5.92e+04    4.17e+04\n",
       "Data warehouse                                                   -4.907e+04   2.12e+04     -2.311      0.021   -9.08e+04   -7356.286\n",
       "Application development                                          -1.106e+04   1.49e+04     -0.741      0.459   -4.04e+04    1.83e+04\n",
       "Scripting                                                        -5.822e+04   7867.026     -7.400      0.000   -7.37e+04   -4.28e+04\n",
       "Bash                                                              1452.1761   1.48e+04      0.098      0.922   -2.77e+04    3.06e+04\n",
       "Microsoft Office                                                 -1.868e+04   8721.855     -2.141      0.033   -3.58e+04   -1538.888\n",
       "QuickBooks                                                        2.148e+04   1.61e+04      1.336      0.182   -1.01e+04    5.31e+04\n",
       "Public health                                                     9683.9446   2.58e+04      0.375      0.708    -4.1e+04    6.04e+04\n",
       "Marketing                                                        -1.448e+04   1.13e+04     -1.281      0.201   -3.67e+04    7735.867\n",
       "TypeScript                                                       -4036.1577   5456.295     -0.740      0.460   -1.48e+04    6685.018\n",
       "Swift                                                            -9655.6609   5517.100     -1.750      0.081   -2.05e+04    1184.991\n",
       "Sensors                                                          -3.406e+04   9287.167     -3.668      0.000   -5.23e+04   -1.58e+04\n",
       "Performance marketing                                            -8171.2490   1.01e+04     -0.805      0.421   -2.81e+04    1.18e+04\n",
       "SSIS                                                             -7.704e+04   1.61e+04     -4.773      0.000   -1.09e+05   -4.53e+04\n",
       "Financial services                                                3.849e+04   1.09e+04      3.537      0.000    1.71e+04    5.99e+04\n",
       "Telecommunication                                                 2.825e+04   2.78e+04      1.018      0.309   -2.63e+04    8.28e+04\n",
       "Associate's degree                                               -6.475e+04   2.17e+04     -2.989      0.003   -1.07e+05   -2.22e+04\n",
       "GitLab                                                            2.261e+04   1.12e+04      2.014      0.045     550.990    4.47e+04\n",
       "Full-stack development                                            -986.0430   2.89e+04     -0.034      0.973   -5.78e+04    5.58e+04\n",
       "Regression analysis                                              -1.915e+04   8290.597     -2.309      0.021   -3.54e+04   -2855.424\n",
       "Legal drafting                                                   -2717.0338   8064.652     -0.337      0.736   -1.86e+04    1.31e+04\n",
       "Drafting                                                         -2717.0338   8064.652     -0.337      0.736   -1.86e+04    1.31e+04\n",
       "Design thinking                                                   -1.44e+04   1.18e+04     -1.219      0.223   -3.76e+04    8811.007\n",
       "AWS                                                               1.814e+04   1.52e+04      1.195      0.233   -1.17e+04     4.8e+04\n",
       "Terraform                                                         1.072e+04   3.12e+04      0.343      0.732   -5.07e+04    7.21e+04\n",
       "Bank Secrecy Act                                                 -3.964e+04   8853.520     -4.478      0.000    -5.7e+04   -2.22e+04\n",
       "Cognos                                                           -3.964e+04   8853.520     -4.478      0.000    -5.7e+04   -2.22e+04\n",
       "Filing                                                            1.121e+04   1.95e+04      0.576      0.565    -2.7e+04    4.95e+04\n",
       "Negotiation                                                      -5.656e+04   2.66e+04     -2.126      0.034   -1.09e+05   -4282.244\n",
       "Graph databases                                                  -3116.7735   6385.921     -0.488      0.626   -1.57e+04    9431.041\n",
       "DynamoDB                                                         -6462.5722   1.66e+04     -0.390      0.697    -3.9e+04    2.61e+04\n",
       "SEM                                                              -3.487e+04   1.05e+04     -3.327      0.001   -5.55e+04   -1.43e+04\n",
       "Web services                                                      1.318e+04   1.18e+04      1.118      0.264   -9980.887    3.63e+04\n",
       "Patient monitoring                                                3.385e+04   2.27e+04      1.490      0.137   -1.08e+04    7.85e+04\n",
       "Qualitative research                                             -2.524e+04   1.34e+04     -1.885      0.060   -5.16e+04    1067.069\n",
       "HITRUST                                                          -1.273e+04   1.54e+04     -0.828      0.408   -4.29e+04    1.75e+04\n",
       "Continuous integration                                           -8040.9962    1.4e+04     -0.576      0.565   -3.55e+04    1.94e+04\n",
       "System testing                                                    3924.8247   2.01e+04      0.195      0.845   -3.56e+04    4.34e+04\n",
       "Kanban                                                              58.0628   1.26e+04      0.005      0.996   -2.47e+04    2.48e+04\n",
       "Rust                                                               139.5141    1.4e+04      0.010      0.992   -2.74e+04    2.77e+04\n",
       "Research & development                                            5.129e+04    1.3e+04      3.947      0.000    2.58e+04    7.68e+04\n",
       "Dart                                                             -5619.5032   4727.756     -1.189      0.235   -1.49e+04    3670.151\n",
       "Pricing                                                           6.487e+04   1.92e+04      3.374      0.001    2.71e+04    1.03e+05\n",
       "OpenCV                                                           -7032.0034   2.04e+04     -0.345      0.730    -4.7e+04     3.3e+04\n",
       "Affiliate marketing                                               1334.3409   1.39e+04      0.096      0.924   -2.61e+04    2.87e+04\n",
       "Ruby on Rails                                                       69.4623   1.03e+04      0.007      0.995   -2.02e+04    2.03e+04\n",
       "Growing experience                                               -8626.2141   1.25e+04     -0.689      0.491   -3.32e+04     1.6e+04\n",
       "Scrum                                                             3.446e+04   9848.779      3.499      0.001    1.51e+04    5.38e+04\n",
       "VBA                                                               4.785e+04   2.38e+04      2.012      0.045    1121.832    9.46e+04\n",
       "Ceridian                                                         -2.258e+04   2.85e+04     -0.793      0.428   -7.85e+04    3.34e+04\n",
       "MTA                                                               2.533e+04   1.05e+04      2.407      0.016    4650.107     4.6e+04\n",
       "New Relic                                                         7843.1707   2.01e+04      0.390      0.696   -3.16e+04    4.73e+04\n",
       "Sailpoint                                                         1.933e+04   2.96e+04      0.653      0.514   -3.88e+04    7.75e+04\n",
       "DevOps                                                           -1.332e+04   8715.071     -1.528      0.127   -3.04e+04    3803.787\n",
       "Backbone.js                                                      -3.384e+04   6221.590     -5.439      0.000   -4.61e+04   -2.16e+04\n",
       "Computer networking                                               -719.2005   7111.260     -0.101      0.919   -1.47e+04    1.33e+04\n",
       "Calibration                                                      -9133.6624   1.19e+04     -0.767      0.444   -3.25e+04    1.43e+04\n",
       "Computer science                                                  -9.21e+04   2.55e+04     -3.607      0.000   -1.42e+05   -4.19e+04\n",
       "Survival analysis                                                -2.548e+04   1.38e+04     -1.842      0.066   -5.27e+04    1702.707\n",
       "Project management methodology                                   -2.147e+04   5056.241     -4.247      0.000   -3.14e+04   -1.15e+04\n",
       "Figma                                                            -7914.3272   2575.138     -3.073      0.002    -1.3e+04   -2854.390\n",
       "Visual design                                                    -7914.3272   2575.138     -3.073      0.002    -1.3e+04   -2854.390\n",
       "InVision                                                         -7914.3272   2575.138     -3.073      0.002    -1.3e+04   -2854.390\n",
       "User research                                                    -7914.3272   2575.138     -3.073      0.002    -1.3e+04   -2854.390\n",
       "Cloud computing                                                   -2.08e+04   1.46e+04     -1.425      0.155   -4.95e+04    7890.837\n",
       "Flask                                                            -1811.9563   1.67e+04     -0.109      0.913   -3.46e+04    3.09e+04\n",
       "Six Sigma Certification                                            2.34e+04   8794.165      2.661      0.008    6124.191    4.07e+04\n",
       "Lean Six Sigma Certification                                       2.34e+04   8794.165      2.661      0.008    6124.191    4.07e+04\n",
       "React                                                             4.089e+04   1.42e+04      2.881      0.004     1.3e+04    6.88e+04\n",
       "Computer graphics                                                 -973.5861   1.56e+04     -0.062      0.950   -3.16e+04    2.97e+04\n",
       "Operations research                                                740.9268    1.8e+04      0.041      0.967   -3.47e+04    3.62e+04\n",
       "Human resources                                                  -1.164e+04   9732.149     -1.196      0.232   -3.08e+04    7482.174\n",
       "SaaS                                                              2108.1078   1.89e+04      0.112      0.911    -3.5e+04    3.92e+04\n",
       "Driver's License                                                 -3.021e+04   1.17e+04     -2.574      0.010   -5.33e+04   -7152.119\n",
       "Marketing mix modeling                                            9949.9272   5554.826      1.791      0.074    -964.852    2.09e+04\n",
       "Continuous improvement                                            9493.0284   1.07e+04      0.884      0.377   -1.16e+04    3.06e+04\n",
       "Linguistics                                                      -2.452e+04   1.57e+04     -1.558      0.120   -5.54e+04    6396.211\n",
       "Geometry                                                         -3.543e+04   2.04e+04     -1.739      0.083   -7.55e+04    4607.883\n",
       "Agriculture                                                      -3716.7572   8968.730     -0.414      0.679   -2.13e+04    1.39e+04\n",
       "Supervising experience                                           -3716.7572   8968.730     -0.414      0.679   -2.13e+04    1.39e+04\n",
       "DB2                                                              -4.402e+04   1.65e+04     -2.666      0.008   -7.65e+04   -1.16e+04\n",
       "Inventory control                                                 -1.44e+04   1.78e+04     -0.809      0.419   -4.94e+04    2.06e+04\n",
       "Alteryx                                                           4266.4865   2.71e+04      0.158      0.875   -4.89e+04    5.74e+04\n",
       "Pass drug screening                                               7223.6617   9545.228      0.757      0.450   -1.15e+04     2.6e+04\n",
       "Integration testing                                              -3.225e+04   1.47e+04     -2.190      0.029   -6.12e+04   -3310.909\n",
       "Program management                                               -2.181e+04   1.44e+04     -1.512      0.131   -5.01e+04    6523.833\n",
       "Databases                                                         3.251e+04   2.54e+04      1.278      0.202   -1.75e+04    8.25e+04\n",
       "RDF                                                               1.683e+04   1.22e+04      1.381      0.168   -7123.274    4.08e+04\n",
       "Change management                                                 3237.9009   1.29e+04      0.250      0.802   -2.22e+04    2.86e+04\n",
       "ICD-10                                                           -3.148e+04   1.04e+04     -3.030      0.003   -5.19e+04   -1.11e+04\n",
       "18 years or older                                                -6398.7547   8692.938     -0.736      0.462   -2.35e+04    1.07e+04\n",
       "Lever                                                            -2.605e+04   1.19e+04     -2.185      0.029   -4.95e+04   -2628.964\n",
       "CRM software                                                     -2.072e+04   5861.043     -3.535      0.000   -3.22e+04   -9200.762\n",
       "Intelligence targeting                                           -2.072e+04   5861.043     -3.535      0.000   -3.22e+04   -9200.762\n",
       "Customer segmentation                                            -2.072e+04   5861.043     -3.535      0.000   -3.22e+04   -9200.762\n",
       "Service-oriented architecture                                     4.127e+04   2.38e+04      1.735      0.083   -5470.154     8.8e+04\n",
       "Julia                                                            -2.926e+04   1.19e+04     -2.460      0.014   -5.26e+04   -5884.259\n",
       "Team management                                                  -1.196e+04   8018.968     -1.492      0.136   -2.77e+04    3795.069\n",
       "AdRoll                                                           -1.921e+04   1.31e+04     -1.464      0.144    -4.5e+04    6573.110\n",
       "Medical records                                                    3.97e+04   9764.716      4.065      0.000    2.05e+04    5.89e+04\n",
       "Project planning                                                 -2.516e+04   1.37e+04     -1.843      0.066    -5.2e+04    1665.455\n",
       "Strategic planning                                               -4874.2787   1.41e+04     -0.345      0.731   -3.27e+04    2.29e+04\n",
       "Reliable transportation                                          -8326.7221   1.22e+04     -0.683      0.495   -3.23e+04    1.56e+04\n",
       "Debugging                                                         3.376e+04   1.81e+04      1.861      0.063   -1889.722    6.94e+04\n",
       "EHR systems                                                      -1.036e+04   1.19e+04     -0.868      0.386   -3.38e+04    1.31e+04\n",
       "Scalability                                                        384.4163   2.61e+04      0.015      0.988   -5.08e+04    5.16e+04\n",
       "C#                                                               -1.195e+04   1.34e+04     -0.891      0.373   -3.83e+04    1.44e+04\n",
       "Technical writing                                                -9441.4127   2.32e+04     -0.406      0.685   -5.51e+04    3.62e+04\n",
       "Design patterns                                                   4.425e+04   1.56e+04      2.839      0.005    1.36e+04    7.49e+04\n",
       "Solr                                                             -9144.2840   2.47e+04     -0.370      0.711   -5.77e+04    3.94e+04\n",
       "Image processing                                                 -1.537e+04   1.33e+04     -1.158      0.247   -4.14e+04    1.07e+04\n",
       "Biostatistics                                                     8104.2126   1.54e+04      0.526      0.599   -2.22e+04    3.84e+04\n",
       "Production design                                                -2.562e+04   1.29e+04     -1.981      0.048    -5.1e+04    -201.914\n",
       "Operating systems                                                -2.988e+04   1.29e+04     -2.317      0.021   -5.52e+04   -4545.624\n",
       "Google Cloud Platform                                            -1.136e+05   2.38e+04     -4.765      0.000    -1.6e+05   -6.67e+04\n",
       "FDA regulations                                                  -1.355e+04    1.1e+04     -1.232      0.219   -3.52e+04    8058.997\n",
       "Certified Nephrology Nurse                                       -1.862e+04   8260.763     -2.254      0.025   -3.48e+04   -2384.764\n",
       "Training & development                                            6.627e+04    2.7e+04      2.450      0.015    1.31e+04    1.19e+05\n",
       "Google Ads                                                        2202.1140   2.46e+04      0.090      0.929   -4.61e+04    5.05e+04\n",
       "Medical terminology                                              -9269.1533    1.3e+04     -0.716      0.474   -3.47e+04    1.62e+04\n",
       "Algebra                                                          -3.837e+04   2.47e+04     -1.555      0.121   -8.69e+04    1.01e+04\n",
       "Search engines                                                   -3.083e+04   1.23e+04     -2.511      0.012    -5.5e+04   -6706.413\n",
       "Current immunizations                                             5.282e+04   1.74e+04      3.031      0.003    1.86e+04    8.71e+04\n",
       "Translation                                                       7361.2876    1.5e+04      0.491      0.624   -2.21e+04    3.68e+04\n",
       "Tooling                                                           2.015e+04   1.79e+04      1.126      0.261    -1.5e+04    5.53e+04\n",
       "Quantitative analysis                                            -7127.4239   1.74e+04     -0.409      0.683   -4.14e+04    2.71e+04\n",
       "Investment                                                       -1.794e+04   1.61e+04     -1.111      0.267   -4.97e+04    1.38e+04\n",
       "Database marketing                                               -2.286e+04   1.15e+04     -1.992      0.047   -4.54e+04    -312.574\n",
       "Construction                                                     -1.499e+04   7388.625     -2.029      0.043   -2.95e+04    -472.920\n",
       "Construction management software                                   727.0345   5932.402      0.123      0.903   -1.09e+04    1.24e+04\n",
       "ProCore                                                            727.0345   5932.402      0.123      0.903   -1.09e+04    1.24e+04\n",
       "Test-driven development                                          -1.429e+04    1.1e+04     -1.305      0.193   -3.58e+04    7230.656\n",
       "Cloud infrastructure                                             -4.807e+04   1.42e+04     -3.378      0.001    -7.6e+04   -2.01e+04\n",
       "Robotics                                                          5.832e+04   3.68e+04      1.586      0.113   -1.39e+04    1.31e+05\n",
       "System architecture                                              -4.566e+04   1.87e+04     -2.448      0.015   -8.23e+04   -9012.225\n",
       "Packaging                                                        -4.115e+04   1.28e+04     -3.220      0.001   -6.63e+04    -1.6e+04\n",
       "Customer relationship management                                 -5752.1427   1.36e+04     -0.423      0.673   -3.25e+04     2.1e+04\n",
       "Sales                                                             3.944e+04   1.45e+04      2.720      0.007     1.1e+04    6.79e+04\n",
       "Data science                                                       5.79e+04   1.53e+04      3.783      0.000    2.78e+04     8.8e+04\n",
       "SOAP                                                             -4.817e+04   1.31e+04     -3.675      0.000   -7.39e+04   -2.24e+04\n",
       "Assembly                                                         -8714.1508   7228.193     -1.206      0.229   -2.29e+04    5488.659\n",
       "Encryption                                                       -8714.1508   7228.193     -1.206      0.229   -2.29e+04    5488.659\n",
       "SPARQL                                                            9104.2128   1.47e+04      0.619      0.536   -1.98e+04     3.8e+04\n",
       "ServiceNow                                                        9841.5713   1.41e+04      0.697      0.486   -1.79e+04    3.76e+04\n",
       "Taxonomy                                                          -3.88e+04   1.19e+04     -3.270      0.001   -6.21e+04   -1.55e+04\n",
       "Oracle                                                           -4.688e+04   1.47e+04     -3.190      0.002   -7.57e+04    -1.8e+04\n",
       "Doctor of Dentistry                                              -3.643e+04   1.49e+04     -2.437      0.015   -6.58e+04   -7057.174\n",
       "VMWare                                                           -3.393e+04   1.99e+04     -1.707      0.088    -7.3e+04    5118.595\n",
       "Database administration                                          -3.935e+04   1.12e+04     -3.522      0.000   -6.13e+04   -1.74e+04\n",
       "Clinical development                                             -1.144e+04   6195.451     -1.846      0.066   -2.36e+04     738.014\n",
       "CDISC standards                                                  -1.144e+04   6195.451     -1.846      0.066   -2.36e+04     738.014\n",
       "Microscopy                                                       -1.297e+04   1.73e+04     -0.751      0.453   -4.69e+04    2.09e+04\n",
       "Spectroscopy                                                     -4330.4984   1.31e+04     -0.331      0.741   -3.01e+04    2.14e+04\n",
       "SoC                                                              -3438.5079   1.08e+04     -0.317      0.751   -2.47e+04    1.79e+04\n",
       "GLP                                                               5068.1305   7459.262      0.679      0.497   -9588.711    1.97e+04\n",
       "CGMP                                                              5068.1305   7459.262      0.679      0.497   -9588.711    1.97e+04\n",
       "Bootstrap                                                         1.706e+04   1.54e+04      1.105      0.270   -1.33e+04    4.74e+04\n",
       "Lending                                                           2.504e+04   2.47e+04      1.014      0.311   -2.35e+04    7.35e+04\n",
       "Grant writing                                                    -1.573e+04   1.24e+04     -1.273      0.204      -4e+04    8541.245\n",
       "Pass polygraph test                                              -1.185e+04   8604.348     -1.377      0.169   -2.88e+04    5054.629\n",
       "Pivot tables                                                      -1.36e+04   7359.387     -1.847      0.065   -2.81e+04     864.448\n",
       "Editing                                                          -3331.1732   1.29e+04     -0.259      0.796   -2.86e+04    2.19e+04\n",
       "Title_Data Analyst                                               -1.336e+04   8174.274     -1.634      0.103   -2.94e+04    2706.037\n",
       "Title_Data Architect                                               5.92e+04   1.41e+04      4.199      0.000    3.15e+04    8.69e+04\n",
       "Title_Data Engineer                                               3.297e+04   8256.950      3.994      0.000    1.68e+04    4.92e+04\n",
       "Title_Data Science Manager                                        4.683e+04   6082.849      7.698      0.000    3.49e+04    5.88e+04\n",
       "Title_Data Scientist                                              1.981e+04   5216.060      3.798      0.000    9559.705    3.01e+04\n",
       "Title_Director of Data Science                                    7.062e+04   9501.931      7.432      0.000    5.19e+04    8.93e+04\n",
       "Title_Head of Data Science                                        3.694e+04   1.18e+04      3.119      0.002    1.37e+04    6.02e+04\n",
       "Title_Machine Learning Engineer                                   2.455e+04   5643.537      4.350      0.000    1.35e+04    3.56e+04\n",
       "Title_Machine Learning Scientist                                  8155.6580   6109.121      1.335      0.183   -3848.266    2.02e+04\n",
       "Title_Software Engineer                                           3.104e+04   6487.497      4.785      0.000    1.83e+04    4.38e+04\n",
       "Title_Statistician                                               -2.757e+04   2.04e+04     -1.352      0.177   -6.76e+04    1.25e+04\n",
       "Title_Vice President of Data Science                              4.164e+04   1.41e+04      2.947      0.003    1.39e+04    6.94e+04\n",
       "Company_3T Biosciences                                           -3.162e+04   2.08e+04     -1.520      0.129   -7.25e+04    9255.740\n",
       "Company_6sense                                                   -6.759e+04   2.49e+04     -2.710      0.007   -1.17e+05   -1.86e+04\n",
       "Company_8th Wall                                                 -4.048e+04    1.3e+04     -3.114      0.002    -6.6e+04   -1.49e+04\n",
       "Company_99                                                       -2.637e+04   2.24e+04     -1.179      0.239   -7.03e+04    1.76e+04\n",
       "Company_ABB                                                      -4.534e+04   1.52e+04     -2.974      0.003   -7.53e+04   -1.54e+04\n",
       "Company_AE Studio                                                -5752.1427   1.36e+04     -0.423      0.673   -3.25e+04     2.1e+04\n",
       "Company_ASML                                                     -8739.5431   8243.187     -1.060      0.290   -2.49e+04    7457.648\n",
       "Company_AT&T                                                     -4.778e+04   2.43e+04     -1.966      0.050   -9.55e+04     -30.601\n",
       "Company_AWM Smart Shelf (Adroit Worldwide Media, Inc.)           -6.136e+04   3.47e+04     -1.769      0.078    -1.3e+05    6796.320\n",
       "Company_Abacus.ai                                                -6.424e+04   2.39e+04     -2.692      0.007   -1.11e+05   -1.74e+04\n",
       "Company_Abbott Laboratories                                      -2.145e+04   9909.512     -2.165      0.031   -4.09e+04   -1982.639\n",
       "Company_Abl Schools                                              -5.138e+04   2.33e+04     -2.204      0.028   -9.72e+04   -5569.933\n",
       "Company_Abnormal Security                                        -7.217e+04   2.34e+04     -3.080      0.002   -1.18e+05   -2.61e+04\n",
       "Company_Accenture                                                 1.322e+04   2.63e+04      0.502      0.616   -3.85e+04     6.5e+04\n",
       "Company_Accion Opportunity Fund                                  -8.355e+04    2.5e+04     -3.348      0.001   -1.33e+05   -3.45e+04\n",
       "Company_Activision                                                 -2.4e+04   2.37e+04     -1.013      0.312   -7.06e+04    2.26e+04\n",
       "Company_Adobe                                                     1.714e+04   1.55e+04      1.109      0.268   -1.32e+04    4.75e+04\n",
       "Company_Afresh                                                    -1.44e+04   1.78e+04     -0.809      0.419   -4.94e+04    2.06e+04\n",
       "Company_Afterpay Touch                                           -3.737e+04   2.12e+04     -1.759      0.079   -7.91e+04    4362.577\n",
       "Company_Agilent Technologies, Inc.                               -4.432e+04   2.57e+04     -1.725      0.085   -9.48e+04    6175.062\n",
       "Company_AiCard                                                    1.981e+05   2.25e+04      8.789      0.000    1.54e+05    2.42e+05\n",
       "Company_Airtable                                                 -2.838e+04   1.19e+04     -2.387      0.017   -5.17e+04   -5018.061\n",
       "Company_Aisera                                                    9841.5713   1.41e+04      0.697      0.486   -1.79e+04    3.76e+04\n",
       "Company_Akamai                                                    -2.55e+04   2.41e+04     -1.057      0.291   -7.29e+04    2.19e+04\n",
       "Company_Albertsons Companies                                     -7531.8663   2.91e+04     -0.259      0.796   -6.48e+04    4.97e+04\n",
       "Company_AlignTech                                                -1.028e+04   2.54e+04     -0.405      0.686   -6.02e+04    3.96e+04\n",
       "Company_Allbirds                                                 -8.067e+04   2.59e+04     -3.114      0.002   -1.32e+05   -2.98e+04\n",
       "Company_Amazon Dev Center U.S., Inc.                              2.603e+04   2.62e+04      0.994      0.321   -2.54e+04    7.75e+04\n",
       "Company_Amazon Web Services, Inc.                                -6.955e+04   2.28e+04     -3.044      0.002   -1.14e+05   -2.47e+04\n",
       "Company_Amazon.com Services LLC                                  -1988.5332   2.12e+04     -0.094      0.925   -4.36e+04    3.96e+04\n",
       "Company_Amgen                                                     3.022e+04   1.25e+04      2.411      0.016    5589.395    5.49e+04\n",
       "Company_Amino, Inc.                                              -2.466e+04    2.4e+04     -1.027      0.305   -7.19e+04    2.25e+04\n",
       "Company_Anthem                                                   -2.947e+04   2.65e+04     -1.112      0.267   -8.16e+04    2.26e+04\n",
       "Company_Apartment List                                           -4.566e+04   2.41e+04     -1.893      0.059    -9.3e+04    1725.480\n",
       "Company_App Annie                                                -2.965e+04   2.71e+04     -1.096      0.274   -8.28e+04    2.35e+04\n",
       "Company_Aquabyte                                                 -6.403e+04   2.39e+04     -2.677      0.008   -1.11e+05    -1.7e+04\n",
       "Company_Aquent                                                   -3062.2987   1.34e+04     -0.229      0.819   -2.93e+04    2.32e+04\n",
       "Company_Arcules, Inc.                                            -9.803e+04   2.41e+04     -4.072      0.000   -1.45e+05   -5.07e+04\n",
       "Company_Argo AI                                                  -3.997e+04   2.43e+04     -1.645      0.101   -8.77e+04    7784.065\n",
       "Company_Ariat International                                       9949.9272   5554.826      1.791      0.074    -964.852    2.09e+04\n",
       "Company_Artizen, Inc.                                            -4.522e+04   2.94e+04     -1.540      0.124   -1.03e+05    1.25e+04\n",
       "Company_Aruba Networks                                           -8481.8936   2.58e+04     -0.329      0.742   -5.91e+04    4.22e+04\n",
       "Company_Ask Media Group                                          -3.519e+04   1.87e+04     -1.883      0.060   -7.19e+04    1536.395\n",
       "Company_AstraZeneca                                              -3.306e+04   1.31e+04     -2.517      0.012   -5.89e+04   -7247.703\n",
       "Company_Atlassian                                                 1.083e+04   2.78e+04      0.389      0.697   -4.38e+04    6.55e+04\n",
       "Company_Atomic AI                                                 3.616e+04   1.28e+04      2.814      0.005    1.09e+04    6.14e+04\n",
       "Company_Atomwise                                                 -4.336e+04   2.42e+04     -1.791      0.074   -9.09e+04    4208.889\n",
       "Company_Atreca                                                   -5.268e+04   2.11e+04     -2.500      0.013   -9.41e+04   -1.13e+04\n",
       "Company_Aurora                                                   -4.516e+04   2.26e+04     -1.994      0.047   -8.97e+04    -665.737\n",
       "Company_Aurora Innovation                                        -7.096e+04   2.04e+04     -3.483      0.001   -1.11e+05   -3.09e+04\n",
       "Company_Auryc                                                    -1.838e+04   1.43e+04     -1.288      0.198   -4.64e+04    9666.262\n",
       "Company_AutoX Inc                                                -2.432e+04    2.5e+04     -0.974      0.331   -7.34e+04    2.48e+04\n",
       "Company_Automat Solutions, Inc.                                   1.211e+04    1.4e+04      0.863      0.388   -1.55e+04    3.97e+04\n",
       "Company_Avanade                                                  -2.371e+04   2.84e+04     -0.835      0.404   -7.95e+04    3.21e+04\n",
       "Company_Aven                                                     -4036.1577   5456.295     -0.740      0.460   -1.48e+04    6685.018\n",
       "Company_Aviatrix                                                 -1.783e+04   1.35e+04     -1.324      0.186   -4.43e+04    8629.342\n",
       "Company_Avila Trading                                            -3.348e+04   2.41e+04     -1.388      0.166   -8.09e+04    1.39e+04\n",
       "Company_BBI                                                      -2.147e+04   5056.241     -4.247      0.000   -3.14e+04   -1.15e+04\n",
       "Company_BICP                                                     -5.143e+04   2.36e+04     -2.180      0.030   -9.78e+04   -5079.741\n",
       "Company_BOEING                                                   -8.475e+04   2.63e+04     -3.226      0.001   -1.36e+05   -3.31e+04\n",
       "Company_BOLD                                                     -9427.4657      2e+04     -0.471      0.638   -4.88e+04    2.99e+04\n",
       "Company_BXGI                                                     -2.379e+04   2.54e+04     -0.935      0.350   -7.38e+04    2.62e+04\n",
       "Company_Baidu USA                                                -1.707e+04   2.36e+04     -0.723      0.470   -6.34e+04    2.93e+04\n",
       "Company_Bayer                                                    -4.822e+04   2.45e+04     -1.970      0.049   -9.63e+04    -122.784\n",
       "Company_Belcan                                                   -4.111e+04   1.35e+04     -3.039      0.003   -6.77e+04   -1.45e+04\n",
       "Company_Big Data Federation, Inc.                                  -5.2e+04   2.76e+04     -1.882      0.060   -1.06e+05    2291.965\n",
       "Company_Black Sesame Technologies Inc                            -5.183e+04    2.4e+04     -2.164      0.031   -9.89e+04   -4759.651\n",
       "Company_BlackBerry                                               -1.119e+04   1.62e+04     -0.690      0.491   -4.31e+04    2.07e+04\n",
       "Company_Blink Health                                             -3.705e+04   2.37e+04     -1.566      0.118   -8.36e+04    9448.627\n",
       "Company_Blockchain.com                                            3224.5817   2.42e+04      0.133      0.894   -4.44e+04    5.08e+04\n",
       "Company_Blue River Technology                                    -3.052e+04   1.82e+04     -1.674      0.095   -6.63e+04    5297.584\n",
       "Company_Bosch Group                                              -3427.9600   4.16e+04     -0.082      0.934   -8.51e+04    7.83e+04\n",
       "Company_BrainChip, Inc.                                          -3438.5079   1.08e+04     -0.317      0.751   -2.47e+04    1.79e+04\n",
       "Company_Brambles Group                                           -1.009e+04   2.49e+04     -0.405      0.686    -5.9e+04    3.89e+04\n",
       "Company_Brightline                                               -1.164e+04   9732.149     -1.196      0.232   -3.08e+04    7482.174\n",
       "Company_Bristol Myers Squibb                                      1.492e+04   1.69e+04      0.880      0.379   -1.84e+04    4.82e+04\n",
       "Company_ByteDance                                                -3.201e+04      2e+04     -1.599      0.111   -7.14e+04    7333.794\n",
       "Company_C3 AI                                                     2.491e+04   1.36e+04      1.826      0.068   -1887.799    5.17e+04\n",
       "Company_CEDENT                                                   -4.821e+04   2.37e+04     -2.034      0.042   -9.48e+04   -1639.100\n",
       "Company_CHEP                                                     -3.355e+04   2.62e+04     -1.283      0.200   -8.49e+04    1.78e+04\n",
       "Company_CaaStle                                                  -2.321e+04    2.5e+04     -0.930      0.353   -7.23e+04    2.58e+04\n",
       "Company_CalPrivate Bank                                          -3.964e+04   8853.520     -4.478      0.000    -5.7e+04   -2.22e+04\n",
       "Company_Calico                                                    1.488e+04   1.23e+04      1.208      0.227   -9313.089    3.91e+04\n",
       "Company_California Institute of Technology                       -3.888e+04   4.17e+04     -0.933      0.351   -1.21e+05     4.3e+04\n",
       "Company_Cameo                                                    -4.536e+04   2.37e+04     -1.915      0.056   -9.19e+04    1194.220\n",
       "Company_Capella Space                                            -3.011e+04   2.35e+04     -1.282      0.200   -7.62e+04     1.6e+04\n",
       "Company_Cardlytics                                                2.033e+04   2.76e+04      0.736      0.462   -3.39e+04    7.46e+04\n",
       "Company_CareDx                                                   -3787.7316   9219.559     -0.411      0.681   -2.19e+04    1.43e+04\n",
       "Company_Cash App                                                 -5.371e+04   2.21e+04     -2.434      0.015   -9.71e+04   -1.03e+04\n",
       "Company_Centene Corporation                                      -2.201e+04   1.12e+04     -1.970      0.049    -4.4e+04     -53.344\n",
       "Company_Cepheid                                                   6324.0355   1.28e+04      0.494      0.621   -1.88e+04    3.15e+04\n",
       "Company_Chan Zuckerberg Initiative                               -1.648e+04   2.45e+04     -0.673      0.502   -6.46e+04    3.17e+04\n",
       "Company_Checkmate Partners                                        7.157e+04   2.49e+04      2.871      0.004    2.26e+04    1.21e+05\n",
       "Company_Chime                                                    -7.563e+04   2.49e+04     -3.033      0.003   -1.25e+05   -2.66e+04\n",
       "Company_Chronus Health, Inc.                                     -1.862e+04   8260.763     -2.254      0.025   -3.48e+04   -2384.764\n",
       "Company_Circle                                                   -1.294e+05   3.09e+04     -4.186      0.000    -1.9e+05   -6.87e+04\n",
       "Company_Cisco Meraki                                             -4.316e+04   2.21e+04     -1.956      0.051   -8.65e+04     201.230\n",
       "Company_City of Hope                                             -7.542e+04   2.29e+04     -3.297      0.001    -1.2e+05   -3.05e+04\n",
       "Company_Clarify Health Solutions.                                 -7.72e+04   2.74e+04     -2.820      0.005   -1.31e+05   -2.34e+04\n",
       "Company_Clarivate Analytics                                      -3.083e+04   1.23e+04     -2.511      0.012    -5.5e+04   -6706.413\n",
       "Company_ClassDojo                                                -4.498e+04    2.4e+04     -1.870      0.062   -9.22e+04    2272.762\n",
       "Company_ClimateAI                                                 4413.6291   9546.053      0.462      0.644   -1.43e+04    2.32e+04\n",
       "Company_Clinical Management Consultants                          -1.673e+04   1.22e+04     -1.366      0.173   -4.08e+04    7334.022\n",
       "Company_Cloudleaf                                                -6.025e+04   2.72e+04     -2.216      0.027   -1.14e+05   -6834.425\n",
       "Company_Cloudwick                                                 -1.83e+04   9614.694     -1.903      0.058   -3.72e+04     595.963\n",
       "Company_Cobalt Robotics                                          -5.044e+04   2.91e+04     -1.731      0.084   -1.08e+05    6820.418\n",
       "Company_Coda                                                     -2.305e+04   2.53e+04     -0.911      0.363   -7.28e+04    2.67e+04\n",
       "Company_Cogitativo                                               -5.265e+04   1.77e+04     -2.967      0.003   -8.75e+04   -1.78e+04\n",
       "Company_Colsh Consultants                                        -4.497e+04   2.51e+04     -1.793      0.074   -9.43e+04    4302.979\n",
       "Company_Convex Tech                                              -1.787e+05   2.35e+04     -7.590      0.000   -2.25e+05   -1.32e+05\n",
       "Company_CooTek                                                   -1.108e+05   2.41e+04     -4.592      0.000   -1.58e+05   -6.34e+04\n",
       "Company_Course Hero                                              -4.451e+04   1.61e+04     -2.772      0.006   -7.61e+04    -1.3e+04\n",
       "Company_Cowbell Cyber Inc.                                         -2.3e+04   2.52e+04     -0.914      0.361   -7.25e+04    2.65e+04\n",
       "Company_Cox Automotive                                           -2.563e+04   1.25e+04     -2.047      0.041   -5.02e+04   -1032.471\n",
       "Company_Cox Communications Inc                                   -2.543e+04   2.71e+04     -0.939      0.348   -7.87e+04    2.78e+04\n",
       "Company_Credible                                                 -2.516e+04   1.37e+04     -1.843      0.066    -5.2e+04    1665.455\n",
       "Company_Crossover Health                                         -3.688e+04   9331.674     -3.952      0.000   -5.52e+04   -1.85e+04\n",
       "Company_CrowdRise                                                  1.74e+04    1.2e+04      1.454      0.147   -6121.283    4.09e+04\n",
       "Company_CyberCoders                                              -3.006e+04   2.23e+04     -1.346      0.179    -7.4e+04    1.38e+04\n",
       "Company_CyberCube                                                -7.582e+04   2.44e+04     -3.105      0.002   -1.24e+05   -2.78e+04\n",
       "Company_DG Savants                                               -6.208e+04   1.87e+04     -3.325      0.001   -9.88e+04   -2.54e+04\n",
       "Company_Databricks                                               -6.377e+04   2.46e+04     -2.592      0.010   -1.12e+05   -1.54e+04\n",
       "Company_Datatron Technologies                                    -6.534e+04   2.95e+04     -2.213      0.027   -1.23e+05   -7316.272\n",
       "Company_Decipher Biosciences                                     -3.179e+04   2.61e+04     -1.217      0.224   -8.31e+04    1.95e+04\n",
       "Company_DecisionLogic                                            -7750.7256      2e+04     -0.387      0.699   -4.71e+04    3.16e+04\n",
       "Company_DeepMap, Inc                                             -2.012e+04   3.04e+04     -0.662      0.508   -7.99e+04    3.96e+04\n",
       "Company_DeepVu                                                    -6.81e+04   1.86e+04     -3.663      0.000   -1.05e+05   -3.16e+04\n",
       "Company_Denali Therapeutics                                      -1.144e+04   6195.451     -1.846      0.066   -2.36e+04     738.014\n",
       "Company_Dermalogica LLC                                           1173.3650   8888.642      0.132      0.895   -1.63e+04    1.86e+04\n",
       "Company_Deserve, Inc.                                            -5.504e+04   2.48e+04     -2.219      0.027   -1.04e+05   -6291.428\n",
       "Company_Dexcom                                                    3.588e+04    3.1e+04      1.156      0.248   -2.51e+04    9.68e+04\n",
       "Company_DiDi Labs                                                -5.016e+04   3.08e+04     -1.628      0.104   -1.11e+05    1.04e+04\n",
       "Company_Diffbot                                                  -3.057e+04   3.11e+04     -0.982      0.326   -9.17e+04    3.06e+04\n",
       "Company_Discord                                                  -3.788e+04   2.22e+04     -1.710      0.088   -8.14e+04    5647.257\n",
       "Company_Disney Media & Entertainment Distribution                -2961.1954   2.67e+04     -0.111      0.912   -5.55e+04    4.95e+04\n",
       "Company_DocuSign                                                 -2.377e+04   2.24e+04     -1.062      0.289   -6.77e+04    2.02e+04\n",
       "Company_Dollar Shave Club                                          370.1971   9019.919      0.041      0.967   -1.74e+04    1.81e+04\n",
       "Company_Doma                                                     -3.653e+04    2.2e+04     -1.663      0.097   -7.97e+04    6619.975\n",
       "Company_Dropbox                                                  -6.657e+04   2.37e+04     -2.808      0.005   -1.13e+05      -2e+04\n",
       "Company_Dynamic Solutions Technology LLC                          1.238e+04   2.23e+04      0.554      0.579   -3.15e+04    5.63e+04\n",
       "Company_E. & J. Gallo Winery                                     -5.495e+04   1.23e+04     -4.471      0.000   -7.91e+04   -3.08e+04\n",
       "Company_EDO, Inc                                                    69.4623   1.03e+04      0.007      0.995   -2.02e+04    2.03e+04\n",
       "Company_ELT Solutions                                            -4.532e+04   2.51e+04     -1.803      0.072   -9.47e+04    4063.063\n",
       "Company_ENERGY SOLUTIONS                                         -1.868e+04   8721.855     -2.141      0.033   -3.58e+04   -1538.888\n",
       "Company_EVB                                                      -4.384e+04   2.89e+04     -1.517      0.130   -1.01e+05    1.29e+04\n",
       "Company_Earnin                                                    -3.87e+04   2.42e+04     -1.598      0.111   -8.63e+04    8890.259\n",
       "Company_EasyPost                                                 -2.582e+04   2.72e+04     -0.949      0.343   -7.93e+04    2.77e+04\n",
       "Company_Edmunds.com                                              -4.115e+04   1.28e+04     -3.220      0.001   -6.63e+04    -1.6e+04\n",
       "Company_Edwards Lifesciences                                      8700.4958   2.48e+04      0.351      0.726   -4.01e+04    5.75e+04\n",
       "Company_Electronic Arts                                          -2.114e+04   1.32e+04     -1.601      0.110   -4.71e+04    4809.688\n",
       "Company_Empower Retirement                                       -1.562e+04   2.55e+04     -0.612      0.541   -6.57e+04    3.45e+04\n",
       "Company_Engage3                                                  -5959.4671   9510.032     -0.627      0.531   -2.46e+04    1.27e+04\n",
       "Company_Envision                                                 -2.512e+04   1.72e+04     -1.460      0.145   -5.89e+04    8692.150\n",
       "Company_Ericsson                                                 -2.843e+04   2.51e+04     -1.131      0.259   -7.78e+04     2.1e+04\n",
       "Company_Essex Property Trust                                     -4.093e+04   1.96e+04     -2.089      0.037   -7.94e+04   -2435.173\n",
       "Company_Ethos Life                                               -5.065e+04   2.35e+04     -2.158      0.031   -9.68e+04   -4523.464\n",
       "Company_Evernote                                                 -7.939e+04   2.46e+04     -3.231      0.001   -1.28e+05   -3.11e+04\n",
       "Company_Evolver. LLC, a CSS Company                              -7.704e+04   1.61e+04     -4.773      0.000   -1.09e+05   -4.53e+04\n",
       "Company_Exagen, Inc.                                             -1.058e+04   1.34e+04     -0.789      0.431   -3.69e+04    1.58e+04\n",
       "Company_Exai Bio Inc                                             -5.639e+04   2.75e+04     -2.052      0.041    -1.1e+05   -2379.987\n",
       "Company_Experian                                                 -1.619e+04   7037.100     -2.301      0.022      -3e+04   -2362.505\n",
       "Company_Exponent                                                 -8.232e+04   2.97e+04     -2.776      0.006   -1.41e+05   -2.41e+04\n",
       "Company_Extend                                                   -2.997e+04   2.21e+04     -1.356      0.176   -7.34e+04    1.35e+04\n",
       "Company_Ezoic                                                    -3.028e+04   2.12e+04     -1.427      0.154    -7.2e+04    1.14e+04\n",
       "Company_Facebook App                                             -6.493e+04   2.26e+04     -2.870      0.004   -1.09e+05   -2.05e+04\n",
       "Company_Faire                                                    -4.212e+04   2.37e+04     -1.775      0.076   -8.87e+04    4495.552\n",
       "Company_Farmers Insurance Group                                  -1.024e+05   3.42e+04     -2.993      0.003    -1.7e+05   -3.52e+04\n",
       "Company_FieldLevel                                               -6.005e+04   2.48e+04     -2.418      0.016   -1.09e+05   -1.13e+04\n",
       "Company_Figure                                                   -5.119e+04   2.71e+04     -1.888      0.060   -1.04e+05    2083.996\n",
       "Company_First American                                            -1.96e+04   7977.487     -2.457      0.014   -3.53e+04   -3928.491\n",
       "Company_First Republic Bank                                      -3.743e+04   2.45e+04     -1.525      0.128   -8.57e+04    1.08e+04\n",
       "Company_Fiserv                                                    4938.4805   2.47e+04      0.200      0.841   -4.35e+04    5.34e+04\n",
       "Company_Fisker Inc                                               -3.906e+04   2.44e+04     -1.598      0.111   -8.71e+04    8968.354\n",
       "Company_Fitbod                                                    -2.08e+04   1.46e+04     -1.425      0.155   -4.95e+04    7890.837\n",
       "Company_Ford Motor Company                                       -2.766e+04   2.64e+04     -1.048      0.295   -7.95e+04    2.42e+04\n",
       "Company_FortressIQ                                               -9.367e+04   2.68e+04     -3.497      0.001   -1.46e+05    -4.1e+04\n",
       "Company_Forward                                                  -6.015e+04    2.1e+04     -2.871      0.004   -1.01e+05    -1.9e+04\n",
       "Company_Forward Slope Inc.                                        1.511e+04   2.72e+04      0.555      0.579   -3.84e+04    6.86e+04\n",
       "Company_Foursquare                                               -7346.2718   2.37e+04     -0.310      0.757   -5.39e+04    3.92e+04\n",
       "Company_Fox Corporation                                          -8.855e+04   3.16e+04     -2.800      0.005   -1.51e+05   -2.64e+04\n",
       "Company_Freedom Financial Network                                 -7.16e+04   2.72e+04     -2.628      0.009   -1.25e+05   -1.81e+04\n",
       "Company_Frequence                                                 5618.2757   2.28e+04      0.247      0.805   -3.91e+04    5.03e+04\n",
       "Company_FriendFinder Networks                                    -1.785e+04   1.29e+04     -1.382      0.168   -4.32e+04    7525.820\n",
       "Company_GE Corporate                                              5453.4585   9116.028      0.598      0.550   -1.25e+04    2.34e+04\n",
       "Company_Gap Inc.                                                 -7.187e+04    2.4e+04     -2.994      0.003   -1.19e+05   -2.47e+04\n",
       "Company_Gayathri's Sandbox                                       -1.191e+05   2.66e+04     -4.487      0.000   -1.71e+05    -6.7e+04\n",
       "Company_Geli                                                     -6.944e+04   2.34e+04     -2.972      0.003   -1.15e+05   -2.35e+04\n",
       "Company_Genentech                                                -5.416e+04    2.2e+04     -2.467      0.014   -9.73e+04    -1.1e+04\n",
       "Company_Getaround                                                  -7.4e+04   2.94e+04     -2.515      0.012   -1.32e+05   -1.62e+04\n",
       "Company_Getty Images                                             -5.079e+04   2.21e+04     -2.299      0.022   -9.42e+04   -7390.111\n",
       "Company_Gilead Sciences                                          -1.009e+04   1.02e+04     -0.988      0.324   -3.02e+04    9976.403\n",
       "Company_Ginger                                                     -5.2e+04   2.81e+04     -1.851      0.065   -1.07e+05    3188.148\n",
       "Company_Glassdoor                                                 -6.16e+04   2.23e+04     -2.766      0.006   -1.05e+05   -1.78e+04\n",
       "Company_GoFundMe                                                   1.74e+04    1.2e+04      1.454      0.147   -6121.283    4.09e+04\n",
       "Company_Golden State Foods                                       -2.873e+04   1.76e+04     -1.632      0.103   -6.33e+04    5852.989\n",
       "Company_GoodRx                                                     1.28e+04   2.99e+04      0.429      0.668   -4.59e+04    7.15e+04\n",
       "Company_Google                                                   -3.299e+04   2.22e+04     -1.483      0.139   -7.67e+04    1.07e+04\n",
       "Company_GotIt!                                                   -7.955e+04   2.91e+04     -2.733      0.007   -1.37e+05   -2.24e+04\n",
       "Company_Grammarly                                                 1.076e+05   2.59e+04      4.148      0.000    5.66e+04    1.59e+05\n",
       "Company_Grammarly, Inc.                                          -6.687e+04    2.3e+04     -2.902      0.004   -1.12e+05   -2.16e+04\n",
       "Company_Groove.co                                                -3.917e+04   2.78e+04     -1.411      0.159   -9.37e+04    1.54e+04\n",
       "Company_Groq                                                     -8.425e+04   2.52e+04     -3.347      0.001   -1.34e+05   -3.48e+04\n",
       "Company_HANUMAYAMMA INNOVATIONS AND TECHNOLOGIES                 -3.406e+04   9287.167     -3.668      0.000   -5.23e+04   -1.58e+04\n",
       "Company_HG Insights                                              -1.273e+05   3.19e+04     -3.988      0.000    -1.9e+05   -6.46e+04\n",
       "Company_HRL Laboratories LLC                                      7484.6881   8513.664      0.879      0.380   -9243.967    2.42e+04\n",
       "Company_Happiest Baby, Inc.                                       9713.6147   2.67e+04      0.364      0.716   -4.27e+04    6.22e+04\n",
       "Company_Harnham                                                   -478.2492   2.21e+04     -0.022      0.983   -4.39e+04    4.29e+04\n",
       "Company_Hayden AI Technologies                                   -3.424e+04   3.04e+04     -1.125      0.261    -9.4e+04    2.55e+04\n",
       "Company_Health Net of California                                 -2.201e+04   1.12e+04     -1.970      0.049    -4.4e+04     -53.344\n",
       "Company_Healthcare Staffing Professionals, Inc.                  -5.311e+04   3.53e+04     -1.504      0.133   -1.22e+05    1.63e+04\n",
       "Company_Heap                                                     -8.447e+04   2.39e+04     -3.537      0.000   -1.31e+05   -3.75e+04\n",
       "Company_Helio Health Inc.                                         9814.1883   1.51e+04      0.650      0.516   -1.99e+04    3.95e+04\n",
       "Company_Herophilus                                               -6.385e+04   2.29e+04     -2.785      0.006   -1.09e+05   -1.88e+04\n",
       "Company_Hewlett Packard Enterprise                               -3.435e+04   2.72e+04     -1.265      0.206   -8.77e+04     1.9e+04\n",
       "Company_Hippo Insurance                                          -1.156e+04   2.25e+04     -0.513      0.608   -5.58e+04    3.27e+04\n",
       "Company_Hive                                                     -4.542e+04   2.48e+04     -1.832      0.068   -9.41e+04    3301.910\n",
       "Company_Hulu                                                     -3711.9900   2.29e+04     -0.162      0.871   -4.87e+04    4.13e+04\n",
       "Company_Hurricane Electric                                       -3.384e+04   6221.590     -5.439      0.000   -4.61e+04   -2.16e+04\n",
       "Company_Hypersonix Inc.                                          -3.058e+04   3.48e+04     -0.879      0.380   -9.89e+04    3.78e+04\n",
       "Company_IBM                                                      -8272.7557   5538.084     -1.494      0.136   -1.92e+04    2609.129\n",
       "Company_ICW Group                                                 1.437e+04   2.99e+04      0.481      0.631   -4.43e+04    7.31e+04\n",
       "Company_ICW Group Holdings, Inc                                   1.437e+04   2.99e+04      0.481      0.631   -4.43e+04    7.31e+04\n",
       "Company_ISO                                                       -2.85e+04   2.54e+04     -1.122      0.262   -7.84e+04    2.14e+04\n",
       "Company_Ignitech Solutions LLC                                   -8.926e+04   4.13e+04     -2.161      0.031    -1.7e+05   -8106.375\n",
       "Company_Illumina                                                 -1.298e+04   1.39e+04     -0.932      0.352   -4.03e+04    1.44e+04\n",
       "Company_Indeed                                                    6.911e+04   2.25e+04      3.068      0.002    2.48e+04    1.13e+05\n",
       "Company_Infogen Labs                                             -2.533e+04   9225.329     -2.745      0.006   -4.35e+04   -7200.982\n",
       "Company_Inland Empire Health Plans                               -4821.2528   1.19e+04     -0.405      0.686   -2.82e+04    1.86e+04\n",
       "Company_Inspire                                                  -3.502e+04   2.54e+04     -1.377      0.169    -8.5e+04     1.5e+04\n",
       "Company_Instacart                                                -3.224e+04   2.26e+04     -1.428      0.154   -7.66e+04    1.21e+04\n",
       "Company_Instagram                                                -8.816e+04   2.35e+04     -3.759      0.000   -1.34e+05   -4.21e+04\n",
       "Company_Intel                                                    -1.484e+04   1.07e+04     -1.392      0.165   -3.58e+04    6115.256\n",
       "Company_Intellimize                                              -6.025e+04   2.69e+04     -2.236      0.026   -1.13e+05   -7299.406\n",
       "Company_Intuit                                                   -4.001e+04   1.97e+04     -2.028      0.043   -7.88e+04   -1250.417\n",
       "Company_Intuitive                                                -5.455e+04   2.31e+04     -2.365      0.018   -9.99e+04   -9233.390\n",
       "Company_Invitae                                                  -1.253e+05   2.42e+04     -5.166      0.000   -1.73e+05   -7.76e+04\n",
       "Company_Ipsos North America                                        100.6002   9870.179      0.010      0.992   -1.93e+04    1.95e+04\n",
       "Company_Itron                                                    -1051.6427   3.17e+04     -0.033      0.974   -6.34e+04    6.13e+04\n",
       "Company_J.D. Power                                               -1.311e+04   2.36e+04     -0.556      0.578   -5.94e+04    3.32e+04\n",
       "Company_JD.com                                                   -2.264e+04   2.56e+04     -0.885      0.377   -7.29e+04    2.77e+04\n",
       "Company_JPL/NASA                                                 -1.028e+05   3.23e+04     -3.184      0.002   -1.66e+05   -3.94e+04\n",
       "Company_Jane Technologies                                        -8.153e+04   2.84e+04     -2.873      0.004   -1.37e+05   -2.58e+04\n",
       "Company_Jazz Pharmaceuticals                                     -4.944e+04   2.48e+04     -1.991      0.047   -9.82e+04    -644.858\n",
       "Company_Jefferies & Company, Inc.                                -2.104e+04   1.17e+04     -1.792      0.074   -4.41e+04    2032.222\n",
       "Company_Joby Aviation                                             6606.5647   8700.800      0.759      0.448   -1.05e+04    2.37e+04\n",
       "Company_John Deere Intelligent Solutions                         -3.052e+04   2.21e+04     -1.379      0.169    -7.4e+04     1.3e+04\n",
       "Company_Johnson & Johnson Family of Companies                    -2.139e+04   2.57e+04     -0.831      0.406    -7.2e+04    2.92e+04\n",
       "Company_Keewi                                                    -8.835e+04   3.03e+04     -2.917      0.004   -1.48e+05   -2.88e+04\n",
       "Company_KelaHealth                                               -1.036e+04   1.19e+04     -0.868      0.386   -3.38e+04    1.31e+04\n",
       "Company_Kelvin Inc                                               -4.041e+04    2.9e+04     -1.395      0.164   -9.73e+04    1.65e+04\n",
       "Company_Kernel                                                   -3.644e+04   1.98e+04     -1.836      0.067   -7.54e+04    2555.828\n",
       "Company_Kett Engineering                                          -5.02e+04   2.92e+04     -1.719      0.086   -1.08e+05    7178.496\n",
       "Company_Khan Academy                                             -2.996e+04   2.32e+04     -1.291      0.197   -7.56e+04    1.56e+04\n",
       "Company_Kharon                                                   -1.548e+04   2.56e+04     -0.605      0.545   -6.57e+04    3.48e+04\n",
       "Company_Kite Pharma                                               3.411e+04   2.27e+04      1.503      0.134   -1.05e+04    7.87e+04\n",
       "Company_Kodiak Robotics                                          -1238.1573   3.48e+04     -0.036      0.972   -6.96e+04    6.72e+04\n",
       "Company_Kyte                                                     -6.145e+04   2.18e+04     -2.814      0.005   -1.04e+05   -1.85e+04\n",
       "Company_Labcorp                                                  -3.703e+04   2.89e+04     -1.283      0.200   -9.37e+04    1.97e+04\n",
       "Company_Lark Health                                              -6.542e+04   2.32e+04     -2.825      0.005   -1.11e+05   -1.99e+04\n",
       "Company_Lawrence Berkeley National Laboratory                    -8232.9055    1.1e+04     -0.746      0.456   -2.99e+04    1.34e+04\n",
       "Company_Legion                                                   -1.421e+04   2.63e+04     -0.540      0.589   -6.59e+04    3.75e+04\n",
       "Company_Leidos                                                    2.045e+04   1.47e+04      1.392      0.165   -8416.965    4.93e+04\n",
       "Company_LendingClub                                              -3.716e+04   2.31e+04     -1.609      0.108   -8.26e+04    8225.595\n",
       "Company_LendingPoint LLC                                          -7.93e+04   3.06e+04     -2.594      0.010   -1.39e+05   -1.92e+04\n",
       "Company_Levi Strauss & Co.                                       -5.194e+04    2.2e+04     -2.362      0.019   -9.51e+04   -8736.256\n",
       "Company_Liftoff+Vungle                                           -6216.7374    1.3e+04     -0.479      0.632   -3.17e+04    1.93e+04\n",
       "Company_Lily AI                                                   -4.56e+04   2.29e+04     -1.987      0.048   -9.07e+04    -502.902\n",
       "Company_Linqia                                                   -5.966e+04   2.55e+04     -2.344      0.019    -1.1e+05   -9642.088\n",
       "Company_LivePerson                                               -1.031e+05   2.32e+04     -4.452      0.000   -1.49e+05   -5.76e+04\n",
       "Company_LiveRamp                                                 -2.286e+04   1.15e+04     -1.992      0.047   -4.54e+04    -312.574\n",
       "Company_Loon                                                     -2.964e+04   2.22e+04     -1.338      0.182   -7.32e+04    1.39e+04\n",
       "Company_Lucid Motors                                              1.433e+04   9490.403      1.510      0.132   -4319.788     3.3e+04\n",
       "Company_Lumiata Inc.                                             -1.273e+04   1.54e+04     -0.828      0.408   -4.29e+04    1.75e+04\n",
       "Company_Lynx Analytics                                           -5.688e+04   2.41e+04     -2.361      0.019   -1.04e+05   -9536.811\n",
       "Company_MCG Health                                               -6.264e+04   2.24e+04     -2.797      0.005   -1.07e+05   -1.86e+04\n",
       "Company_MOLOCO                                                    5.123e+04   1.36e+04      3.765      0.000    2.45e+04     7.8e+04\n",
       "Company_Manifest Medex                                           -2.563e+04   8542.461     -3.000      0.003   -4.24e+04   -8843.382\n",
       "Company_MariaDB Corporation Ab                                   -1025.1554   2.87e+04     -0.036      0.972   -5.75e+04    5.54e+04\n",
       "Company_MasterCard                                               -4.969e+04   2.62e+04     -1.899      0.058   -1.01e+05    1717.010\n",
       "Company_MasterClass                                              -4.784e+04   2.36e+04     -2.030      0.043   -9.42e+04   -1525.402\n",
       "Company_Matroid                                                   6401.6773   3.39e+04      0.189      0.850   -6.03e+04    7.31e+04\n",
       "Company_MediaAlpha                                                -1.36e+04   7359.387     -1.847      0.065   -2.81e+04     864.448\n",
       "Company_Medtronic                                                -5619.5032   4727.756     -1.189      0.235   -1.49e+04    3670.151\n",
       "Company_Mercedes-Benz Research & Development North America, Inc. -2.605e+04   1.19e+04     -2.185      0.029   -4.95e+04   -2628.964\n",
       "Company_Meredith Corporation                                     -1.065e+04   2.66e+04     -0.401      0.689   -6.28e+04    4.15e+04\n",
       "Company_Microsoft                                                -1.537e+04   2.06e+04     -0.746      0.456   -5.59e+04    2.51e+04\n",
       "Company_Mirati Therapeutics Inc                                   5068.1305   7459.262      0.679      0.497   -9588.711    1.97e+04\n",
       "Company_Mission Analytics Group, Inc.                            -3.643e+04   1.49e+04     -2.437      0.015   -6.58e+04   -7057.174\n",
       "Company_Mission Support and Test Services, LLC                   -1.185e+04   8604.348     -1.377      0.169   -2.88e+04    5054.629\n",
       "Company_MobilityWare                                             -6841.3522   1.34e+04     -0.512      0.609   -3.31e+04    1.94e+04\n",
       "Company_Momentive                                                -2.548e+04   1.38e+04     -1.842      0.066   -5.27e+04    1702.707\n",
       "Company_Motional                                                 -8326.7221   1.22e+04     -0.683      0.495   -3.23e+04    1.56e+04\n",
       "Company_Moveworks                                                -1.494e+04   2.26e+04     -0.662      0.508   -5.93e+04    2.94e+04\n",
       "Company_Movoto                                                   -3.487e+04   1.05e+04     -3.327      0.001   -5.55e+04   -1.43e+04\n",
       "Company_Mulligan Funding                                          2.709e+04   1.43e+04      1.893      0.059   -1034.252    5.52e+04\n",
       "Company_Mynurse.ai                                                9059.3418   1.14e+04      0.793      0.428   -1.34e+04    3.15e+04\n",
       "Company_NBCUniversal                                             -1.535e+04   5449.627     -2.818      0.005   -2.61e+04   -4646.490\n",
       "Company_NEXT Trucking                                            -4.716e+04   2.95e+04     -1.598      0.111   -1.05e+05    1.08e+04\n",
       "Company_NVIDIA                                                    -4.59e+04   2.25e+04     -2.040      0.042   -9.01e+04   -1692.186\n",
       "Company_Narvar                                                   -6591.7910   1.52e+04     -0.435      0.664   -3.64e+04    2.32e+04\n",
       "Company_National General Insurance                                3.552e+04   1.79e+04      1.987      0.048     390.345    7.06e+04\n",
       "Company_Nauto                                                    -2.277e+04   2.34e+04     -0.974      0.331   -6.87e+04    2.32e+04\n",
       "Company_Neomorph, Inc                                            -2.052e+04   2.09e+04     -0.982      0.327   -6.16e+04    2.05e+04\n",
       "Company_Netflix                                                  -2.951e+04   2.25e+04     -1.310      0.191   -7.38e+04    1.47e+04\n",
       "Company_Next Insurance                                            6.749e+04   4.18e+04      1.615      0.107   -1.46e+04     1.5e+05\n",
       "Company_NextRoll                                                 -1.921e+04   1.31e+04     -1.464      0.144    -4.5e+04    6573.110\n",
       "Company_Nextdoor                                                 -1.288e+04   2.49e+04     -0.517      0.605   -6.18e+04     3.6e+04\n",
       "Company_Niantic                                                  -2.109e+04   2.38e+04     -0.886      0.376   -6.79e+04    2.57e+04\n",
       "Company_Nordstrom Inc                                             -3.07e+04   2.16e+04     -1.422      0.156   -7.31e+04    1.17e+04\n",
       "Company_Northrop Grumman                                          2023.5615   2.68e+04      0.076      0.940   -5.06e+04    5.47e+04\n",
       "Company_Novo Technologies Inc                                     4.949e+04   1.54e+04      3.221      0.001    1.93e+04    7.97e+04\n",
       "Company_Numerade                                                 -3.522e+04   2.46e+04     -1.433      0.152   -8.35e+04    1.31e+04\n",
       "Company_Numerdox                                                 -5.113e+04   3.13e+04     -1.635      0.103   -1.13e+05    1.03e+04\n",
       "Company_Nuro                                                     -2.765e+04   2.16e+04     -1.283      0.200      -7e+04    1.47e+04\n",
       "Company_OTTR Chronic Care Solutions                               6212.2684   9219.559      0.674      0.501   -1.19e+04    2.43e+04\n",
       "Company_Oculus Search Partners LLC                               -6.948e+04   2.52e+04     -2.761      0.006   -1.19e+05      -2e+04\n",
       "Company_One Medical                                              -3.935e+04   1.12e+04     -3.522      0.000   -6.13e+04   -1.74e+04\n",
       "Company_Oneida ESC Group                                         -2.018e+04   9482.579     -2.128      0.034   -3.88e+04   -1551.097\n",
       "Company_Onto Innovation                                          -1.837e+04   1.22e+04     -1.510      0.132   -4.23e+04    5538.608\n",
       "Company_Opendoor                                                  1.213e+04   9216.813      1.316      0.189   -5981.528    3.02e+04\n",
       "Company_OpsRamp, Inc.                                            -1.898e+04   2.55e+04     -0.743      0.458   -6.92e+04    3.12e+04\n",
       "Company_Oracle                                                   -6.696e+04   2.82e+04     -2.374      0.018   -1.22e+05   -1.15e+04\n",
       "Company_Orbital Sidekick                                           -61.6976    1.8e+04     -0.003      0.997   -3.55e+04    3.54e+04\n",
       "Company_Osair Technologies                                       -8.607e+04   2.33e+04     -3.696      0.000   -1.32e+05   -4.03e+04\n",
       "Company_Osmo                                                      -4.89e+04   2.54e+04     -1.928      0.054   -9.87e+04     924.874\n",
       "Company_Otter.ai                                                 -2.345e+04   2.43e+04     -0.964      0.336   -7.13e+04    2.44e+04\n",
       "Company_Oura                                                     -4.523e+04   2.43e+04     -1.858      0.064   -9.31e+04    2600.070\n",
       "Company_PG&E Corporation                                         -7.287e+04   2.58e+04     -2.830      0.005   -1.23e+05   -2.23e+04\n",
       "Company_Palo Alto Networks                                       -1.189e+05   3.17e+04     -3.752      0.000   -1.81e+05   -5.66e+04\n",
       "Company_Parallel Bio                                              2.453e+04   3.39e+04      0.724      0.469   -4.21e+04    9.11e+04\n",
       "Company_PayPal                                                   -6.231e+04   2.33e+04     -2.672      0.008   -1.08e+05   -1.65e+04\n",
       "Company_Penfield Search Partners                                 -3.331e+04   1.26e+04     -2.649      0.008    -5.8e+04   -8603.100\n",
       "Company_PennyMac                                                  9493.0284   1.07e+04      0.884      0.377   -1.16e+04    3.06e+04\n",
       "Company_Philo                                                     8231.2795   8453.893      0.974      0.331   -8379.932    2.48e+04\n",
       "Company_Philo Inc.                                               -1768.7205   6923.739     -0.255      0.798   -1.54e+04    1.18e+04\n",
       "Company_PicnicHealth                                             -3.197e+04   2.39e+04     -1.338      0.182   -7.89e+04     1.5e+04\n",
       "Company_Pinnacle Group                                           -9.464e+04   2.88e+04     -3.289      0.001   -1.51e+05   -3.81e+04\n",
       "Company_Pinterest                                                -5.181e+04   2.16e+04     -2.396      0.017   -9.43e+04   -9316.903\n",
       "Company_Plaid                                                    -1.288e+04   2.37e+04     -0.545      0.586   -5.94e+04    3.36e+04\n",
       "Company_Platform Science                                         -1.787e+04   2.49e+04     -0.718      0.473   -6.68e+04    3.11e+04\n",
       "Company_Plato Systems                                            -9071.9648   1.54e+04     -0.591      0.555   -3.92e+04    2.11e+04\n",
       "Company_PlayStation Global                                       -5.216e+04   2.57e+04     -2.027      0.043   -1.03e+05   -1585.425\n",
       "Company_Plume                                                     -2.78e+04   2.26e+04     -1.231      0.219   -7.21e+04    1.66e+04\n",
       "Company_Plus                                                     -4278.3575   1.14e+04     -0.374      0.709   -2.68e+04    1.82e+04\n",
       "Company_Plus Power                                                8286.2963   1.43e+04      0.577      0.564   -1.99e+04    3.65e+04\n",
       "Company_PocketPills                                              -1.719e+04   2.56e+04     -0.672      0.502   -6.74e+04     3.3e+04\n",
       "Company_Point Digital Finance                                    -4.039e+04   2.47e+04     -1.637      0.102   -8.89e+04    8079.787\n",
       "Company_Pollen                                                   -2.072e+04   5861.043     -3.535      0.000   -3.22e+04   -9200.762\n",
       "Company_Postclick                                                -4.451e+04   1.85e+04     -2.402      0.017   -8.09e+04   -8099.814\n",
       "Company_Prealize Health                                          -6.796e+04    2.6e+04     -2.616      0.009   -1.19e+05   -1.69e+04\n",
       "Company_Procore Technologies                                     -2.514e+04   9405.200     -2.673      0.008   -4.36e+04   -6657.564\n",
       "Company_Prosper                                                  -7.831e+04   2.62e+04     -2.985      0.003    -1.3e+05   -2.68e+04\n",
       "Company_Prove                                                    -4.807e+04   1.42e+04     -3.378      0.001    -7.6e+04   -2.01e+04\n",
       "Company_PwC                                                      -3.473e+04   2.58e+04     -1.344      0.180   -8.55e+04    1.61e+04\n",
       "Company_QuestBridge                                              -6.059e+04   2.07e+04     -2.922      0.004   -1.01e+05   -1.99e+04\n",
       "Company_RAPP                                                     -3.897e+04   2.12e+04     -1.835      0.067   -8.07e+04    2766.964\n",
       "Company_REDICA Systems                                           -1.094e+05   3.42e+04     -3.198      0.001   -1.77e+05   -4.22e+04\n",
       "Company_Recruiting From Scratch                                  -5606.4682   2.44e+04     -0.230      0.818   -5.36e+04    4.23e+04\n",
       "Company_Recurly                                                   8796.2050   2.35e+04      0.374      0.708   -3.74e+04     5.5e+04\n",
       "Company_Recurrency                                               -1.182e+05   3.07e+04     -3.850      0.000   -1.78e+05   -5.79e+04\n",
       "Company_Red Bull                                                 -2.524e+04   1.34e+04     -1.885      0.060   -5.16e+04    1067.069\n",
       "Company_Reddit                                                   -4.099e+04   2.19e+04     -1.870      0.062   -8.41e+04    2077.119\n",
       "Company_Resiliency LLC                                           -1.176e+05    4.2e+04     -2.803      0.005      -2e+05   -3.52e+04\n",
       "Company_Resonance AI                                             -4.221e+04   2.56e+04     -1.646      0.100   -9.26e+04    8167.952\n",
       "Company_Retool                                                   -6.408e+04   2.31e+04     -2.770      0.006    -1.1e+05   -1.86e+04\n",
       "Company_Revenue.io                                               -3.225e+04   1.47e+04     -2.190      0.029   -6.12e+04   -3310.909\n",
       "Company_Rhombus Power                                            -4.688e+04   1.47e+04     -3.190      0.002   -7.57e+04    -1.8e+04\n",
       "Company_Ripple                                                   -4.405e+04   2.08e+04     -2.118      0.035   -8.49e+04   -3180.490\n",
       "Company_Rippling                                                 -8.583e+04   2.42e+04     -3.553      0.000   -1.33e+05   -3.84e+04\n",
       "Company_Riva Health                                              -4.664e+04   3.05e+04     -1.530      0.127   -1.07e+05    1.33e+04\n",
       "Company_Rivian Automotive                                        -1.071e+04   1.29e+04     -0.827      0.408   -3.61e+04    1.47e+04\n",
       "Company_Robin Healthcare                                          -4.14e+04   2.68e+04     -1.544      0.123   -9.41e+04    1.13e+04\n",
       "Company_Robinhood                                                 -7.46e+04   2.45e+04     -3.049      0.002   -1.23e+05   -2.65e+04\n",
       "Company_Roche                                                    -2.721e+04   2.26e+04     -1.202      0.230   -7.17e+04    1.73e+04\n",
       "Company_Roku                                                     -6.431e+04   2.99e+04     -2.154      0.032   -1.23e+05   -5650.134\n",
       "Company_Roo                                                      -4.984e+04   2.89e+04     -1.726      0.085   -1.07e+05    6899.318\n",
       "Company_Route                                                    -3.731e+04   2.96e+04     -1.262      0.207   -9.54e+04    2.08e+04\n",
       "Company_Rubicon                                                   3.087e+04   1.75e+04      1.764      0.078   -3524.957    6.53e+04\n",
       "Company_SAMBA TV                                                  3.895e+04    3.3e+04      1.181      0.238   -2.59e+04    1.04e+05\n",
       "Company_SCAN Health Plan                                         -1.729e+04   1.34e+04     -1.292      0.197   -4.36e+04    8998.770\n",
       "Company_SLAC National Accelerator Laboratory                      -3.16e+04   2.63e+04     -1.200      0.231   -8.34e+04    2.02e+04\n",
       "Company_SRI International                                        -2.373e+04   2.62e+04     -0.905      0.366   -7.53e+04    2.78e+04\n",
       "Company_STAR Labs                                                -3.103e+04   2.48e+04     -1.251      0.212   -7.98e+04    1.77e+04\n",
       "Company_Salesforce                                               -8.224e+04   2.15e+04     -3.826      0.000   -1.24e+05      -4e+04\n",
       "Company_ScaleMonk                                                -1.882e+04   2.55e+04     -0.737      0.462    -6.9e+04    3.14e+04\n",
       "Company_Scaleapi                                                  1483.3723   1.17e+04      0.127      0.899   -2.15e+04    2.45e+04\n",
       "Company_Seer                                                      2.837e+04   1.51e+04      1.876      0.061   -1346.523    5.81e+04\n",
       "Company_Segula Technologies                                      -2.986e+04   1.77e+04     -1.684      0.093   -6.47e+04    4980.143\n",
       "Company_Sense Talent Labs, Inc.                                  -5.761e+04   2.47e+04     -2.337      0.020   -1.06e+05   -9164.305\n",
       "Company_ServiceNow                                               -3.051e+04   2.47e+04     -1.237      0.217    -7.9e+04     1.8e+04\n",
       "Company_SetSail                                                   2052.5684   1.63e+04      0.126      0.900   -2.99e+04     3.4e+04\n",
       "Company_Shift                                                    -5.402e+04   3.03e+04     -1.783      0.075   -1.14e+05    5513.570\n",
       "Company_Shipt                                                     -5.35e+04   2.07e+04     -2.587      0.010   -9.41e+04   -1.29e+04\n",
       "Company_Shopify                                                  -1.013e+05   2.86e+04     -3.540      0.000   -1.58e+05   -4.51e+04\n",
       "Company_Shutterfly                                               -5.268e+04   1.39e+04     -3.800      0.000   -7.99e+04   -2.54e+04\n",
       "Company_Sift                                                     -5.448e+04   2.56e+04     -2.124      0.034   -1.05e+05   -4088.516\n",
       "Company_Signifyd                                                 -5.696e+04   2.66e+04     -2.143      0.033   -1.09e+05   -4733.713\n",
       "Company_SimplePractice                                            2.503e+04   1.88e+04      1.329      0.185    -1.2e+04    6.21e+04\n",
       "Company_Singularity 6                                             5.686e+04   2.25e+04      2.524      0.012    1.26e+04    1.01e+05\n",
       "Company_Skai                                                     -6.732e+04   2.47e+04     -2.720      0.007   -1.16e+05   -1.87e+04\n",
       "Company_Slack                                                     -8.37e+04    2.2e+04     -3.800      0.000   -1.27e+05   -4.04e+04\n",
       "Company_Slate Technologies                                       -6.048e+04   2.55e+04     -2.367      0.018   -1.11e+05   -1.03e+04\n",
       "Company_Sleep Number                                              1664.7955   9792.260      0.170      0.865   -1.76e+04    2.09e+04\n",
       "Company_Snapchat                                                 -4.719e+04   2.24e+04     -2.103      0.036   -9.13e+04   -3095.764\n",
       "Company_Snowflake                                                -5.596e+04   2.94e+04     -1.906      0.057   -1.14e+05    1734.344\n",
       "Company_Socure                                                   -8.927e+04   2.39e+04     -3.727      0.000   -1.36e+05   -4.22e+04\n",
       "Company_Sofar Ocean                                              -5.968e+04   2.41e+04     -2.471      0.014   -1.07e+05   -1.22e+04\n",
       "Company_Sojern                                                   -1.094e+05   1.78e+04     -6.129      0.000   -1.44e+05   -7.43e+04\n",
       "Company_SpanIdea Systems                                         -1.301e+04   6359.840     -2.046      0.041   -2.55e+04    -512.834\n",
       "Company_Spanidea Systemms                                        -9.692e+04   2.86e+04     -3.384      0.001   -1.53e+05   -4.06e+04\n",
       "Company_Specific Diagnostics                                      1.426e+04   1.21e+04      1.180      0.238   -9475.503     3.8e+04\n",
       "Company_Spin                                                      -5.99e+04   2.46e+04     -2.436      0.015   -1.08e+05   -1.16e+04\n",
       "Company_Spotline Inc                                              4.296e+04   8953.331      4.798      0.000    2.54e+04    6.06e+04\n",
       "Company_Spring Discovery                                           1.22e+04    1.4e+04      0.870      0.385   -1.53e+04    3.97e+04\n",
       "Company_Standard Cognition                                       -3.694e+04   2.87e+04     -1.288      0.199   -9.33e+04    1.94e+04\n",
       "Company_Stanford Health Care                                     -5.511e+04   1.71e+04     -3.216      0.001   -8.88e+04   -2.14e+04\n",
       "Company_Stanford University                                       1.089e+04   9222.661      1.180      0.238   -7235.745     2.9e+04\n",
       "Company_Steady Platform                                          -1.641e+04   2.43e+04     -0.674      0.501   -6.43e+04    3.14e+04\n",
       "Company_Step                                                     -6544.7235   3.29e+04     -0.199      0.842   -7.12e+04    5.81e+04\n",
       "Company_Step Mobile                                               2.242e+04   3.36e+04      0.668      0.504   -4.35e+04    8.84e+04\n",
       "Company_StreetLight Data                                         -4.296e+04   3.91e+04     -1.098      0.273    -1.2e+05    3.39e+04\n",
       "Company_Suki.ai                                                   4.632e+04   1.79e+04      2.587      0.010    1.11e+04    8.15e+04\n",
       "Company_Surya Systems                                            -2.318e+04   2.55e+04     -0.908      0.364   -7.33e+04     2.7e+04\n",
       "Company_Susquehanna International Group                           1.145e+04   1.62e+04      0.707      0.480   -2.04e+04    4.33e+04\n",
       "Company_Sutter Health                                             7863.8910   1.06e+04      0.742      0.459    -1.3e+04    2.87e+04\n",
       "Company_SynTouch Inc.                                            -1.385e+04   7855.706     -1.763      0.078   -2.93e+04    1583.372\n",
       "Company_Synergy Solutions                                        -5.139e+04   2.72e+04     -1.891      0.059   -1.05e+05    2018.677\n",
       "Company_Synopsys                                                 -3.361e+04    2.5e+04     -1.344      0.180   -8.27e+04    1.55e+04\n",
       "Company_TMC Software                                              6110.0938   1.33e+04      0.458      0.647   -2.01e+04    3.23e+04\n",
       "Company_Taboola                                                  -4.901e+04   2.56e+04     -1.912      0.057   -9.94e+04    1364.830\n",
       "Company_Talent Search PRO                                        -7.926e+04   4.01e+04     -1.975      0.049   -1.58e+05    -387.684\n",
       "Company_Talkdesk                                                 -2.573e+04    1.4e+04     -1.838      0.067   -5.32e+04    1771.521\n",
       "Company_TalkingPoints                                            -5.848e+04    2.7e+04     -2.168      0.031   -1.11e+05   -5482.092\n",
       "Company_Tapcart                                                  -3.465e+04   2.62e+04     -1.325      0.186    -8.6e+04    1.67e+04\n",
       "Company_Target                                                    -3.56e+04   1.65e+04     -2.158      0.031    -6.8e+04   -3190.140\n",
       "Company_TargetCW                                                 -1.228e+05   1.57e+04     -7.827      0.000   -1.54e+05    -9.2e+04\n",
       "Company_Teknatio                                                 -1.766e+05   3.35e+04     -5.278      0.000   -2.42e+05   -1.11e+05\n",
       "Company_Tempus                                                   -2.021e+04    1.9e+04     -1.063      0.288   -5.76e+04    1.71e+04\n",
       "Company_TeraWatt Infrastructure                                  -4.817e+04   1.31e+04     -3.675      0.000   -7.39e+04   -2.24e+04\n",
       "Company_Terrafuse AI                                             -2.296e+04   3.46e+04     -0.664      0.507   -9.09e+04    4.49e+04\n",
       "Company_Terray Therapeutics                                       6.042e+04   2.19e+04      2.763      0.006    1.74e+04    1.03e+05\n",
       "Company_Tesla                                                     2639.7967   8083.052      0.327      0.744   -1.32e+04    1.85e+04\n",
       "Company_Tesseract                                                -4330.4984   1.31e+04     -0.331      0.741   -3.01e+04    2.14e+04\n",
       "Company_The Aerospace Corporation                                -7.086e+04   3.06e+04     -2.318      0.021   -1.31e+05   -1.08e+04\n",
       "Company_The Clorox Company                                       -1740.1729   3.02e+04     -0.058      0.954   -6.12e+04    5.77e+04\n",
       "Company_The Patrick J. McGovern Foundation                        3.436e+04    1.2e+04      2.865      0.004    1.08e+04    5.79e+04\n",
       "Company_The Walt Disney Studios                                   1.462e+04   3.06e+04      0.478      0.633   -4.55e+04    7.48e+04\n",
       "Company_The Yes                                                   -6.17e+04    2.2e+04     -2.800      0.005   -1.05e+05   -1.84e+04\n",
       "Company_Thermo Fisher Scientific                                   1.47e+04   1.37e+04      1.071      0.285   -1.23e+04    4.17e+04\n",
       "Company_Thorn                                                    -6.536e+04   2.39e+04     -2.729      0.007   -1.12e+05   -1.83e+04\n",
       "Company_Thumbtack                                                -2.562e+04   1.29e+04     -1.981      0.048    -5.1e+04    -201.914\n",
       "Company_TikTok                                                     -3.3e+04   1.97e+04     -1.672      0.095   -7.18e+04    5783.390\n",
       "Company_Tiktok Pte. Ltd.                                         -3.874e+04   2.23e+04     -1.739      0.083   -8.25e+04    5040.898\n",
       "Company_Tinder                                                   -2.199e+04   1.22e+04     -1.802      0.072    -4.6e+04    1990.026\n",
       "Company_Together Labs                                            -3.264e+04   1.85e+04     -1.760      0.079   -6.91e+04    3791.732\n",
       "Company_Tonal                                                     -7.89e+04   2.27e+04     -3.471      0.001   -1.24e+05   -3.42e+04\n",
       "Company_Totus Medicines                                          -7.909e+04   2.49e+04     -3.178      0.002   -1.28e+05   -3.02e+04\n",
       "Company_Toyota Research Institute                                -5165.8601   1.11e+04     -0.467      0.641   -2.69e+04    1.66e+04\n",
       "Company_Transcarent                                              -1.674e+04   2.61e+04     -0.640      0.522   -6.81e+04    3.46e+04\n",
       "Company_Transform Data                                           -2.221e+04   2.56e+04     -0.866      0.387   -7.26e+04    2.82e+04\n",
       "Company_Trusaic                                                  -1.413e+04   2.21e+04     -0.640      0.523   -5.75e+04    2.92e+04\n",
       "Company_TuSimple                                                 -1.143e+04    2.5e+04     -0.457      0.648   -6.06e+04    3.77e+04\n",
       "Company_TuSimple, Inc.                                            -4.79e+04   2.14e+04     -2.243      0.025   -8.99e+04   -5933.890\n",
       "Company_Tubi                                                     -7.192e+04   2.53e+04     -2.841      0.005   -1.22e+05   -2.22e+04\n",
       "Company_Turntide Technologies                                    -7.555e+04   2.85e+04     -2.651      0.008   -1.32e+05   -1.95e+04\n",
       "Company_Twin Health                                              -8919.0819   1.19e+04     -0.748      0.455   -3.24e+04    1.45e+04\n",
       "Company_Twitch                                                   -3.035e+04    2.1e+04     -1.445      0.149   -7.16e+04    1.09e+04\n",
       "Company_Twitch Interactive, Inc.                                 -4.294e+04   2.12e+04     -2.022      0.044   -8.47e+04   -1207.266\n",
       "Company_U.S. Bank                                                 2.254e+04   1.72e+04      1.307      0.192   -1.13e+04    5.64e+04\n",
       "Company_UC San Diego                                              -445.8536   1.57e+04     -0.028      0.977   -3.13e+04    3.04e+04\n",
       "Company_UCLA                                                      -3.08e+04   2.52e+04     -1.222      0.222   -8.03e+04    1.87e+04\n",
       "Company_UCLA Health                                               -1.26e+04   2.07e+04     -0.610      0.542   -5.32e+04     2.8e+04\n",
       "Company_UKG (Ultimate Kronos Group)                              -2.361e+04   2.78e+04     -0.849      0.397   -7.83e+04    3.11e+04\n",
       "Company_Uber                                                     -4.157e+04   2.12e+04     -1.957      0.051   -8.33e+04     173.951\n",
       "Company_Ubisoft                                                  -6.387e+04   1.76e+04     -3.636      0.000   -9.84e+04   -2.94e+04\n",
       "Company_UnitedHealth Group                                         3.97e+04   9764.716      4.065      0.000    2.05e+04    5.89e+04\n",
       "Company_Universal Music Group                                     4.146e+04   3.21e+04      1.291      0.197   -2.16e+04    1.05e+05\n",
       "Company_Universal Orlando                                        -1.535e+04   5449.627     -2.818      0.005   -2.61e+04   -4646.490\n",
       "Company_University of California San Francisco                   -2.076e+04   1.04e+04     -1.991      0.047   -4.13e+04    -270.476\n",
       "Company_Upgrade                                                  -3.021e+04   1.17e+04     -2.574      0.010   -5.33e+04   -7152.119\n",
       "Company_Ursus                                                    -2.527e+04   2.16e+04     -1.171      0.242   -6.77e+04    1.71e+04\n",
       "Company_Varo Money                                               -5.386e+04   2.67e+04     -2.014      0.045   -1.06e+05   -1315.877\n",
       "Company_Velodyne                                                 -5286.5201   1.22e+04     -0.433      0.665   -2.92e+04    1.87e+04\n",
       "Company_Verana Health                                             4135.3636   2.69e+04      0.154      0.878   -4.87e+04     5.7e+04\n",
       "Company_Verizon                                                   1.361e+04   1.15e+04      1.184      0.237   -8988.941    3.62e+04\n",
       "Company_Vertex Pharmaceuticals                                    9.964e+04   4.56e+04      2.187      0.029    1.01e+04    1.89e+05\n",
       "Company_ViaSat                                                   -1.829e+04   1.33e+04     -1.379      0.169   -4.44e+04    7776.395\n",
       "Company_VideoAmp Careers Website                                 -2.926e+04   1.19e+04     -2.460      0.014   -5.26e+04   -5884.259\n",
       "Company_View, Inc.                                               -4318.3913   2.05e+04     -0.211      0.833   -4.45e+04    3.59e+04\n",
       "Company_Virtualitics                                             -1.092e+05   3.41e+04     -3.199      0.001   -1.76e+05   -4.21e+04\n",
       "Company_Visa                                                     -2059.6868   1.18e+04     -0.174      0.862   -2.53e+04    2.12e+04\n",
       "Company_Vitria Technology                                        -5.979e+04   2.76e+04     -2.167      0.031   -1.14e+05   -5574.823\n",
       "Company_Vivun                                                    -7.355e+04   1.69e+04     -4.355      0.000   -1.07e+05   -4.04e+04\n",
       "Company_Volt Workforce Solutions                                 -5.506e+04   1.39e+04     -3.963      0.000   -8.24e+04   -2.78e+04\n",
       "Company_Warman O'Brien                                           -1.872e+05   3.16e+04     -5.928      0.000   -2.49e+05   -1.25e+05\n",
       "Company_WarnerMedia                                              -2.743e+04   2.52e+04     -1.089      0.277   -7.69e+04    2.21e+04\n",
       "Company_Wayfair                                                  -4.519e+04   2.13e+04     -2.123      0.034    -8.7e+04   -3358.198\n",
       "Company_Weee! Inc                                                 9483.3192   1.22e+04      0.779      0.437   -1.45e+04    3.34e+04\n",
       "Company_Wells Fargo                                               6744.6614   9960.273      0.677      0.499   -1.28e+04    2.63e+04\n",
       "Company_Whip Media                                                1.928e+04   2.64e+04      0.732      0.465   -3.25e+04    7.11e+04\n",
       "Company_Williams Sonoma                                           -3.28e+04   2.27e+04     -1.447      0.149   -7.73e+04    1.17e+04\n",
       "Company_Wish                                                     -4.282e+04   2.32e+04     -1.842      0.066   -8.85e+04    2854.996\n",
       "Company_Woebot Health                                            -4.927e+04   2.35e+04     -2.100      0.036   -9.54e+04   -3178.523\n",
       "Company_Woodruff Sawyer                                          -3.144e+04   4.31e+04     -0.730      0.466   -1.16e+05    5.32e+04\n",
       "Company_Workato                                                  -2.951e+04   2.74e+04     -1.075      0.283   -8.34e+04    2.44e+04\n",
       "Company_Woven Planet Level 5                                     -4.124e+04   2.46e+04     -1.679      0.094   -8.95e+04    7031.465\n",
       "Company_XL Data Corp                                              4051.3927   1.05e+04      0.387      0.699   -1.65e+04    2.46e+04\n",
       "Company_XPeng Motors                                             -2.515e+04   2.01e+04     -1.253      0.211   -6.46e+04    1.43e+04\n",
       "Company_Xerox                                                    -1.573e+04   1.24e+04     -1.273      0.204      -4e+04    8541.245\n",
       "Company_ZL Technologies                                           9501.8866   1.66e+04      0.572      0.568   -2.32e+04    4.22e+04\n",
       "Company_Zenith Electronics, LLC                                  -4686.3133   1.56e+04     -0.300      0.764   -3.54e+04     2.6e+04\n",
       "Company_Zest AI                                                   9468.3453   2.97e+04      0.319      0.750   -4.89e+04    6.79e+04\n",
       "Company_ZineOne                                                  -4959.1168   1.27e+04     -0.390      0.697   -2.99e+04       2e+04\n",
       "Company_Zippin                                                    9928.5567   1.96e+04      0.506      0.613   -2.86e+04    4.85e+04\n",
       "Company_Zscaler                                                  -2.988e+04   1.29e+04     -2.317      0.021   -5.52e+04   -4545.624\n",
       "Company_Zuora                                                    -1.986e+04   2.35e+04     -0.844      0.399   -6.61e+04    2.64e+04\n",
       "Company_aiXplain                                                  4799.7193    2.7e+04      0.178      0.859   -4.82e+04    5.78e+04\n",
       "Company_eHealth                                                   -5.49e+04   2.51e+04     -2.190      0.029   -1.04e+05   -5642.368\n",
       "Company_f5                                                       -3.876e+04   2.29e+04     -1.695      0.091   -8.37e+04    6172.897\n",
       "Company_firstlight.ai                                             2.997e+04   2.86e+04      1.047      0.296   -2.63e+04    8.62e+04\n",
       "Company_hims & hers                                              -4.401e+04   1.59e+04     -2.766      0.006   -7.53e+04   -1.27e+04\n",
       "Company_iMerit                                                   -1.398e+05   2.42e+04     -5.768      0.000   -1.87e+05   -9.22e+04\n",
       "Company_iRhythm Technologies                                     -8.108e+04   2.63e+04     -3.084      0.002   -1.33e+05   -2.94e+04\n",
       "Company_largeton,inc                                             -2.531e+04   1.38e+04     -1.835      0.067   -5.24e+04    1786.625\n",
       "Company_opentext                                                 -2.187e+04   3.14e+04     -0.696      0.487   -8.36e+04    3.99e+04\n",
       "Company_sharethrough                                              2705.4785   1.47e+04      0.184      0.854   -2.61e+04    3.15e+04\n",
       "Location_Aliso Viejo, CA                                          3.178e+04   2.41e+04      1.317      0.188   -1.56e+04    7.92e+04\n",
       "Location_Berkeley, CA                                             1.683e+04   8574.855      1.962      0.050     -23.561    3.37e+04\n",
       "Location_Brisbane, CA                                             2424.5368   1.06e+04      0.228      0.820   -1.85e+04    2.33e+04\n",
       "Location_Burbank, CA                                             -1.377e+04    1.9e+04     -0.726      0.468    -5.1e+04    2.35e+04\n",
       "Location_Burlingame, CA                                           8.452e+04   1.91e+04      4.428      0.000     4.7e+04    1.22e+05\n",
       "Location_California City, CA                                      4051.3927   1.05e+04      0.387      0.699   -1.65e+04    2.46e+04\n",
       "Location_Carlsbad, CA                                            -3.387e+04   1.21e+04     -2.801      0.005   -5.76e+04   -1.01e+04\n",
       "Location_Carpinteria, CA                                         -2.587e+04   8668.328     -2.984      0.003   -4.29e+04   -8832.491\n",
       "Location_Carson, CA                                               1173.3650   8888.642      0.132      0.895   -1.63e+04    1.86e+04\n",
       "Location_Concord, CA                                              4.701e+04   1.44e+04      3.272      0.001    1.88e+04    7.52e+04\n",
       "Location_Costa Mesa, CA                                          -1.619e+04   7037.100     -2.301      0.022      -3e+04   -2362.505\n",
       "Location_Culver City, CA                                          8186.5391    1.5e+04      0.547      0.585   -2.12e+04    3.76e+04\n",
       "Location_Cupertino, CA                                            1429.0815   1.27e+04      0.113      0.910   -2.34e+04    2.63e+04\n",
       "Location_Davis, CA                                               -5959.4671   9510.032     -0.627      0.531   -2.46e+04    1.27e+04\n",
       "Location_Duarte, CA                                               2.664e+04   1.65e+04      1.618      0.106   -5710.174     5.9e+04\n",
       "Location_East Palo Alto, CA                                       4.859e+04   1.49e+04      3.258      0.001    1.93e+04    7.79e+04\n",
       "Location_El Segundo, CA                                           3.283e+04   1.62e+04      2.030      0.043    1053.136    6.46e+04\n",
       "Location_Emeryville, CA                                          -1.657e+04   8813.081     -1.880      0.061   -3.39e+04     747.705\n",
       "Location_Folsom, CA                                              -1.484e+04   1.07e+04     -1.392      0.165   -3.58e+04    6115.256\n",
       "Location_Foster City, CA                                         -1.215e+04   1.01e+04     -1.206      0.229    -3.2e+04    7652.234\n",
       "Location_Fountain Valley, CA                                     -2.644e+04   1.73e+04     -1.532      0.126   -6.03e+04    7470.138\n",
       "Location_Fremont, CA                                             -9605.3302   8848.122     -1.086      0.278    -2.7e+04    7780.508\n",
       "Location_Fresno, CA                                               9.021e+04   2.27e+04      3.980      0.000    4.57e+04    1.35e+05\n",
       "Location_Glendale, CA                                            -1.385e+04   7855.706     -1.763      0.078   -2.93e+04    1583.372\n",
       "Location_Hollywood, CA                                           -1.535e+04   5449.627     -2.818      0.005   -2.61e+04   -4646.490\n",
       "Location_Irvine, CA                                              -1.114e+04   9530.882     -1.168      0.243   -2.99e+04    7591.792\n",
       "Location_Irwindale, CA                                            1.377e+04   1.68e+04      0.819      0.413   -1.93e+04    4.68e+04\n",
       "Location_Laguna Niguel, CA                                        -2.18e+04   1.18e+04     -1.842      0.066   -4.51e+04    1459.446\n",
       "Location_Lake Forest, CA                                          3791.8554   1.63e+04      0.233      0.816   -2.82e+04    3.57e+04\n",
       "Location_Lodi, CA                                                 3.509e+04   1.83e+04      1.920      0.055    -825.233     7.1e+04\n",
       "Location_Long Beach, CA                                           3.021e+04   1.72e+04      1.760      0.079   -3512.466    6.39e+04\n",
       "Location_Los Altos, CA                                           -2.355e+04   1.12e+04     -2.112      0.035   -4.55e+04   -1637.087\n",
       "Location_Los Angeles, CA                                          1.011e+04   1.05e+04      0.965      0.335   -1.05e+04    3.07e+04\n",
       "Location_Los Gatos, CA                                            2.103e+04   1.57e+04      1.337      0.182   -9887.326     5.2e+04\n",
       "Location_Malibu, CA                                               7484.6881   8513.664      0.879      0.380   -9243.967    2.42e+04\n",
       "Location_Marina del Rey, CA                                        370.1971   9019.919      0.041      0.967   -1.74e+04    1.81e+04\n",
       "Location_Menlo Park, CA                                           5.201e+04   1.42e+04      3.669      0.000    2.42e+04    7.99e+04\n",
       "Location_Milpitas, CA                                            -1.815e+04   1.06e+04     -1.706      0.089   -3.91e+04    2753.067\n",
       "Location_Modesto, CA                                             -5466.7098   1.13e+04     -0.484      0.629   -2.77e+04    1.67e+04\n",
       "Location_Mountain View, CA                                         1.89e+04   9223.099      2.049      0.041     777.994     3.7e+04\n",
       "Location_Newark, CA                                              -3968.0461   9239.237     -0.429      0.668   -2.21e+04    1.42e+04\n",
       "Location_Northridge, CA                                          -5619.5032   4727.756     -1.189      0.235   -1.49e+04    3670.151\n",
       "Location_Oakland, CA                                             -4.927e+04   1.13e+04     -4.378      0.000   -7.14e+04   -2.72e+04\n",
       "Location_Ontario, CA                                             -2.836e+04    1.3e+04     -2.173      0.030    -5.4e+04   -2717.292\n",
       "Location_Palo Alto, CA                                            1.124e+04   1.12e+04      1.006      0.315   -1.07e+04    3.32e+04\n",
       "Location_Pasadena, CA                                             5.582e+04   2.34e+04      2.388      0.017    9885.413    1.02e+05\n",
       "Location_Pittsburg, CA                                           -2.147e+04   5056.241     -4.247      0.000   -3.14e+04   -1.15e+04\n",
       "Location_Pleasanton, CA                                           5093.6389   1.96e+04      0.260      0.795   -3.34e+04    4.36e+04\n",
       "Location_Rancho Cucamonga, CA                                    -4821.2528   1.19e+04     -0.405      0.686   -2.82e+04    1.86e+04\n",
       "Location_Redwood City, CA                                         6738.3197   6180.398      1.090      0.276   -5405.658    1.89e+04\n",
       "Location_Sacramento, CA                                          -9631.6834   2.19e+04     -0.439      0.661   -5.27e+04    3.35e+04\n",
       "Location_San Carlos, CA                                          -3.176e+04   1.12e+04     -2.845      0.005   -5.37e+04   -9822.520\n",
       "Location_San Clemente, CA                                        -3.688e+04   9331.674     -3.952      0.000   -5.52e+04   -1.85e+04\n",
       "Location_San Diego, CA                                           -2.204e+04   1.51e+04     -1.459      0.145   -5.17e+04    7634.751\n",
       "Location_San Francisco Bay Area, CA                              -3.604e+04   9583.441     -3.761      0.000   -5.49e+04   -1.72e+04\n",
       "Location_San Francisco, CA                                        3.021e+04   9143.241      3.304      0.001    1.22e+04    4.82e+04\n",
       "Location_San Jose, CA                                             1.022e+04   1.13e+04      0.900      0.368   -1.21e+04    3.25e+04\n",
       "Location_San Mateo, CA                                            1.963e+04   1.88e+04      1.044      0.297   -1.73e+04    5.66e+04\n",
       "Location_San Ramon, CA                                            5453.4585   9116.028      0.598      0.550   -1.25e+04    2.34e+04\n",
       "Location_Santa Ana, CA                                            -1.96e+04   7977.487     -2.457      0.014   -3.53e+04   -3928.491\n",
       "Location_Santa Barbara, CA                                       -1850.0570   1.57e+04     -0.118      0.906   -3.27e+04     2.9e+04\n",
       "Location_Santa Clara, CA                                          3039.4481    1.3e+04      0.234      0.815   -2.25e+04    2.85e+04\n",
       "Location_Santa Cruz, CA                                           6606.5647   8700.800      0.759      0.448   -1.05e+04    2.37e+04\n",
       "Location_Santa Monica, CA                                        -9650.9391   1.23e+04     -0.784      0.434   -3.39e+04    1.45e+04\n",
       "Location_Silicon Valley, CA                                       1.988e+04   1.43e+04      1.387      0.166   -8281.597     4.8e+04\n",
       "Location_South San Francisco, CA                                 -1.933e+04   1.15e+04     -1.675      0.095    -4.2e+04    3347.546\n",
       "Location_Stanford, CA                                             1.089e+04   9222.661      1.180      0.238   -7235.745     2.9e+04\n",
       "Location_Sunnyvale, CA                                            1.839e+04   9137.002      2.013      0.045     436.174    3.63e+04\n",
       "Location_Sylmar, CA                                              -2.145e+04   9909.512     -2.165      0.031   -4.09e+04   -1982.639\n",
       "Location_Thousand Oaks, CA                                        3.022e+04   1.25e+04      2.411      0.016    5589.395    5.49e+04\n",
       "Location_Union City, CA                                           9949.9272   5554.826      1.791      0.074    -964.852    2.09e+04\n",
       "Location_Universal City, CA                                      -1.535e+04   5449.627     -2.818      0.005   -2.61e+04   -4646.490\n",
       "Location_Valencia, CA                                            -2.533e+04   9225.329     -2.745      0.006   -4.35e+04   -7200.982\n",
       "Location_Venice, CA                                              -5752.1427   1.36e+04     -0.423      0.673   -3.25e+04     2.1e+04\n",
       "Location_Ventura, CA                                             -2.018e+04   9482.579     -2.128      0.034   -3.88e+04   -1551.097\n",
       "Location_Vista, CA                                                9875.4540   1.02e+04      0.970      0.332   -1.01e+04    2.99e+04\n",
       "Location_West Hollywood, CA                                      -4003.0790   1.17e+04     -0.343      0.732   -2.69e+04    1.89e+04\n",
       "Location_West Sacramento, CA                                     -4779.8995   1.38e+04     -0.347      0.728   -3.18e+04    2.23e+04\n",
       "Location_Westlake Village, CA                                    -2.957e+04   1.52e+04     -1.944      0.052   -5.95e+04     313.485\n",
       "Location_Woodland Hills, CA                                       3.021e+04   1.74e+04      1.734      0.084   -4026.642    6.44e+04\n",
       "Levels_Jr.                                                       -2.435e+04   2.27e+04     -1.071      0.285    -6.9e+04    2.03e+04\n",
       "Levels_Lead                                                      -8533.7567   2.32e+04     -0.367      0.714   -5.42e+04    3.71e+04\n",
       "Levels_Principal                                                 -2937.4538   2.32e+04     -0.127      0.899   -4.85e+04    4.26e+04\n",
       "Levels_Sr.                                                       -5654.1669   2.29e+04     -0.247      0.805   -5.06e+04    3.93e+04\n",
       "Levels_Staff                                                     -2.101e+04   2.31e+04     -0.910      0.363   -6.64e+04    2.43e+04\n",
       "Levels_Unknown                                                   -3.017e+04    2.3e+04     -1.314      0.189   -7.53e+04    1.49e+04\n",
       "==============================================================================\n",
       "Omnibus:                      230.753   Durbin-Watson:                   1.887\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             4342.294\n",
       "Skew:                          -0.204   Prob(JB):                         0.00\n",
       "Kurtosis:                      11.989   Cond. No.                     1.54e+17\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The smallest eigenvalue is 2.09e-31. This might indicate that there are\n",
       "strong multicollinearity problems or that the design matrix is singular.\n",
       "\"\"\""
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_sm = sm.add_constant(X_drop_first)\n",
    "model = sm.OLS(y.astype(float),X_sm.astype(int))\n",
    "results = model.fit()\n",
    "results.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bd8b00f",
   "metadata": {},
   "source": [
    "## Assessing the model\n",
    "\n",
    "The $R^{2}$ metric shows that 96% of the variation is explained by the model. However, since there are 986 predictors, a better metric is the $adj. R^{2}$ since $R^{2}$ increases with the number of predictors and $adj. R^{2}$ penalizes additional predictors. The $R^{2}$ metric is given by:\n",
    "\n",
    "$$R^{2} = \\frac{\\sum_{i}^{n}(\\hat{y}_{i}-\\bar{y})}{\\sum_{i}^{n}(y_{i}-\\bar{y})} = 1 - \\frac{RSS}{TSS}$$\n",
    "\n",
    "where $\\bar{y}$ is the mean of the response variable and $TSS = \\sum_i^{n}{(y_{i} - \\bar{y_{i}})^{2}}$ is the total sum of squares.\n",
    "\n",
    "The $adj. R^{2}$ metric is given by:\n",
    "\n",
    "$$adj. R^{2} = 1 - \\frac{(1-R^{2})(n-1)}{n-p-1}$$\n",
    "\n",
    "The $adj. R^{2}$ metric shows that 89.4% of the variation is explained by this model.\n",
    "\n",
    "Next, the model is assessed using the F-statistic and its corresponding p-value. The F-statistic is given by\n",
    "\n",
    "$$F = \\frac{(TSS-RSS)/p}{RSS/(n-p-1)}$$\n",
    "\n",
    "If the linear model assumptions are correct then the expectation value of the denomenator is equal to $\\sigma^2$ (the variance) and if the null hypothesis is true (that there is no relationship between any predictors and the response) then the expectation value of the numerator is also equal to $\\sigma^2$. Hence, the further away the F-statistic is from 1, the more likely the alternative hypothesis is true.\n",
    "\n",
    "F-statistic for this OLS model is 14.44 and the p-value is 1.63e-161. Choosing an $\\alpha$ of 0.05, the null hypothesis is rejected. This means the model explains some relationship between the predictors and salary such that the relationship is statistically significant."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce777117",
   "metadata": {},
   "source": [
    "## Bonferroni correction\n",
    "\n",
    "Due to the large number of predictors, a family-wise error rate (FWER) correction is used. The Bonferroni method is used due to it's simplicity and ease of use. It sets the threshold for rejecting each hypothesis test to $\\alpha/p$ where $\\alpha$ is 0.05 and $p$ is 986. Therefore, the probability of making a Type I error is $\\leq 0.05/986 = 5.07\\times 10^{-5}$.\n",
    "\n",
    "With 986 predictors, the number of Type I errors that are expected is 0.05 (i.e., $5.07\\times 10^{-5} \\times 985$)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "828f95dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of hypothesis tests: 986\n",
      "Number of null hypotheses rejected at alpha = 0.05 (i.e., without the Bonferroni correction): 372\n",
      "Number of null hypotheses rejected with Bonferroni method: 46\n",
      "Threshold after FWER correction by Bonferroni method: 5.070993914807303e-05\n"
     ]
    }
   ],
   "source": [
    "p_set = results.pvalues.values[1:]\n",
    "\n",
    "reject, p_corrected, alphac_sidak, alphac_bonf = multipletests(pvals=p_set,\n",
    "                                                               method='bonferroni',\n",
    "                                                               alpha=0.05, \n",
    "                                                               is_sorted=False,\n",
    "                                                               returnsorted=False)\n",
    "\n",
    "print('Total number of hypothesis tests:', len(p_set))\n",
    "print('Number of null hypotheses rejected at alpha = 0.05 (i.e., without the Bonferroni correction):', sum(results.pvalues.values < 0.05))\n",
    "print('Number of null hypotheses rejected with Bonferroni method:', sum(reject))\n",
    "print('Threshold after FWER correction by Bonferroni method:', alphac_bonf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "adf26086",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variables with a rejected null hypothesis using Bonferroni method:\n",
      "Statistical analysis\n",
      "Writing skills\n",
      "Shell Scripting\n",
      "Unit testing\n",
      "Keras\n",
      "Pre-employment physical examination\n",
      "Adobe Photoshop\n",
      "Linux\n",
      "Cleaning\n",
      "Docker\n",
      "Ontology\n",
      "Scripting\n",
      "SSIS\n",
      "Bank Secrecy Act\n",
      "Cognos\n",
      "Backbone.js\n",
      "Project management methodology\n",
      "Google Cloud Platform\n",
      "Title_Data Architect\n",
      "Title_Data Science Manager\n",
      "Title_Director of Data Science\n",
      "Title_Machine Learning Engineer\n",
      "Title_Software Engineer\n",
      "Company_AiCard\n",
      "Company_BBI\n",
      "Company_CalPrivate Bank\n",
      "Company_Circle\n",
      "Company_Convex Tech\n",
      "Company_CooTek\n",
      "Company_E. & J. Gallo Winery\n",
      "Company_Evolver. LLC, a CSS Company\n",
      "Company_Gayathri's Sandbox\n",
      "Company_Grammarly\n",
      "Company_Hurricane Electric\n",
      "Company_Invitae\n",
      "Company_LivePerson\n",
      "Company_Sojern\n",
      "Company_Spotline Inc\n",
      "Company_TargetCW\n",
      "Company_Teknatio\n",
      "Company_Vivun\n",
      "Company_Warman O'Brien\n",
      "Company_iMerit\n",
      "Location_Burlingame, CA\n",
      "Location_Oakland, CA\n",
      "Location_Pittsburg, CA\n"
     ]
    }
   ],
   "source": [
    "rejected_null = []\n",
    "\n",
    "print('Variables with a rejected null hypothesis using Bonferroni method:')\n",
    "for i in results.pvalues.index[1:][reject]:\n",
    "    print(i)\n",
    "    rejected_null.append(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14b0ee8e",
   "metadata": {},
   "source": [
    "## Interpreting the OLS results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f7aead70",
   "metadata": {},
   "outputs": [],
   "source": [
    "order = results.pvalues.index[1:][reject][pd.DataFrame(results.params.values[1:][reject]).sort_values(by=0, ascending=False).index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d5c044b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Company_23andMe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Title_Applied Scientist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Levels_Distinguished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Location_Alameda, CA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         0\n",
       "0          Company_23andMe\n",
       "1  Title_Applied Scientist\n",
       "2     Levels_Distinguished\n",
       "3     Location_Alameda, CA"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#model baseline\n",
    "dropped_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "94f1041c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA50AAASKCAYAAADdWArnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzde7yn9bz//8dTTQeVkmIPm4ZIiCYqSjQ5tJ02RclhkJyGLcdy2GyV00a+bCKhn4qSdEJtFJ2VzqaZapc2NRsth5QI1TS9fn9c76VPq3VuPrNm1nrcb7d1W9fnfb2v9/t1vdZan9u85n1d1ydVhSRJkiRJ/XCfqQ5AkiRJkjR9WXRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvLDql5ej4448vYMSv3/3ud6Punylf5sE8mAfzYB7MgXlYKfIgrRAWndJy9Pe//33U/XfeeecKimTlZh465qFjHjrmoWMezMEg89AxD5oOVp/qACRJEtx+5CEsmeogVhLmwRwMmsl52GTfA6Y6BGm5caVTkiRJktQ3Fp2SJEmSpL6x6JQkSZIk9Y1FpyRJkiSpbyw6JUmSJEl9Y9EpSZIkSeobi84ZIMk/JflWkl8kuTLJ95NsNtVxTVaSrZJUkn8Z0n5ez/Zm7Tz/N8n/JPl2kgfdizkPT7LbvYlbkiRJmoksOqe5JAFOBM6sqk2r6rHAvwOTLsBWAi8HftK+/0NVbQ+QZC3gv4EvVdUjq+oxwJeAjcczeJLVlm+4kiRJ0sy1+lQHoL7bCVhaVYcMNlTVwnQOBJ4LFPDRqjomyTzgAOB3wFzgBGAx8HZgbWCXqvpFksOBW4HH0RWw76qqk5PMAb4BrNOme2tVndfG3R+4AdgCuASYDzyj9dkVIMmzgTdX1YuHO5lWRO8GPBs4J8laVXVr23dLVa0LvAL4aVWd1HPOZ7Q+o8W3HzAAzE3yOOCgFt+1QMbMNLB06VIGBgYmvX+mMA8d89AxD5J0T4Pvi/18j5w9e3ZfxpWGsuic/gYLvKFeTFdUbglsBFyU5Oy2b0vgMcCNwC+BQ6tq2yRvB/YG3tH6zQF2BDYFzkjySOD3wLOr6tYkjwKOBrZu/beiK1KvB84FngqcDnwxycZV9QfgtcBho5zPU4FrW+F7JvA8usJ4POfMGPFtC2xRVdcmeTHwaODxdEX1lcDXRokLgFmzZo36Bj4wMOAbPOZhkHnomIfOkqkOQNJKZfB90fdITQdeXjtz7QAcXVXLqup3wFnANm3fRVU1UFW3Ab8ATm3ti+kKzUHfrqo7q+oauuJ0c2AW8NUki4Fjgcf29L+wqn5dVXcCC4E5VVV0K4/zk2wAbAf8YJS4Xw58q21/iyGX2I7DWPFd27afzl35uZ6uOJYkSZI0Qa50Tn9X0F2OOtRol4ve1rN9Z8/rO7n770wNOa6Ad9Jdmrsl3X9q3DrCuMt6xjoMOKn1Pbaq7hguqHav5UuAFyb5QDuHByRZr6r+0tP1CroV2OGMFt9fhzkfSZIkSfeCK53T3+nAmkneMNiQZBvgJmCPJKsl2ZhuZe/CCY69e5L7JNkUeARwNbA+MNBWM18FjPlQnraSeD3wQeDwUbo+C7isqh5aVXOqahPgeGCXIf2+CWyf5PmDDUmek+TxE4jvbOBlLT+z6e6NlSRJkjRBFp3TXLt8dVfg2e0jU66ge6DPN4FFwGV0hel7quq3Exz+arrLcn8ALGgP9DkYeE2S84HNuOfq4UiOAn5VVVeO0ufldE/i7XU83YOD/qGq/g68ANg7yTVJrgT2pLufc7zxnQhcQ3dJ8ZfaeUqSJEmaIC+vnQHaSuJLh9m1b/vq7XsmcGbP63kj7QPOrap3Djn+GuAJPU3vH2Hctw6JZQfgq2Ocx57DtH0P+F7bXren/SrgOcMM87txxlfA0BglSZIkTZBFp6ZckkvoVhzfPdWxSJIkSVq+LDo1KcOtOt6LsZ40tC3JBcCaQ5pfVVWLl9e8kiRJkvrPolMrpap68lTHIEmSJOnes+iUJGklsMb8BX4APDAwMDDj82AOOuZBmj58eq0kSZIkqW8sOiVJkiRJfWPRKUmSJEnqG4tOSZIkSVLf+CAhSZJWArcfeQhLpjqIlYR5mJk52GTfA6Y6BEl94kqnJEmSJKlvLDolSZIkSX1j0SlJkiRJ6huLTkmSJElS31h0SpIkSZL6xqJTUy7JPyf5bpJrkvwiyeeSrDHGMf8+zrFvWT5RSpIkSZoMi05NqSQBTgC+U1WPAjYD1gU+Nsah4yo6JUmSJE0ti05NtWcAt1bVYQBVtQx4J7BXkrckOSHJD9sq6KcAknwCWDvJwiRHtbZ3Jbm8fb1j6CTpHNj2L06yR2u/T5KDk1yR5OQk30+yW5JnJjmx5/hnJzmh79mQJEmSppnVpzoAzXiPAy7pbaiqPyf5P7rfz7nAVsBtwNVJDqqq9yV5a1XNBUjyJOC1wJOBABckOauqftYz7IvbWFsCGwEXJTkbeCowB3g88EDgf4CvAacDX0yycVX9oY1/2Fgns3TpUgYGBia9f6YwDx3z0DEPkoB7vA/43tDpZx5mz57dl3GloSw6NdUC1Cjtp1XVzQBJrgQ2AX41pO8OwIlV9dfW7wTgacDPhvQ5uq2k/i7JWcA2rf3YqroT+G2SMwCqqpJ8A5if5DBgO+DVY53MrFmzRn0DHxgY8A0e8zDIPHTMQ2fJVAcgTbGh7wO+N3TMg6YDi05NtSuAl/Q2JLkf8FBgGd0K56BlDP87m3HMM1Kf0Y49DDgJuJWuML1jHPNIkiRJ6uE9nZpqpwH3TfJqgCSrAf8POBz42yjHLU0yq22fDeyS5L5J1gF2Bc4Z0v9sYI8kqyXZGHg6cCHwE+Al7d7OBwHzBg+oquuB64EPtngkSZIkTZBFp6ZUVRVdkbh7kmuAn9OtLI71dNqvAIuSHFVVl9IVhRcCFwCHDrmfE+BEYBFwGd39mu+pqt8CxwO/Bi4HvtyOv7nnuKOAX1XVlZM+SUmSJGkG8/JaTbmq+hXwr8PsOpyeFcaqekHP9nuB9/a8/gzwmWHGXrd9L2Df9tW7/84k+1TVLUkeQFe4Lu7psgPw1QmflCRJkiTAolMCODnJBsAawEfaCihJLgH+Crx7CmOTJEmSVmkWnZrxqmreCO1PWsGhSJIkSdOO93RKkiRJkvrGlU5JklYCa8xf4Gfx4WcSgjmQNP240ilJkiRJ6huLTkmSJElS31h0SpIkSZL6xqJTkiRJktQ3PkhIkqSVwO1HHsKSqQ5iJWEeJpaDTfY9oG9xSNLy4EqnJEmSJKlvLDolSZIkSX1j0SlJkiRJ6huLTkmSJElS31h0SpIkSZL6xqJT00aSW4ZpW5Dk1VMRjyRJkiQ/MkXTXFUdMtUxSJIkSTOZK52a1pLsn2Sftn1mkk8muTDJz5M8rbXvmeQLPcecnGRekk2SXJNkoyT3SXJOkp2n6lwkSZKkVZErnZppVq+qbZM8D9gPeNZIHatqSZJPAocAFwBXVtWpKyhOSZIkaVqw6NRMc0L7fgkwZ6zOVXVokt2BBcDcsfovXbqUgYGBSe+fKcxDxzx0zIN070zXvx/fGzr9zMPs2bP7Mq40lEWnZprb2vdl3PX7fwd3v9R8rcGNJPcF/rm9XBf4y2iDz5o1a9Q38IGBAd/gMQ+DzEPHPHSWTHUAWmVN178f3xs65kHTgfd0SnAdMLfdt/lQYNuefZ8EjgI+BHx1CmKTJEmSVmmudGo6uW+SX/e8/sw4jzsXuBZYDFwOXAqQZEdgG+CpVbUsyUuSvLaqDlueQUuSJEnTmUWnpo2qGnXlvqrm9WzfQLuns6oKeOUIhz2l55gX3+sgJUmSpBnGy2slSZIkSX1j0SlJkiRJ6huLTkmSJElS31h0SpIkSZL6xgcJSZK0Elhj/gI/iw8/kxDMgaTpx5VOSZIkSVLfWHRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvvFBQpIkrQRuP/IQlkx1ECsJ8zC+HGyy7wF9j0OSlgdXOiVJkiRJfWPRKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHoXEkk+ack30ryiyRXJvl+ks2mOq7JSLJuki+1c/lZkkuSvGGq4xqPJHsm+cJUxyFJkiRNFxadK4EkAU4EzqyqTavqscC/Aw+a2sgm7VDgJuBRVbUV8Bxgw6Gdkqy2ogMbTRI/t1aSJElazvxH9sphJ2BpVR0y2FBVC9M5EHguUMBHq+qYJPOAA4DfAXOBE4DFwNuBtYFdquoXSQ4HbgUeR1fAvquqTk4yB/gGsE6b7q1VdV4bd3/gBmAL4BJgPvCM1mdXgCTPBt5cVS8eeiJJNgW2BV5RVXe2c/kD8Mm2fx6wHzDQYn9sku8ADwXWAj5XVV9pfW8Bvgg8i66I/XfgU8DDgHdU1feS7AnsAqzWYv5/wBrAq4DbgOdV1Y1tpfWNbd//Aq+qqr+1HN0IbAVc2vJIkvWARcBmVbU0yf3a60dV1dJ7/ASbpUuXMjAwMNLuMffPFOahYx465kGanOn+d+N7Q6efeZg9e3ZfxpWGsuhcOQwWeEO9mK4w2xLYCLgoydlt35bAY+gKpl8Ch1bVtkneDuwNvKP1mwPsCGwKnJHkkcDvgWdX1a1JHgUcDWzd+m9FV6ReD5wLPBU4Hfhiko1bAfla4LARzuVxwGWDBecItgW2qKpr2+u9WmG4djvH46vqj3RF8ZlV9d4kJwIfBZ4NPBY4AvheT/62oita/xd4b1VtleSzwKuB/wJOqKqvAiT5KPA64KB2/GbAs6pqWStiqaq/JDkTeD7wHeBlwPGjFZwAs2bNGvUNfGBgwDd4zMMg89AxD50lUx2AVjnT/e/G94aOedB04OW1K7cdgKOrallV/Q44C9im7buoqgaq6jbgF8CprX0xXaE56NtVdWdVXUNXnG4OzAK+mmQxcCxdETfowqr6dSsaFwJzqqroVkbnJ9kA2A74wXhOIMkHkixMcv2QOa7tef22JJcB59OteD6qtd8O/LDnvM5qRd/Qczyjqv7SCuKbgZOGycUWSc5p5/xKuuJ40LFVtWyY8A+lK7Bh9EJbkiRJ0ghc6Vw5XAHsNkx7Rjnmtp7tO3te38ndf6415LgC3kl3ae6WdP/xcOsI4y7rGeswumLuVroi7Y4R4roS2DLJfVqx+zHgY+1S2UF/Hdxol9s+C9iuXe56Jt2KJXSXHA/G/49zrKo7h9x/OZ5cHE532fFlbTVz3nDx9Kqqc5PMSbIjsFpVXT7COUuSJEkagSudK4fTgTV7n/CaZBu6+xj3SLJako2BpwMXTnDs3ZPcp91r+QjgamB9YKCtZr6K7n7IUVXV9XSX3H6QroAbqd//AhcDHx18UFCStRi5gF4fuKkVnJsDTxnviU3QesBAkll0K53j9XW6y49d5ZQkSZImwaJzJdBW83YFnt0+ZuQKugf6fJPu4TWX0RWm76mq305w+KvpLsv9AbCgqm4FDgZek+R8uvsZh13pG8ZRwK+q6sox+r0eeADwv0kuAX4MvHeEvj8EVk+yCPgI3SW2/fAfwAXAj4CrJnDcUcD96QpPSZIkSROUu65e1HTTnsx6clUdt5zG+wLws6r6/5bHeKuCJLsBL6qqV42n/5FHHlnz588fcb8PA+iYh4556JiHzpID95vqELSK2WTfA6Y6hL7yvaHT5zyMdiuXtNx4T6fGpa1Y/hV491THsqIkOYju42qeN9WxSJIkSasqi85prKr2XI5jPWloW5ILgDWHNL+qqhYvr3mnUlXtPdUxSJIkSas6i05NWlU9eapjkCRJkrRys+iUJGklsMb8Bd6/hvfxgTmQNP349FpJkiRJUt9YdEqSJEmS+saiU5IkSZLUN97TKUnSSuD2Iw9hyVQHsZKYiXmY7p+5KWlmc6VTkiRJktQ3Fp2SJEmSpL6x6JQkSZIk9Y1FpyRJkiSpbyw6JUmSJEl9Y9EpSZIkSeobi06tMpIsS7IwyRVJLkvyriST+h1Ocl2SjZZ3jJIkSZLuzs/p1Krk71U1FyDJA4FvAusD+62oAJKsXlV3rKj5JEmSpFWdK51aJVXV74E3Am9NZ60khyVZnORnSXYCSLJakk+39kVJ9u4dJ8naSX6Y5A1J1knytSQXtTFe1PrsmeTYJCcBp67wk5UkSZJWYa50apVVVb9sl9c+EJjf2h6fZHPg1CSbAa8FHg5sVVV3JNmwZ4h1gW8BX6+qryf5OHB6Ve2VZAPgwiQ/bn23A55QVTeOFtPSpUsZGBiY9P6Zwjx0zEPHPEjc7W/Av4mOeej0Mw+zZ8/uy7jSUBadWtWlfd8BOAigqq5KsgTYDHgWcMjgJbFDisbvAp+qqqPa652BFybZp71eC3hY2/7RWAUnwKxZs0Z9Ax8YGPANHvMwyDx0zENnyVQHoCnV+zfg30THPHTMg6YDL6/VKivJI4BlwO+5q/i8RzegRth3LvDcJOnp+5Kqmtu+HlZV/9P2/XV5xS1JkiTNJBadWiUl2Rg4BPhCVRVwNvDKtm8zuhXKq+nuwVyQZPW2r/fy2g8BfwQObq9PAfYeLEKTbLUCTkWSJEma1iw6tSpZe/AjU4Af0xWUB7R9BwOrJVkMHAPsWVW3AYcC/wcsSnIZ8IohY74DWCvJp4CPALNa38vba0mSJEn3gvd0apVRVauNsu9WYM9h2u8A3tW+etvn9Lx8bc/2m4YZ43Dg8InEKkmSJKnjSqckSZIkqW8sOiVJkiRJfWPRKUmSJEnqG+/plCRpJbDG/AV+Fh9+JqEkTUeudEqSJEmS+saiU5IkSZLUNxadkiRJkqS+seiUJEmSJPWNDxKSJGklcPuRh7BkqoNYSaxqedhk3wOmOgRJWqm50ilJkiRJ6huLTkmSJElS31h0SpIkSZL6xqJTkiRJktQ3Fp2SJEmSpL6x6JQkSZIk9Y1F53KQ5JY+jbtBkrf0vH5wkuOW8xzXJVmcZGH7/qJJjLF/kn3a9oeTPGt5xthPSdZN8uUkv0hyRZKzkzy5Z/+uSSrJ5lMZpyRJkrSqsuhcuW0A/KPorKrrq2q3PsyzU1XNBXYDPj+RA5Pc7bNeq+pDVfXj5Rhbvx0K3Ag8qqoeB+wJbNSz/+XAT4CXrfjQJEmSpFWfRWefJJmb5Pwki5KcmOT+rf2RSX6c5LIklybZtK22ndZe9642fgLYtK1CHphkTpLL2zhrJTms9f9Zkp1a+55JTkjywyTXJPnUBMK+H3BTG+cfc7XX+yTZv22fmeTjSc4C3j7kvA9Pslvbvi7JAT3ntXlr3zjJj1r7l5MsSbJR2/edJJe0Vcc39ox7S5JPtn0/TrJti+OXSV7Y+qzW8nRRy/ubxvgZbQo8GfhgVd0JUFW/rKr/bvvXBZ4KvA6LTkmSJGlSVh+7iybp68DeVXVWkg8D+wHvAI4CPlFVJyZZi67wvx3Ytar+3Iqv85N8D3gfsEVbhSTJnJ7x/w2gqh7firlTk2zW9s0FtgJuA65OclBV/WqUWM9IEuARwEvHeX4bVNWOLa79R+l3Q1U9sV0mvA/werpcnF5V/5nkOcAbe/rvVVU3JlkbuCjJ8VX1R2Ad4Myqem+SE4GPAs8GHgscAXyPrji8uaq2SbImcG6SU6vq2hFiexywsKqWjbB/F+CHVfXzJDcmeWJVXTpaUpYuXcrAwMCk988U5qFjHjrmQau65f37699Exzx0+pmH2bNn92VcaSiLzj5Isj5dUXZWazoCODbJesBDqupEgKq6tfWfBXw8ydOBO4GHAA8aY5odgIPaOFclWQIMFp2nVdXNbewrgU2A0YrOnarqhrbyd1qSM8dxmseMow/ACe37JcCLe2LftcX+wyQ39fR/W5Jd2/ZDgUcBf6QrzH/Y2hcDt1XV0iSLgTmtfWfgCYMrrcD67fiRis6xvBz4r7b9rfZ61KJz1qxZo76BDwwM+AaPeRhkHjrmobNkqgPQpC3v31//JjrmoWMeNB1YdK5YGaH9lcDGwJNaIXUdsNYkx4JuhXPQMsb5c66qXyT5Hd3q4fXc/fLrofH8dTxj9sTSG8ewsSeZBzwL2K6q/taK38F5l1ZVte07B8etqjt77isN3eryKeOM7QpgyyT3Gby8tieWBwDPALZIUsBqQCV5T08ckiRJksbgPZ190FYZb0rytNb0KuCsqvoz8OskuwAkWTPJfelW5H7fCs6d6FYmAf4CrDfCNGfTFau0y2ofBlx9b+JO8kDg4XT/4f474IFJHtAuVX3BvRl7iJ/QLuNNsjNw/9a+PnBTKzg3B54ywXFPAd7cVo5JslmSddr2VUM7V9UvgIuBA9rlxSR5VLundjfg61W1SVXNqaqH0q2Y7jDBmCRJkqQZzaJz+bhvkl/3fL0LeA1wYJJFdPdYfrj1fRXdJaSLgPOAf6K7z3PrJBfTFZJXAbR7Gc9NcnmSA4fMeTCwWru89Bhgz6q6jck5I8lC4AzgfVX1u6pa2mK+ADh5MKbl5ABg5ySXAs8FBugK7B8Cq7fcfAQ4f4LjHgpcCVzaHoL05TbeRoy8Mvx6up/B/7ZcfpVulfflwIlD+h4PvGKCMUmSJEkzWrxSUCtaWzldVlV3JNkO+NLgw5L6NN8LgEdU1YQ+DmYyjjzyyJo/f/6I+70vo2MeOuahYx46Sw7cb6pD0CRtsu8By3U8/yY65qHT5zyMdruWtNx4T6emwsOAbycZfHLvG/o5WVWd3M/xJUmSJI3MonOGSHIBsOaQ5ldV1eIVHUtVXUP3kS6SJEmSpjmLzhmiqp481TFIkiRJmnksOiVJWgmsMX+B96/hfXySNB359FpJkiRJUt9YdEqSJEmS+saiU5IkSZLUNxadkiRJkqS+8UFCkiStBG4/8hCWTHUQK4kVlYdN9j1gBc0kSTObK52SJEmSpL6x6JQkSZIk9Y1FpyRJkiSpbyw6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt/MiKIzyQOSLGxfv03ym7Z9S5KDW595SbbvOWb/JPtMYq79e8a/JskJSR7bs//Q3tf34pzuFu/yluToJIuSvHNI+6jnN8p4eyZ58ARjeHSSM9tc/5PkK2P0Xy65lSRJkrT8zIjP6ayqPwJzoSuagFuq6tNDus0DbgHOWw5TfnZw/CR7AKcneXxV/aGqXj/cAUlWq6plE5hjHhOMN8nqVXXHOPr9E7B9VW0yQpcRz2+UYfcELgeuH2+8wOfbXN9tcz1+tM4j5VaSJEnS1JkRRedIkswD9gHeCiwAliWZD+w9pN+mwBeBjYG/AW+oqqvGM0dVHZPk+cArgM8lORPYp6ouTnIL8BngX4B3J5kDvA1YA7gAeEtVLUvyHODjwGrADcDrhon3/4CvtRj/ALy2qv4vyeHAjcBWwKXAu3vOay3gS8DWwB3Au6rqDOBU4IFJFgJ7V9U5Ezi/DwH/CqxNVxC/CXhJm+OoJH8HtgP2HdqvqmrI8LOBX/fMtbjFvRrwyZa3Ar5aVQcNye3OwAHAmsAvWj5uSXIdcESbexawe1VdlWRd4KAWZwEHVNXxI40zUj6WLl3KwMDASLvH3D9TmIeOeeiYB02VlfX3zr+Jjnno9DMPs2fP7su40lAzuugcVFXXJTmEnhXQJM/s6fIVYEFVXZPkycDBwDMmMMWlwObDtK8DXF5VH0ryGOC9wFOramm77PeVSX4AfBV4elVdm2TDqrpxmHhPAr5eVUck2YtulXCXNs9mwLOGWUn9t3b+j0+yOXBqks2AFwInV9XcSZzfF6rqwy2mbwAvqKrjkryVVhC2fffoB5w0ZNzP0q2inkdXCB9WVX8C3gg8HNiqqu5IsmHvQUk2Aj7YzvmvSd4LvAv4cOtyQ1U9Mclb6P7T4fXAfwA3V9Xj2xj3H8c49zBr1qxR38AHBgZ8g8c8DDIPHfPQWTLVAcxAK+vvnX8THfPQMQ+aDiw6x9BWwLYHjk0y2LzmRIcZoX0ZcHzbfibwJOCiNs/awO+BpwBnV9W1AFV14whjbQe8uG1/A/hUz75jR7h0dwe61T3aat8SugL1z+M4p16957dTkvcA9wU2BK7gnsXkuPpV1WFJTgGeA7wIeFOSLYFnAYcMXio8TE6eAjwWOLflcg3gpz37T2jfL+GunD0LeFnP3DclecEY40iSJEkag0Xn2O4D/GkCq37D2Qq4eJj2W3uKwQBHVNX7ezskeSHd5Z4T1XvMX0foM1IxPFFbARe3y3UPBrauql+1+2fXusek4+wHUFXX0102/LUklwNbtLhHy0mAH1XVy0fYf1v7voy7/gaGG3OscSRJkiSNYUY8vXac/gKsN7Sxqv4MXJtkd4B0thzvoEleAuwMHD1G19OA3ZI8sB23YZJN6FbWdkzy8MH2EeI9j7tW6l4J/GQc4Z3d+tIuq30YcPU4jvuHIec3WDje0FaId+vp2hvvaP16x35Okllt+5+ABwC/obvUdkGS1du+DYccej7w1CSPbPvv285vNKfS3ds7OPf9JzmOJEmSpB4WnXc5Cdi1fTzH04bseyXwuiSX0V0G+qIxxnrn4EeKAPOBZ4zxZFeq6kq6+wdPTbII+BEwux33RuCENv8xI8T7NuC17dhXAW8fxzkfDKyWZHEbd8+qum2MY0Y8v3a/5VeBxcB3gIt6jjkcOKQ9nOi2Ufr12hm4vJ33KcC+VfVb4FC6Byctavte0XtQy9mewNEtH+cz/D21vT4K3D/J4Hw7TXIcSZIkST1yzweGSpqsI488subPnz/ifh8G0DEPHfPQMQ+dJQfuN9UhzDib7HvAVIcwLP8mOuah0+c8LK9braRRudIpSZIkSeobHyQ0SUk+AOw+pPnYqvrYVMQjSZIkSSsji85JasWlBaYkSZIkjcKiU5KklcAa8xd4/xrexydJ05H3dEqSJEmS+saiU5IkSZLUNxadkiRJkqS+8Z5OSZJWArcfeQhLpjqIlcTyysPK+jmckjTTuNIpSZIkSeobi05JkiRJUt9YdEqSJEmS+saiU5IkSZLUNxadkiRJkqS+sejUsJJ8IMkVSRYlWZjkya39uiQbTWCceUlObtt7JvnCMH0elOTkJJcluTLJ9ycY64Ikrx5HHNtP5BhJkiRJ954fmaJ7SLId8ALgiVV1Wysy1+jjlB8GflRVn2vzP2G8ByZZvaoOGUfXecAtwHkA4zxGkiRJ0r1k0anhzAZuqKrbAKrqhiH7907yr8AsYPequirJOsBBwOPpfq/2r6rvTmC+UwdfVNWiwe0k7wFeBdwJ/KCq3pfkTLri8anA95KsB9xSVZ9u+xYC2wL3A/YCfg8sAJYlmQ/sDTxzyDEXADsBGwCvq6pzktwXOBzYHPgfYA7wb1V18TjPS5IkSZrxvLxWwzkVeGiSnyc5OMmOQ/bfUFVPBL4E7NPaPgCcXlXb0BVvB7ZCdDy+CPx/Sc5ol/U+GCDJc4FdgCdX1ZbAp3qO2aCqdqyq/zfMeOtU1fbAW4CvVdV1wCHAZ6tqblWdM8wxq1fVtsA7gP1a21uAm6rqCcBHgCeN83wkSZIkNa506h6q6pYkTwKeRldAHpPkfVV1eOtyQvt+CfDitr0z8MIkg0XoWsDDxjnfKUkeATwHeC7wsyRbAM8CDquqv7V+N/YcdswoQx7d+p+d5H5JNhhHGL3nNKdt7wB8ro11eZJFwxx3N0uXLmVgYGDS+2cK89AxDx3zoH5ZVX+v/JvomIdOP/Mwe/bsvowrDWXRqWFV1TLgTODMJIuB19BdagpwW/u+jLt+hwK8pKqu7h0nyYPGOd+NwDeBb7YHDz29jVkjHPLX0YYb4/VwRjqnCZk1a9aob+ADAwO+wWMeBpmHjnnoLJnqAKahVfX3yr+JjnnomAdNB15eq3tI8ugkj+ppmsvY/x46he5ez7QxtprAfM9o90/S7s/cFPg/ust89+rZt+E4h9yj9d8BuLmqbgb+Aqw33pianwAvbWM9lu5+VUmSJEkT4EqnhrMucFC7LPUO4H+BN45xzEeA/wIWtcLzOron4I7Hk4AvJLmD7j9CDq2qiwCSzAUuTnI78H3g38cx3k1JzuOuBwkBnAQcl+RFdA8SGo+DgSPaZbU/AxYBN4/zWEmSJElYdGoYVXUJsP0I++b0bF9M91EkVNXfgTcN0/9Must0afeEHj5MnwOBA0eY7xPAJ4a0zRvyev8hhx1fVe8f0ufnQO9HsZzTs29ez/YN3HVP563A/Kq6NcmmwGl4BZwkSZI0IRad0sjuC5yRZBbd/Z1vrqrbpzgmSZIkaZVi0alpZegq6L0c6y/A1strPEmSJGkm8kFCkiRJkqS+seiUJEmSJPWNl9dKkrQSWGP+Aj+LDz+TUJKmI1c6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+sYHCUmStBK4/chDWDLVQawkJpKHTfY9oG9xSJKWD1c6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+saiU5IkSZLUNxadkiRJkqS+sehcRSR5QJKF7eu3SX7Ttm9JcnDrMy/J9j3H7J9kn0nMtX/P+NckOSHJY8dx3J5JHjzR+dqxlyU5ehLH7ZnkCyPs+36SDdrXWyYTVxtnl/GcvyRJkqR7suhcRVTVH6tqblXNBQ4BPtter1tVgwXVPGD7kcaYoMHxHwUcA5yeZOMxjtkTmHDRmeQxdL+LT0+yzgh9JvyZslX1vKr6E7ABMOmiE9gFsOiUJEmSJmHC/5DXyiXJPGAf4K3AAmBZkvnA3kP6bQp8EdgY+Bvwhqq6ajxzVNUxSZ4PvAL4XJIPAf8KrA2cB7wJeAmwNXBUkr8D2wH7Du1XVTXMFK8AvgE8BnghcHSL+cx23FOB7yU5G/gcsA5wG/DMdvyDk/wQ2BQ4sare046/rsX0CWDTJAuBH1XVvkn2BV4KrNmO2a8d8+qWzwIWAV9qMe2Y5IPAS6rqFyPlaunSpQwMDIyYy7H2zxTmoWMeOuZB98Z0/N3xb6JjHjr9zMPs2bP7Mq40lEXnNFFV1yU5BLilqj4NkOSZPV2+AiyoqmuSPBk4GHjGBKa4FNi8bX+hqj7c5vgG8IKqOi7JW4F9quritu8e/YCThhl7D+DZwKPpiufey2w3qKodk6wBXAXsUVUXJbkf8PfWZy6wFV0henWSg6rqVz1jvA/Yoq0Sk2Rn4FHAtkDoCtqnA38EPgA8tapuSLJhVd2Y5HvAyVV13FhJmjVr1qhv4AMDA77BYx4GmYeOeegsmeoAVlHT8XfHv4mOeeiYB00HFp0zQJJ16S67PTbJYPOaEx2mZ3unJO8B7gtsCFzB8MXkmP2SbAP8oaqWJPk18LUk96+qm1qXY9r3RwMDVXURQFX9uR0PcFpV3dxeXwlsAvQWnUPt3L5+1l6vS1eEbgkcV1U3tDluHGUMSZIkSeNg0Tkz3Af40+BK3yRtBVycZC26VdKtq+pXSfYH1hraebz9gJcDm7dLYQHuR3ep7qHt9V8Hh6S75HU4t/VsL2Ps3+sA/1lVXx4S89tGmUOSJEnSJPggoenlL8B6QxvbquC1SXYHSGfL8Q6a5CV0K4NHc1fheENbQd1thPlH6zc47n2A3YEnVNWcqpoDvIiuEB3qKrp7N7dpx643gYcLDc3LKcBeLS6SPCTJA4HTgJcmeUBr33CE4yVJkiSNk0Xn9HISsGv7qJOnDdn3SuB1SS6ju8z1RWOM9c7Bj0wB5gPPqKo/tKfBfhVYDHwHuKjnmMOBQ9oDe24bpd+gpwO/qarf9LSdDTw2yd1uXqiq2+nu/TyoncOPGH7l9B6q6o/AuUkuT3JgVZ0KfBP4aZLFwHHAelV1BfAx4Kw2x2faEN8C9k3ys/ZAJkmSJEnjlOEfJippMo488siaP3/+iPt9GEDHPHTMQ8c8dJYcuN9Uh7BK2mTfA6Y6hOXOv4mOeej0OQ8Zu4t077nSKUmSJEnqGx8kNIMl+QDdPZW9jq2qj01FPJIkSZKmH4vOGawVlxaYkiRJkvrGolOSpJXAGvMXeP8a3scnSdOR93RKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHolCRJkiT1jQ8SkiRpJXD7kYewZKqDWEmMlIdN9j1ghcYhSVo+XOmUJEmSJPWNRackSZIkqW8sOiVJkiRJfWPRKUmSJEnqG4tOSZIkSVLfWHROc0l2TVJJNh+lz5lJth5jnFvuRQx7JvlDkoVJrkzyhta+f5J9JjDOBkneci/imPQ5SJIkSZoci87p7+XAT4CXTXEcx1TVXGAe8PEkD5rEGBsAky46JUmSJK14Fp3TWJJ1gacCr6On6EyydpJvJVmU5Bhg7Z59L0+yOMnlST45ZLz/l+TSJKcl2bi1bZrkh0kuSXLOaCuqAFX1e+AXwCat6bFtpfWXSd7WM9e7WgyXJ3lHa/4EsGlbMT0wnQNbn8VJ9mjHzk5ydut3eZKn9Yz7sSSXJTl/sPBNskk7p0Xt+8Na++FJDmnn9fMkL5hI/iVJkiTB6lMdgPpqF+CHVfXzJDcmeWJVXQq8GfhbVT0hyROASwGSPBj4JPAk4Cbg1CS7VNV3gHWAS6vq3Uk+BOwHvBX4CrCgqq5J8mTgYOAZIwWU5BHAI4D/bU2bAzsB6wFXJ/kS8ATgtcCTgQAXJDkLeB+wRVsxJclLgLnAlsBGwEVJzgZeAZxSVR9Lshpw3zbXOsD5VfWBJJ8C3gB8FPgC8PWqOiLJXsDnW+4A5gA7ApsCZyR5ZFXdOtL5LV26lIGBgZF2j7l/pjAPHfPQMQ8ar5nye+LfRMc8dPqZh9mzZ/dlXGkoi87p7eXAf7Xtb7XXlwJPpyusqKpFSRa1PtsAZ1bVHwCSHNX6fge4Ezim9TsSOKGtpG4PHJtkcM41R4hljyQ7ALcBb6qqG9sx/11VtwG3Jfk98CBgB+DEqvpri+ME4GnA94aMuQNwdFUtA37XCtNtgIuAryWZBXynqha2/rcDJ7ftS4Bnt+3tgBe37W8An+qZ49tVdSdwTZJf0hXJCxnBrFmzRn0DHxgY8A0e8zDIPHTMQ2fJVAewCpgpvyf+TXTMQ8c8aDqw6JymkjyAbsVxiyQFrAZUkve0LjXcYROYouguz/7T4MrjGI6pqrcO035bz/Yyut/J8cYxbL+qOjvJ04HnA99IcmBVfR1YWlWD5z0417BDjLA93GtJkiRJo/CezulrN7pLRjepqjlV9VDgWrrVwbOBVwIk2YLuclaAC4Adk2zULkt9OXBW23efNiZ0l6/+pKr+DFybZPc2VpJsuRxiPxvYJcl9k6wD7AqcA/yF7jLc3n57JFmt3WP6dODCJJsAv6+qrwL/H/DEMeY7j7vueX0l3YOXBu2e5D5JNqW7LPjqe3lukiRJ0oziSuf09XK6B+/0Op6uYHwXcFi7rHYhcCFAVQ0keT9wBt0q4ver6rvt2L8Cj0tyCXAzsEdrfyXwpSQfBGbRXcZ72b0JvKouTXL4YFzAoVX1M4Ak5ya5HPgB8B66S2Mvo1uBfE9V/TbJa4B9kywFbgFePcaUb6O7HHdf4A9095MOupqu8H4Q3b2rI97PKUmSJOmeLDqnqaqaN0zb53teDvsRKlX1TeCbw7Sv2zb/Y0j7tcBzxojlcODwYdr3H/J6i57tzwCfGeaYVwxp2rd99fY5AjhimGPX7dk+DjiubV/HyA8/Oreq3jnCPkmSJElj8PJaSZIkSVLfuNIpjaCq9pzqGCRJkqRVnSudkiRJkqS+caVTkqSVwBrzF/hZfPiZhJI0HbnSKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGolOSJEmS1Dc+SEiSpJXA7UcewpKpDmIF22TfA6Y6BEnSCuBKpyRJkiSpbyw6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+saiU5IkSZLUNxadTZIHJFnYvn6b5Ddt+5YkB7c+85Js33PM/kn2mcRc+/eMf02SE5I8dhzH7ZnkwROc69FJzmxz/U+Sr4zR/9DxxLK8JTk8yd+SrNfT9rkklWSjFR2PJEmSpOXDz+lsquqPwFzoikLglqr69JBu84BbgPOWw5SfHRw/yR7A6UkeX1V/GOWYPYHLgesnMM/n21zfbXM9frTOVfX6CYy9vP0v8CLgyCT3AXYCfjOF8QwryWpVtWyq45AkSZJWBa50jqGtbp6cZA6wAHhnWzV82pB+myb5YZJLkpyTZPPxzlFVxwCnAq9oY30oyUVJLk/ylXR2A7YGjmrzrz1cv2GGnw38umeuxW2O1ZJ8OsniJIuS7N3az0yyddveOclPk1ya5Ngk67b265Ic0NoXD55rknWTHNYz5ktGG2cYRwN7tO15wLnAHT05/k7L7xVJ3tjTfkuSjyW5LMn5SR7U2v81yQVJfpbkxz3tGyf5UYvny0mWDK6mJpmf5MKW4y8nWa1njg8nuQDYblw/WEmSJEmudI5XVV2X5BB6VkCTPLOny1eABVV1TZInAwcDz5jAFJcCg4XqF6rqw22ObwAvqKrjkrwV2KeqLm777tEPOGnIuJ+lW0U9j66wPayq/gS8EXg4sFVV3ZFkw96DWhH2QeBZVfXXJO8F3gV8uHW5oaqemOQtwD7A64H/AG6uqse3Me4/jnF6XQO8KMn9gZcDRwLP7dm/V1XdmGRt4KIkx7cV6nWA86vqA0k+BbwB+CjwE+ApVVVJXg+8B3g3sB9welX9Z5LntFyQ5DF0Re9Tq2ppusuqXwl8vc1xeVV9aJi4/2Hp0qUMDAxMev9MYR465qFjHmau4X7u/j6Yg0HmodPPPMyePbsv40pDWXQuB23lbnvg2J7FxjUnOkzP9k5J3gPcF9gQuIJ7FpPj6ldVhyU5BXgO3aWrb0qyJfAs4JCquqP1u3HI2E8BHguc285pDeCnPftPaN8vAV7ctp8FvKxn7puSvGCMcYY6oY3xZOBNQ/a9LcmubfuhwKOAPwK3Ayf3xPPstv3PwDFJZrd5r23tOwC7thh/mOSm1v5M4El0BS3A2sDv275lwPGjxA3ArFmzRn0DHxgY8A0e8zDIPHTMQ2fJVAcwBYb7ufv7YA4GmYeOedB0YNG5fNwH+FNVzb0XY2wFXJxkLbpV0q2r6lfp7i9da2jn8fYDqKrrga8BX0tyObAFXZFbo8QT4EdV9fIR9t/Wvi/jrt+j4cYca5yhvkW36ntEVd05WMQnmUdX1G5XVX9LciZ3ne/Sqhqctzeeg4DPVNX32vH798Q0nLR53z/Mvlu9j1OSJEmaOO/pnJi/AOsNbayqPwPXJtkdoN2DueV4B233Pu5Md0/jYCF1Q1tB3W2E+Ufr1zv2c5LMatv/BDyA7uE8pwILkqze9m045NDzgacmeWTbf98km41xKqcCb+2Z+/4THaeq/g/4AF1B3Wt94KZWcG5OtxI7lvW560FEr+lp/wnw0hbPzsD9W/tpwG5JHtj2bZhkk3HMI0mSJGkEFp0TcxKwa4Z5kBDdvX+vS3IZ3WWuLxpjrHe2ca4B5gPPqKo/tPstvwosBr4DXNRzzOHAIUkW0q00jtSv187A5S2uU4B9q+q3wKHA/wGL2r5X9B7UnqK7J3B0kkV0xeNYD0f6KHD/dA82ugzYaTLjVNWXq+oXQ5p/CKzexvhIG2cs+9Nd8nwOcENP+wHAzkkupbtndAD4S1VdSXf/6altnh/RPYhJkiRJ0iTlrqsSpZkhyZrAsvYApe2AL93LS6P/4cgjj6z58+ePuN/7MjrmoWMeOuahs+TA/aY6hBVuk30PuEebvw/mYJB56PQ5DyPdciQtV97TqZnoYcC3030W6O10T7uVJEmS1AcWnX2U5APA7kOaj62qj01FPOpU1TV0D26SJEmS1GcWnX3UiksLTEmSJEkzlkWnJEkrgTXmL/D+NUnStOTTayVJkiRJfWPRKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGBwlJkrQSuP3IQ1gy1UH00Sb7HjDVIUiSpogrnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvLDolSZIkSX1j0SlJkiRJ6huLTkmSJElS31h0TqEk/5TkW0l+keTKJN9PstlUxzVZSfZKsjjJoiSXJ3nRJMeZl2T7ntf7J9mnbX84ybOWQ6xzklx+b8eRJEmSNDo/p3OKJAlwInBEVb2stc0FHgT8fApDm5Qk/wx8AHhiVd2cZF1g40kONw+4BThv6I6q+tCkg5QkSZK0wll0Tp2dgKVVdchgQ1UthH8UpJ8CngsU8NGqOibJPOAA4HfAXOAEYDHwdmBtYJeq+kWSw4FbgcfRFbHvqqqTk8wBvgGs06Z8a1Wd18bdH7gB2AK4BJgPPKP12bXF9WzgzVX14mHO54HAX+iKRarqlsHtJGcCC4FtgfsBe1XVhUk2BL4GPAL4G/BG4M/AAmBZkvnA3r2TtHM7uaqOS3IdcATwr8AsYPequirJOsBBwOPpfsf3r6rvDvdDaGPuCbwQuC+wKXBiVb2n7XsO8HFgNeCGqnrmSOMALF26lIGBgUnvnynMQ8c8dMzDzDDen7G/D+ZgkHno9DMPs2fP7su40lAWnVNnsLgbzovpisotgY2Ai5Kc3fZtCTwGuBH4JXBoVW2b5O10Bdo7Wr85wI50RdQZSR4J/B54dlXdmuRRwNHA1q3/VnRF6vXAucBTgdOBLybZuKr+ALwWOGyEmC+jK4avTXIacEJVndSzf52q2j7J0+kKzS3oCuifVdUuSZ4BfL2q5iY5BLilqj4NkGS0Qu+GqnpikrcA+wCvp1txPb2q9kqyAXBhkh9X1V9HGWduy8FtwNVJDqIr3L8KPL2qrm1F8qhmzZo16hv4wMCAb/CYh0HmoWMeOkumOoA+G+/P2N8HczDIPHTMg6YD7+lcOe0AHF1Vy6rqd8BZwDZt30VVNVBVtwG/AE5t7YvpCs1B366qO6vqGrridHO61cCvJlkMHAs8tqf/hVX166q6k25Vck5VFd3K6PxWvG0H/GC4gKtqGfAcYDe6y4M/m2T/ni5Ht35nA/dr4+3QxqeqTgcekGT98SapOaF9v6Tn/HcG3pdkIXAmsBbwsDHGOa2qbq6qW4ErgU2ApwBnV9W1LcYbJxibJEmSNOO50jl1rqAr0IaTUY67rWf7zp7Xd3L3n2cNOa6Ad9KtRm5J9x8Ot44w7rKesQ4DTmp9j62qO0YKrBWpF9KtLP6oHbv/KPEMd55D+41lMO7emAO8pKqunsQ4vWNlEvFIkiRJ6uFK59Q5HVgzyRsGG5Jsk2RH4GxgjySrJdkYeDpdMTcRuye5T5JN6e6ZvBpYHxhoq5mvortPcVRVdT3dJbcfBA4fqV+SByd5Yk/TXO5+tdgerd8OwM1VdTPdeb6ytc+ju1T2z3T3hq43npMcwSnA3u3eWJJsNclxfgrsmOThbZwxL6+VJEmSdHeudE6RqqokuwL/leR9dCuJ19Hdk3k23aWsl9GttL2nqn6bZPMJTHE13WW5DwIWtPs4DwaOT7I7cAYw2j2OvY4CNq6qK0fpMwv4dJIHt3P5A90DgQbdlOQ82oOEWtv+wGFJFtE9SOg1rf0k4Lj2kSt3e5DQOH0E+C9gUSs8rwNeMNFBquoPSd4InJDkPrR7YicRjyRJkjRjWXROobaK+NIRdu/bvnr7n0l3j+Lg63kj7QPOrap3Djn+GuAJPU3vH2Hctw6JZQe6B+qMqKqW0D3tdiTHV9X7hxxzI3CPz/Ksqp8PifOcnn179mzP6dm+mO6jVqiqvwNvGiPe6+geZkRVHU7PKm5VvaBn+weMcB+rJEmSpLFZdGpUSS6hWxF991THIkmSJGnVY9E5DfWuBi6HsZ40tC3JBcCaQ5pfVVWLRxhj3vKKR5IkSdKqxaJTE1ZVT57qGCRJkiStGiw6JUlaCawxf4EfAC9Jmpb8yBRJkiRJUt9YdEqSJEmS+saiU5IkSZLUN97TKUnSSuD2Iw9hyVQHMYZN9j1gqkOQJK2CXOmUJEmSJPWNRackSZIkqW8sOiVJkiRJfWPRKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGolOSJEmS1DcWnX2U5AFJFrav3yb5Tdu+JcnBrc+8JNv3HLN/kn0mMdejk5zZxv+fJF8ZxzFHJ1mU5J1J3pHkvhOdd3lo5/ybnlwtTLLBJMdakOTVyzlESZIkSZO0+lQHMJ1V1R+BudAVVsAtVfXpId3mAbcA593L6T4PfLaqvtvme/xonZP8E7B9VW3SXl8HHAn87V7G0TvH6lV1xzi7f3aY3ExYVR1yb8cYTZIAqao7+zmPJEmSNF1YdE6BJPOAfYC3AguAZUnmA3sP6bcp8EVgY7pi8A1VddUIw84Gfj34oqoWtzHWAr4EbA3cAbyrqs4ATgUemGQhcCLwYOCMJDe0/k+pqncleTvw9qp6RIvniKraIcmHgH8F1qYrmN9UVZXkzPb6qcD32uvPAOsCNwB7VtXAOPO0J/BC4L7ApsCJVfWetu91wHuB64FrgNuq6q29xX2b+wJgJ2AD4HVVdU6S1YBP0BX8awJfrKovt3H3BV7a2k+sqv2SzAF+AJwBbAfsAiwZLualS5cyMDDy6Y21f6YwDx3z0DEPq44V8XPy98EcDDIPnX7mYfbs2X0ZVxrKonMKVdV1SQ6hZwU0yTN7unwFWFBV1yR5MnAw8IwRhvsscHqS8+gKysOq6k/Av7W5Hp9kc+DUJJvRFXMnV9XcNu9rgZ2q6oa2CrpvG/dpwB+TPATYATintX+hqj7cjv0G8ALgpLZvg6raMcks4CzgRVX1hyR7AB8D9hom/ne2whvgpqraqW3PBbYCbgOuTnIQsAz4D+CJwF+A04HLRsjL6lW1bZLnAfsBzwJeB9xcVdskWRM4N8mpwKPa17ZA6IrmpwP/BzwaeG1VvWWEeQCYNWvWqG/gAwMDvsFjHgaZh4556Az7P1krmRXxc/L3wRwMMg8d86DpwKJzJZVkXWB74Njuik6gW30bVlUdluQU4DnAi4A3JdmSrlA8qPW5KskSYDPgz6OM9dsk6yZZD3go8E3g6XQF6Amt205J3kO3CrkhcAV3FZ3HtO+PBrYAftTOYTVgpP+qG+ny2tOq6maAJFcCmwAbAWdV1Y2t/dh2TsMZjPcSYE7b3hl4QpLd2uv16YrNndvXz1r7uq39/4AlVXX+CHNIkiRJGoFF58rrPsCfBlcix6Oqrge+BnwtyeV0BV9GP2pEPwVeC1xNt7q5F92lpe9ul+weDGxdVb9ql7Su1XPsX9v3AFdU1XaTjAG6Fc5By+h+ZydyToPHDx47GNfeVXVKb8ck/wL85+Cltj3tc7jrnCRJkiRNgE+vnXp/AdYb2lhVfwauTbI7dA+waSuXw0rynHY56+BDgh4A/AY4G3hla98MeBhdITlWHGfT3Xd6Nt3K3050903ezF0F5g1tRXY3hnc1sHGS7dr8s5I8bqRzmIALgR2T3D/J6sBLJnj8KcCbe/K1WZJ1Wvte7ZxI8pAkD1wO8UqSJEkzliudU+8k4LgkL2LIg4ToisUvJfkgMAv4FiPfu7gz8Lkkt7bX+7bLZA8GDkmymO5BQntW1W09l+wO+grwgyQD7X7Kc+gurT27qpYl+RVwFUBV/SnJV4HFwHXARcMFVFW3t0tYP59kfbrft/+iuxR3qN57OqF7WM+wquo3ST5O95Cg64ErgZtH6j+MQ+kutb20PY32D8AuVXVqkscAP235uQWYT7dKKkmSJGkSUlVTHYM0YUnWrapb2krnicDXqurEqY7ryCOPrPnz54+434cBdMxDxzx0zENnyYH7TXUIY9pk3wP6Poe/D+ZgkHno9DkPk70NS5oQL6/Vqmr/9nEvlwPXAt+Z0mgkSZIkDcvLa1cxST4A7D6k+diq+thUxDNVqmqfqY5BkiRJ0tgsOlcxrbicUQWmJM0Ea8xf4KWEkqRpyctrJUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+sYHCUmStBK4/chDWDKF86+Iz+CUJM1MrnRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvLDolSZIkSX2zyhSdSR6QZGH7+m2S37TtW5Ic3PrMS7J9zzH7J9lnEnPtn6SSPLKn7Z2tbetJjLdnki+MsO/7STaY6JgTmaMfkrwwyfuW01iHJ7m25+d73r0Y68NJnrU84pIkSZJ0760yn9NZVX8E5kJXFAK3VNWnh3SbB9wCTLpo6bEYeBnw0fZ6N+DK5TDu3VTV85b3mMtLktWqatlw+6rqe8D3luN0+1bVcfd2kKr60PIIZiSj5USSJEnSPa0yK50jaaubJyeZAywA3tlWy542pN+mSX6Y5JIk5yTZfIyhvwO8qB37COBm4A89430pycVJrkhyQE/7NknOS3JZkguTrNd2PbjNf02ST/X0vy7JRknmJPmfJF9tY56aZO1Jxt573vNbHAuTfDnJamPEf12SDyX5CbB7e31AkkuTLB6cu3dlta1Ufr6d9y+T7Nba75Pk4DbHyW1Vd7cJxL5/kq8lObON+7aeff+R5KokP0py9OCKdotlcP6RYl+njXtRkp8lGfw5r5bkwNa+KMmbWvu8JGck+Sbdf0ZIkiRJGqdVZqVzLFV1XZJD6FkBTfLMni5fARZU1TVJngwcDDxjlCH/DPwqyRZ0xecxwGt79n+gqm5sRdxpSZ4AXNX67VFVFyW5H/D31n8usBVwG3B1koOq6ldD5nwU8PKqekOSbwMvAY6cROy0838MsAfw1Kpamu4y5FcCXx8u/qpa1A69tap2aGN8Arihqp6Y5C3APsDrh5luNrADsDndCuhxwIuBOcDjgQcC/wN8bYRwD0zywbZ9RVW9sm1vDuwErNfy9iVgy5abreh+hy8FLhlh3OFi/wBwelXtle7S5guT/Ljl5uaq2ibJmsC5SU5t42wLbFFV144wDwBLly5lYGBg0vtnCvPQMQ8d87ByWFl+Bv4+mINB5qHTzzzMnj27L+NKQ02bonM0SdYFtgeOTTLYvOY4Dv0W3SW2/wI8k7sXnS9N8ka6HM4GHgsUMFBVFwFU1Z/b/ACnVdXN7fWVwCbA0KLz2qpa2LYvAebci9hpMT8JuKgduzbw+1HiHyw6jxkyzgk9Mb14hLm+U1V3AlcmeVBr2wE4trX/NskZo8Q60uW1/11VtwG3Jfk98KA27ner6u8ASU4aZdzhYt8ZeGHuut93LeBhrf0JPaux69P9R8DtwIVjFZwAs2bNGvUNfGBgwDd4zMMg89AxD50lUzz/yvIz8PfBHAwyDx3zoOlgRhSddJcR/6mq5k7wuJOAA4GLq+rPg0VfkofTrZptU1U3JTmcrnAJXeE5nNt6tpcxfO6H9ln7XsROi+eIqnr/3RpHjn/QX0eIa6S4h8aeId/vjeHyNpFxh4s9wEuq6urejul+wHtX1SlD2udxz5xIkiRJGodV/p7OIf5Cdxnm3bQVx2uT7A5dcZFky7EGaytp7wU+NmTX/eiKkJvbqt5zW/tVdPdubtPmWS/JvSrsJxt7cxqwW5IHtmM3TLLJKPEvbz8BXtLu7XwQ3YOelte4/5pkrbYS/PwJHn8KsHcrMkmyVU/7m5PMau2bJVlnOcUsSZIkzUjTreg8Cdg1wzxIiO5+vdcluQy4gvaQoLFU1beq6tIhbZcBP2vjfA04t7XfTncP5UFtnh9x9xXEyRpv7Hsm+fXgF919qR8ETk2yqMUze6T4++B44NfA5cCXgQvoHsg0nANz10emLEyyxkiDtsuXvwdcRnf57MWjjDucjwCzgEVJLm+vAQ6le0Lxpa39y8ycqwEkSZKkvkjVSFeDSvdeknWr6pYkDwAupHuo0W+X47j3Bc4G3jj0PwemwpFHHlnz588fcb/3ZXTMQ8c8dMxDZ8mB+03p/Jvse8DYnVYAfx/MwSDz0OlzHpbHrVDSmFzFUb+d3J4QuwbwkeVRcDZfSfJYupXkI1aGglOSJEnSPc3oojPJB4DdhzQfW1VD7+HUJFXVvD6N+4p+jCtJkiRp+ZrRRWcrLi0wJUmSJKlPZnTRKUnSymKN+Qu8f02SNC1Nt6fXSpIkSZJWIhadkiRJkqS+seiUJEmSJPWNRackSZIkqW98kJAkScNYcuB+K3S+NeYvWKHzSZK0orjSKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHo1LSQ5Jae7ecluSbJw6YyJkmSJEkWnZpmkjwTOAh4TlX93ziPWa2/UUmSJEkzl0Wnpo0kTwO+Cjy/qn7R2uYnuTDJwiRfHiwwk9yS5MNJLgC2S/KhJBcluTzJV5Kk9XtbkiuTLEryrSk7OUmSJGkVtfpUByAtJ2sC3wXmVdVVAEkeA+wBPLWqliY5GHgl8HVgHeDyqvpQ63tlVX24bX8DeAFwEvA+4OFVdVuSDcYKYunSpQwMDEx6/0xhHjrmoWMeOuahYx7MwSDz0OlnHmbPnt2XcaWhLDo1XSwFzgNeB7y9tT0TeBJwUVu4XBv4fdu3DDi+5/idkrwHuC+wIXAFXdG5CDgqyXeA74wVxKxZs0Z9Ax8YGPANHvMwyDx0VtY8LFnB8431/jFTrKy/DyuSOeiYh4550HTg5bWaLu4EXgpsk+TfW1uAI6pqbvt6dFXt3/bdWlXLAJKsBRwM7FZVj6e7RHet1u/5wBfpitdLkvgfNZIkSdIEWHRq2qiqv9FdFvvKJK8DTgN2S/JAgCQbJtlkmEMHC8wbkqwL7Nb63wd4aFWdAbwH2ABYt79nIUmSJE0vrtpoWqmqG5M8BzgbeAfwQeDUVkAuBf6NIVfNVdWfknwVWAxcB1zUdq0GHJlkfbpV089W1Z9WwGlIkiRJ04ZFp6aFqlq3Z/tXwMN7dh8zWv/2+oN0BepQOyyvGCVJkqSZyMtrJUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+sYHCUmSNIxN9j1ghc43MDCwQueTJGlFcaVTkiRJktQ3Fp2SJEmSpL6x6JQkSZIk9Y33dEqSNIwlB+63QudbY/6CFTqfJEkriiudkiRJkqS+seiUJEmSJPWNRackSZIkqW8sOiVJkiRJfWPRKUmSJEnqG4tOSZIkSVLfWHROkSS39GncDZK8pef1g5Mct5znuC7J4iSXJTk1yT/1zpNkbpLn9fSfl2T7McbcM8kXlmec49Fi/1aSXyS5Msn3k2zWs/+dSW5Nsv6Kjk2SJEmaDiw6p58NgH8UnVV1fVXt1od5dqqqLYGLgX8fMs9c4Hk9fecBoxad91aSCX/mbJIAJwJnVtWmVfVY4N+BB/V0ezlwEbDrcglUkiRJmmEsOlcibYXw/CSLkpyY5P6t/ZFJftxWFi9NsmmSdZOc1l4vTvKiNswngE2TLExyYJI5SS5v46yV5LDW/2dJdmrteyY5IckPk1yT5FMTCPts4JGD8yRZA/gwsEeL4b3AAuCd7fXTkuze+l6W5OyesR7aYrg6yX4ttn/E317vk2T/tn1mko8nOQt4e5JtWu5+2s79cka3E7C0qg4ZbKiqhVV1Tht/U2Bd4IN0xackSZKkCZrw6pD66uvA3lV1VpIPA/sB7wCOAj5RVScmWYvuPwtuB3atqj8n2Qg4P8n3gPcBW1TVXOiKtp7x/w2gqh6fZHPg1J5LSecCWwG3AVcnOaiqfjWOmF8ALB58UVW3J/kQsHVVvbXFsDZwS1V9ur1eDPxLVf0myQY9Y20LbAH8DbgoyX8DN4wx/wZVtWMb93LgjVV1XpJPjCP2LYBLRtn/cuBo4Bzg0UkeWFW/H23ApUuXMjAwMOn9M4V56JiHjnnomIeOeTAHg8xDp595mD17dl/GlYay6FxJtHsGN6iqs1rTEcCxSdYDHlJVJwJU1a2t/yzg40meDtwJPIS7XxY6nB2Ag9o4VyVZAgwWnadV1c1t7CuBTYDRis4zkiwDFtGtBG4wgdM9Fzg8ybeBE3raf1RVf2wxnNDi/c4YYx3T+m8ArFdV57X2b9IVxPfGy+gK+ztbPLsDXxztgFmzZo36Bj4wMOAbPOZhkHnorKx5WLKC5xvr/WOmWFl/H1Ykc9AxDx3zoOnAonPllxHaXwlsDDypqpYmuQ5Ya5JjQbfCOWgZY/9u7FRV/1iFHLJiOaqqWpDkycDzgYVJ5g7uGtoVuIO7XwY+9Bz/OhjCeOfvcQUw7P2uSZ4APAr4UXfrJ2sAv2SMolOSJEnS3XlP50qirTLelORprelVwFlV9Wfg10l2AUiyZpL7AusDv28F5050K5MAfwHWG2Gas+mKVdpltQ8Dru7D6QyN4W6vk2xaVRdU1YfoLp99aNv17CQbtstxd6FbEf0d8MAkD0iyJiOsXlbVTcBfkjylNb2sZ76HJDltmMNOB9ZM8oaevtsk2ZHu0tr9q2pO+3ow8JAkmwwzjiRJkqQRWHROnfsm+XXP17uA1wAHJllEd4/lh1vfVwFva+3nAf9Ed5/n1kkupiskrwJol6ee2x7Uc+CQOQ8GVmv3VB4D7FlVt7H8nQE8tj04aA/gJGDXwQcJtXNc3O7BPBu4rB33E+AbwELg+Kq6uKqWtjxcAJw8eJ4jeB3wlSQ/pVv5vLm1z6ZbMb2bqiq6p9I+O91HplwB7A9cT1e0njjkkBPpKWYlSZIkjc3La6dIVY1U8D9laENVXQM8Y5i+240w9iuGNG3R2m8F9hym/+HA4T2vR70XsqrmDNN2Xc88NwLbDOnyhJ7tc4YZ9m4xDBn788Dnh2mfN6Tpiqp6AkCS99F9nAt0OR32stiquh546TC7Hj5M33cNN4YkSZKkkVl0ajp5fpL30/1eL6EV2FX1hakMSpIkSZrJLDo1oiQXAGsOaX5VVS0erv9Uq6pjaE+zlSRJkrRysOjUiKrqyVMdgyRJkqRVm0WnJEnD2GTfA1bofP368HdJkqaaT6+VJEmSJPWNRackSZIkqW8sOiVJkiRJfWPRKUmSJEnqGx8kJEnSMJYcuN8KnW+N+QtW6HySJK0ornRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvVoqiM8myJAuTXJ7k2CT3ncCxWyf5/CTnfcdE5popkvx7n8adk+QVPa/3TPKFezHemMcn2T/JPpOdQ5IkSdK9s1IUncDfq2puVW0B3A7c7bnxSVYb6cCquriq3jbJed8BWHTeU1+KTmAO8IqxOkmSJEmaPlaWorPXOcAjk8xLckaSbwKLk6yV5LAki5P8LMlOAK3fyW17nSRfS3JR6/Oi1r5akk+3Yxcl2TvJ24AHA2ckOWNoEEmuS/LxJD9NcnGSJyY5JckvkixofdZNclqSS9vYg/PNSfI/Sb6a5IokpyZZu+17Q4vvsiTHD660Jtk0yflt34eT3NITy76tfVGSA3rmuCrJoW2F+Kgkz0pybpJrkmw7Rk72THJCkh+2/p9q7Z8A1m4rz0cNk5dbknwyySVJfpxk2yRnJvllkhf25PvAnpjf1A7/BPC0NvY7W9uDh8bQxnh5y+nlST7Z0/7aJD9Pchbw1J72TdrPYlH7/rBhYp/bcrwoyYlJ7t/at2ltP21xX97az0kyt+f4c5M8Yei4kiRJkka2+lQH0CvJ6sBzgR+2pm2BLarq2iTvBqiqxyfZHDg1yWZDhvgAcHpV7ZVkA+DCJD8GXg08HNiqqu5IsmFV3ZjkXcBOVXXDCCH9qqq2S/JZ4HC6Imct4ArgEOBWYNeq+nOSjYDzk3yvHfso4OVV9YYk3wZeAhwJnFBVX23n+1HgdcBBwOeAz1XV0YNFbeuzcxtrWyDA95I8Hfg/4JHA7sAbgYvoVhF3AF5It1q5yyg5AZgLbAXcBlyd5KCqel+St1bV3BFysg5wZlW9N8mJwEeBZwOPBY4AvtfO6eaq2ibJmsC5SU4F3gfsU1UvaOe253AxAMuATwJPAm6i+1nvAlwAHNDabwbOAH7W4voC8PWqOiLJXsDn2/n3+jqwd1WdleTDwH50q92HAW+sqvNa0T3oUGBP4B3td23Nqlo0Ql4AWLp0KQMDA5PeP1OYh4556JiHjnnomAdzMMg8dPqZh9mzZ/dlXGmolaXoXDvJwrZ9DvD/AdsDF1bVta19B7rijKq6KskSYGjRuTPwwtx1D99awMOAZwGHVNUd7fgbxxnXYAG5GFi3qv4C/CXJra2A+yvw8VYE3gk8BHhQO+baqho8p0voLi0F2KIVmxsA6wKntPbtuKtI+ibw6Z5z2pm7iqt16YrQ/2tzLAZIcgVwWlVVksU9842UE1r/m9vxVwKbAL8aIye3c9d/CiwGbquqpcPM+YQku7XX67eYbx9mvOFieABdYfuH1n4U8PTWv7f9GO76HdgOeHHb/gbwj1XT1nd9YIOqOqs1HQEc236O61XVea39m8AL2vaxwH8k2RfYi+4/HkY1a9asUd/ABwYGfIPHPAwyD52VNQ9LVvB8Y71/zBQr6+/DimQOOuahYx40HawsReffh66sJYGuqPtH0zjGCfCSqrp6yFgBahJx3da+39mzPfh6deCVwMbAk1rhdR1dUceQ/suAtdv24cAuVXVZW+mbN0YMAf6zqr58t8ZkzjAx9cY7+LMdKSdPHibG8fw+LK2qwVz+Y86qurOtVA/OuXdVndJ7YJJ5w4w3XAyj/azH+3Mcb78R56qqvyX5EfAi4KXA1uMcU5IkSVKzMt7TOZKz6Yo82qWODwOuHtLnFGDvVmSSZKvWfiqwYLAoSrJha/8LsN69iGl94Pet4NyJbpVuLOsBA0lmDZ5Pcz7dJbgAL+tpPwXYK8m6LfaHJHngBGIcKSejWdrim6xTgDcPjpFksyTrMP58XwDsmGSjdA+RejlwVmufl+QBbezde445j7vy9krgJ70DttXUm5I8rTW9Cjirqm6iW71+SmvvzT10l9h+HrhoAivkkiRJkppVqeg8GFitXcZ5DLBnVQ2ukg2uan0EmAUsag+D+UhrP5TuctRFSS7jrieofgX4QYZ5kNA4HQVsneRiukLnqnEc8x90xdOPhvR/B/CuJBcCs+nuWaSqTqW75POn7dyPY2KF8kg5Gc1XWv97PEhonA4FrgQubXN+mW4FcxFwR7qHKL1zpIOragB4P909m5cBl1bVd1v7/sBPgR8Dl/Yc9jbgtUkW0RWUbx9m6NcAB7Y+c4EPt/bXAV9J8lO6lc+be2K5BPgz3X2fkiRJkiYod10puWpK8hLghVX1mqmO5d5I9xTbv7d7Ml9G9xCiF011XDNBknWr6pa2/T5gdlW9vb1+MHAmsHlV3TnWWEceeWTNnz9/xP3el9ExDx3z0FlZ87DkwP1W6HxrzF+wUuZhRVtZfx9WJHPQMQ+dPudhPLevSffaynJP56Sk+4iOj9E95GVV9yTgC+0y2D8xPc5pVfH8JO+n+3tYQvfEWpK8mu73613jKTglSZIk3dMqXXRW1fe46wmzq7SqOgfYcqrjmImq6hi6S7aHtn+d7mNWJEmSJE3SqnRPpyRJkiRpFWPRKUmSJEnqm1X68lpJkvplk30PWKHzDQwMrND5JElaUVzplCRJkiT1jUWnJEmSJKlvLDolSZIkSX1j0SlJkiRJ6hsfJCRJ0jCWHLjfCp1vjfkLVuh8kiStKK50SpIkSZL6xqJTkiRJktQ3Fp2SJEmSpL6x6JQkSZIk9Y1FpyRJkiSpbyw6JUmSJEl9Y9GpcUnyT0m+leQXSa5M8v0km011XJOR5Loki5MsbN9f1LNvWWu/LMmlSbZv7XOSXD51UUuSJEmrJj+nU2NKEuBE4Iiqellrmws8CPj5FIZ2b+xUVTckeTRwKvDd1v73qpoLkORfgP8EdpyaECVJkqRVn0WnxmMnYGlVHTLYUFUL0zkQeC5QwEer6pgk84ADgN8Bc4ETgMXA24G1gV2q6hdJDgduBR5HV8C+q6pOTjIH+AawTpvurVV1Xht3f+AGYAvgEmA+8IzWZ1eAJM8G3lxVLx7Hud0PuGkS+4a1dOlSBgYGJr1/pjAPHfPQMQ8d89AxD+ZgkHno9DMPs2fP7su40lAWnRqPwQJvqBfTFZVbAhsBFyU5u+3bEngMcCPwS+DQqto2yduBvYF3tH5z6FYSNwXOSPJI4PfAs6vq1iSPAo4Gtm79t6IrUq8HzgWeCpwOfDHJxlX1B+C1wGFjnNMZbQX3EcBLe9rXTrIQWAuYTVfQjtusWbNGfQMfGBjwDR7zMMg8dFbWPCxZwfON9f4xU6ysvw8rkjnomIeOedB04D2dujd2AI6uqmVV9TvgLGCbtu+iqhqoqtuAX9BdwgrdiuecnjG+XVV3VtU1dMXp5sAs4KtJFgPHAo/t6X9hVf26qu4EFgJzqqroVkbnJ9kA2A74wRix71RVWwCPB76QZN3W/veqmltVmwPPAb7eilNJkiRJk+BKp8bjCmC3YdpHK8Zu69m+s+f1ndz9966GHFfAO+kuzd2S7j9Gbh1h3GU9Yx0GnNT6HltVd4wS212TdZf5/o6usL1wyL6fJtkI2Hg8Y0mSJEm6J1c6NR6nA2smecNgQ5Jt6O533CPJakk2Bp7OkMJtHHZPcp8km9Jd6no1sD4w0FYzXwWsNtYgVXU93SW3HwQOH+/kSR4IPJxhrqRLsnmb+4/jHU+SJEnS3bnSqTFVVSXZFfivJO+jW028ju6+zHWBy+hWKN9TVb9txdp4XU13We6DgAXtPs6DgeOT7A6cAfx1nGMdBWxcVVeOo+8ZSZbRXcr7vnZ5MNx1Tyd0K7mvqaplXmErSZIkTY5Fp8alrSS+dJhd+7av3r5nAmf2vJ430j7g3Kp655DjrwGe0NP0/hHGfeuQWHYAvjraebTj5oyyb9hV1aq6ju6BSpIkSZImwKJT00KSS+hWRN891bFIkiRJuotFp6ZMVe25HMd60tC2JBcAaw5pflVVLV5e80qSJEkanUWnpq2qevJUxyBJkiTNdBadkiQNY5N9D1ih8w0MDKzQ+SRJWlH8yBRJkiRJUt9YdEqSJEmS+saiU5IkSZLUN97TKUmaMZYcuN9UhzCiNeYvmOoQJEnqC1c6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+saiU5IkSZLUNxad00CSDyS5IsmiJAuTPLm1vyPJfcdx/N36Jfl+kg2WV/9RxtkzyRcmetwE5zgzydaTOO7QJI/tR0ySJEnSTGLRuYpLsh3wAuCJVfUE4FnAr9rudwBjFp1D+1XV86rqT8ux/yqnql5fVVdOdRySJEnSqs6ic9U3G7ihqm4DqKobqur6JG8DHgyckeQMgCRfSnJxWxU9oLUN1++6JBslWSfJfye5LMnlSfYYrX/bfnVbcb0syTda278muSDJz5L8OMmDRjuhJNsmOa/1Py/Jo1v7nklOSPLDJNck+VTPMfc4tyFjvi7JZ3tevyHJZ4Y7x7b/zCRbJ1ktyeFt3+Ik75zUT0mSJEmaoVaf6gB0r50KfCjJz4EfA8dU1VlV9fkk7wJ2qqobWt8PVNWNSVYDTkvyhBH6DXoOcH1VPR8gyfpVdfNI/ZM8DvgA8NSquiHJhm3XT4CnVFUleT3wHuDdo5zTVcDTq+qOJM8CPg68pO2bC2wF3AZcneSgqvrVCOe2qGfMbwGLkrynqpYCrwXeNNw5DollLvCQqtqi7d9glLglSZIkDWHRuYqrqluSPAl4GrATcEyS91XV4cN0f2mSN9L93GcDjwUWDdNv0GLg00k+CZxcVeeMEc4zgOMGi9GqurG1/3OLazawBnDtGOOsDxyR5FFAAbN69p1WVTcDJLkS2ITucuJRz62q/prkdOAFSf4HmFVVi5PcNsY5/hJ4RJKDgP+mK/JHtHTpUgYGBia9f6YwDx3z0DEPHfPQMQ/mYJB56PQzD7Nnz+7LuNJQFp3TQFUtA84EzkyyGHgNcHhvnyQPB/YBtqmqm5IcDqw1xrg/bwXt84D/THJqVX14lENCVyQOdRDwmar6XpJ5wP5jnNJHgDOqatckc9q5DbqtZ3sZsPoEzu1Q4N/pVlIPG885tvG2BP4F+DfgpcBeIwU+a9asUd/ABwYGfIPHPAwyD50VmYclK2SWyRnr/WOm8O/CHAwyDx3zoOnAezpXcUke3VYEB83lrn9X/QVYr23fD/grcHO7p/K5Pcf09usd+8HA36rqSODTwBNH6w+cRrfi+IB2/ODltesDv2nbrxnHafX233Mc/Uc7t3+oqguAhwKvAI5uMY50jrT9GwH3qarjgf8Yul+SJEnS6FzpXPWtCxzU7jW8A/hf4I1t31eAHyQZqKqdkvwMuILuktFze8a4W7+e9scDBya5E1gKvHm0/lV1RZKPAWclWQb8jK5o3B84NslvgPOBh49xTp+iu7z2XcDpYyWgqi4b5dyG+jYwt6puGuMcBz0EOCzJ4H/QvH+seCRJkiTdJVXDXQ0pTU9JTgY+W1Wn9WP8I488subPnz/ifi+R6ZiHjnnorNDLaw/cb4XMMxlrzF/g7wP+XYA5GGQeOn3OQ/o1sNTLy2s1IyTZoD3h9+/9KjglSZIk3ZOX12pGqKo/AZtNdRySJEnSTONKpyRJkiSpbyw6JUmSJEl94+W1kqQZY5N9D5jqEEbUrw9/lyRpqrnSKUmSJEnqG4tOSZIkSVLfWHRKkiRJkvrGolOSJEmS1Dc+SEiSNGMsOXC/qQ5hRGvMXzDVIUiS1BeudEqSJEmS+saiU5IkSZLUNxadkiRJkqS+seiUJEmSJPWNRackSZIkqW8sOjVhST6b5B09r09JcmjP6/+X5F3DHLcgyavb9p5JHtyz79Akj+1jzNcl2WiY9vPa9zlJLm/b85Kc3K9YJEmSpJnEolOTcR6wPUCS+wAbAY/r2b89cG7vAUlWr6pDqurrrWlP4B9FZ1W9vqqu7GfQw6mq7Vf0nJIkSdJMYtGpyTiXVnTSFZuXA39Jcv8kawKPAX6W5MwkH09yFvD2JPsn2SfJbsDWwFFJFiZZu/XdGiDJLUk+luSyJOcneVBr37S9vijJh5PcMjSwJOsk+e927OVJ9hiyf+0kP0zyhsG5RjvRJDu2GBcm+VmS9e5V5iRJkqQZZvWpDkCrnqq6PskdSR5GV3z+FHgIsB1wM7Coqm5PArBBVe0IkGT/dvxxSd4K7FNVF7d9vVOsA5xfVR9I8ingDcBHgc8Bn6uqo5OM9CnqzwGur6rnt3HX79m3LvAt4Os9K65j2Qf4t6o6N8m6wK2jdV66dCkDAwOT3j9TmIeOeeiYh4556JgHczDIPHT6mYfZs2f3ZVxpKItOTdbgauf2wGfois7t6YrO83r6HTOJsW8HBu+pvAR4dtveDtilbX8T+PQwxy4GPp3kk8DJVXVOz77vAp+qqqMmEMu5wGeSHAWcUFW/Hq3zrFmzRn0DHxgY8A0e8zDIPHRWZB6WrJBZJmes94+Zwr8LczDIPHTMg6YDL6/VZA3e1/l4ustrz6crCofez/nXSYy9tKqqbS9jAv85UlU/B55EV3z+Z5IP9ew+F3huhiyrjjHeJ4DXA2sD5yfZfLzHSpIkSbLo1OSdC7wAuLGqllXVjcAGdIXnT8dx/F+Aid4feT7wkrb9suE6tCfi/q2qjqRbCX1iz+4PAX8EDh7vhEk2rarFVfVJ4GLAolOSJEmaAItOTdZiuqfWnj+k7eaqumEcxx8OHDL4IKFxzvkO4F1JLgRm013KO9TjgQuTLAQ+QHcv6NAx1mr3io5rzvZAosuAvwM/GOdxkiRJkvCeTk1SVS0D7jekbc8hr+cNeb1/z/bxwPE9u+f17Fu3Z/s44Lj28jfAU6qqkryMbuVxaFynAKcM0z6n5+Vrh85VVdcBW7TtM4Ez2/beQ8eSJEmSNH4WnVqVPAn4Qrsn80/AXlMbjiRJkqSxWHRqldGeRLvlVMchSZIkafy8p1OSJEmS1DcWnZIkSZKkvvHyWknSjLHJvgdMdQgjGhgYmOoQJEnqC1c6JUmSJEl9Y9EpSZIkSeobi05JkiRJUt9YdEqSJEmS+sYHCUmSpp0lB+431SFM2BrzF0x1CJIk9YUrnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvLDolSZIkSX1j0SlJkiRJ6huLTi0XSZYlWZjksiSXJtl+kuMcnmS3YdqvS7LRvY903HEcmuSxK2o+SZIkabryI1O0vPy9quYCJPkX4D+BHac0onuhql4/1TFIkiRJ04ErneqH+wE3ASRZN8lpbfVzcZIXDXZK8uoki9rq6DeGDpLkI23lc/D3dN8kF7avR7Y+m7TxF7XvD2vthyf5fJLzkvyyd/U0yb5JLmrHHDDcCSQ5M8nWSVZrY13e4n/n8kuTJEmSNP250qnlZe0kC4G1gNnAM1r7rcCuVfXndnns+Um+BzwW+ADw1Kq6IcmGvYMl+RSwPvDaqqokAH+uqm2TvBr4L+AFwBeAr1fVEUn2Aj4P7NKGmQ3sAGwOfA84LsnOwKOAbYEA30vy9Ko6e4Tzmgs8pKq2aHFtMFoSli5dysDAwKT3zxTmoWMeOuahYx465sEcDDIPnX7mYfbs2X0ZVxrKolPLS+/ltdsBX0+yBV1h9/EkTwfuBB4CPIiuKD2uqm4AqKobe8b6D+CCqnrjkDmO7vn+2ba9HfDitv0N4FM9/b9TVXcCVyZ5UGvbuX39rL1el64IHano/CXwiCQHAf8NnDpaEmbNmjXqG/jAwIBv8JiHQeah0488LFmuo60YY71/zBT+XZiDQeahYx40HVh0armrqp+2Vc2Ngee170+qqqVJrqNbDQ1QIwxxEfCkJBsOKUZrhG1GaL+tZzs93/+zqr48znO5KcmWwL8A/wa8FNhrPMdKkiRJ8p5O9UGSzYHVgD/SXSL7+1Zw7gRs0rqdBrw0yQPaMb2X1/4Q+ATw30nW62nfo+f7T9v2ecDL2vYrgZ+MEd4pwF5J1m3zPiTJA0c5l42A+1TV8XQrsE8cY3xJkiRJPVzp1PIyeE8ndKuJr6mqZUmOAk5KcjGwELgKoKquSPIx4Kwky+gud91zcLCqOrYVnN9L8rzWvGaSC+j+s+Tlre1twNeS7Av8AXjtaEFW1alJHgP8tN0negswH/h9ku8Dr6+q6we7010OfFjPw4zeP8G8SJIkSTOaRaeWi6pabYT2G+juuxxu3xHAEUPa9uzZ/hrwtfZyTvt+wJD+13HXQ4uGHae9Xrdn+3PA54Y55nk9Lx8A3FhV1+LqpiRJkjRpXl4rDZHkR8DiVnBKkiRJuhdc6ZSGqKpnT3UMkiRJ0nThSqckSZIkqW9c6ZQkTTub7HvA2J1WMv368HdJkqaaK52SJEmSpL6x6JQkSZIk9Y1FpyRJkiSpbyw6JUmSJEl944OEJEnTzpID95vqECZsjfkLpjoESZL6wpVOSZIkSVLfWHRKkiRJkvrGolOSJEmS1DcWnZIkSZKkvrHolCRJkiT1jUWnJEmSJKlvLDqBJP+U5FtJfpHkyiTfT7LZVMc1WUmuS7JRz+t5SU5eDuN+P8kG93acScx7ZpKrkyxsX8e19v2T7DOJ8TZI8pYx+pw32XglSZIk3WXGf05nkgAnAkdU1cta21zgQcDPpzC0KdNykqq6c8jr501hWK+sqouX01gbAG8BDh66I8lqVbWsqrZfTnNJkiRJM5ornbATsLSqDhlsqKqFVXVOOgcmuTzJ4iR7wD9WDs9K8u0kP0/yiSSvTHJh67dp63d4kkOSnNP6vaC1z2ltl7av7XvGPTPJcUmuSnJUi+GZSU4cjC/Js5OcMJmTHbo62M5tTvv6nyQHA5cCTxvy+qG9K6hJXp1kUZLLknyjtf1rkguS/CzJj5M8qGfOr7Vz+2WSt/XMP7/lbWGSLydZbZLntWmSHya5pOV289b+oCQntjgva7n+BLBpm/PAlvczknwTWNyOu6Vn7Pe0n+tlST4xmfgkSZKkmWrGr3QCWwCXjLDvxcBcYEtgI+CiJGe3fVsCjwFuBH4JHFpV2yZ5O7A38I7Wbw6wI7ApcEaSRwK/B55dVbcmeRRwNLB1678V8DjgeuBc4KnA6cAXk2xcVX8AXgscNsZ5nZFkWdteF7hqjP4AjwZeW1VvSTKn9zVAt+AJSR4HfAB4alXdkGTDdvxPgKdUVSV5PfAe4N1t3+Z0Bf56wNVJvgQ8EtijjbO0FbivBL4+TGxHJfl72/5RVe07ZP9XgAVVdU2SJ9OtYj4D+DxwVlXt2gradYH3AVtU1dx2PvOAbVvbtb2DJnkusAvw5Kr6W8+5Dmvp0qUMDAxMev9MYR465qFjHjrmoWMezMEg89DpZx5mz57dl3GloSw6R7cDcHRVLQN+l+QsYBvgz8BFVTUAkOQXwKntmMV0xdWgb7fLVK9J8ku64uta4AvtMt5lQO/9oxdW1a/buAuBOVX1k7aaOD/JYcB2wKvHiH2nqrqhjTMPGM+9j0uq6vxRXg96BnDc4PhVdWNr/2fgmCSzgTXaeQ7676q6Dbgtye/pLl9+JvAkumIeYG26gnw4I15em2RdYHvg2MHCGFizJ9ZXtziXATcnuf8ww1w4tOBsngUcVlV/G3Kuw5o1a9aob+ADAwO+wWMeBpmHTj/ysGS5jrZijPX+MVP4d2EOBpmHjnnQdGDRCVcAu42wLyO0A9zWs31nz+s7uXtea8hxBbwT+B3daul9gFtHGHdZz1iHASe1vsdW1R2jxDaaO7j7ZdVr9Wz/dUjfoa8HhXueF8BBwGeq6nut0N2/Z99w5xW6e2nfP2bUo7sP8KfBlctJmui5SpIkSRoH7+nsLl1dM8kbBhuSbJNkR+BsYI8kqyXZGHg6cOEEx989yX3afZ6PAK4G1gcG2groq4Ax72OsquvpLrn9IHD4BGPodR3wRIAkTwQePokxTgNemuQBbZzBS07XB37Ttl8zznF2S/LAwXGSbDLRYKrqz8C1SXZv4yTJlj1zvLm1r5bkfsBf6C7zHY9Tgb2S3HcwxonGJ0mSJM1kM77orKoCdgWene4jU66gW6G7nu6ptouAy+iK0/dU1W8nOMXVwFnAD+juObyV7n7D1yQ5n+7S2pFW2YY6CvhVVV05wRh6HQ9s2C7dfTOTeEJvVV0BfAw4K8llwGfarv3pLnE9B7hhHONc+f+zd+9xdlX1/f9fbyAgigUVxNTfV1IQikAlyk0EJahYbW0VRVEJilYstiqiYrVSAautLbZab8WKAgIioOCFakXlJvdrIIAicklrGUEERazBkHx+f+x19DDMNZnDJDOv5+MxD85Ze+21P/szZ/aDT9ba+9AV0WcluRb4NjDa+pGT8ruvTPnOCNv3A/6ixXM98OLWfjCwZ5LFdPfubltVPwMubA9ROmqcGP8L+BpwRcvZpL+iRZIkSZrN0tVcGoQkxwFnVtWXpmi8TwBXV9Vnp2I8Tb0TTzyxFi5cOOp278vomIeOeegM5J7Oow6f0vEeDusuPMjPA/5dgDnoMQ+dAedhrFvJpCnjPZ1riCRX0s2IvmO8vpIkSZK0urDoHKCqOmAKx9pheFuSS/ndU1p79q+qxVN1XEmSJElaFRada7Cq2mW6Y5AkSZKksVh0SpJmnM0OPXK6Q5i0QX35uyRJ023WP71WkiRJkjQ4Fp2SJEmSpIGx6JQkSZIkDYxFpyRJkiRpYHyQkCRpjbTkqMOnO4Qpte7Cg6Y7BEmSBsKZTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDYxFpyRJkiRpYCw6JyHJE5J8McnNSW5I8o0kW013XCsryQZJPt3O5/ok5yfZZZx9bkuycXu9PMmiJNclOS3JI0fZ56KVjG9eklevxH69uK5JclWSZ67M8dtY5ybZcWX3lyRJkmY7i84JShLgDODcqtqiqrYB/hbYdHojWyXHAHcDW1bVtsABwMaT2P/XVTW/qrYDfgM86EvmkqwNUFUrW/TNAyZddPbFtT3wHuAfV/L4kiRJklbROtMdwBpkT2BZVR3da6iqRfDbgvSfgRcCBXygqk5JsgA4ErgDmA+cDiwGDgbWB15SVTcnOQ5YCmxLV8S+varOTDIPOAF4VDvkm6vqojbuEcBdwHbAlcBC4Dmtz94trr2AN1XVS4efTJItgF2A/apqRTufW4Bb2vavAP8PeATwb1X1H+Pk53vAU1tshwND7Zy3SXJfVW2Q5BTg+Kr6RjvGccDXW/wPOU/gQ8BTkiwCjgc+1toWAOsBn6yqT48T1+8B97TjbQB8FXgMMAc4rKq+2vL8TeAC4JnA/wIvrqpf9+VrLeBY4H+q6rDRDrZs2TKGhoZGDWa87bOFeeiYh4556JiHjnkwBz3moTPIPMydO3cg40rDWXROXK+4G8lL6Qqs7elmCi9Pcn7btj3wFLoZxVuAY6pq5yQHA28B3tb6zQP2ALYAzknyZOBOYK+qWppkS+BkoLfU82l0RertwIXAbsDZwCeTbFJVPwVeR1cojWRbYFFVLR9l++ur6u4k67fz+XJV/WykjknWoSu4/6s17QxsV1W3Duv6RWBf4BtJ1gWeC7wJyCjn+W7gnVX1onacNwK/qKqdkqwHXJjkrBGOs34rVB8BzKUrxqEr7PeuqnvbEuFLknytbdsSeFVVHZjkVOBlwIlt2zrAScB1VfXBUfIFwJw5c8a8gA8NDXmBxzz0mIfOyuZhyQBimU7jXT9mC/8uzEGPeeiYB80ELq+dGrsDJ1fV8qq6AzgP2Kltu7yqhqrqfuBm4KzWvpiu0Ow5tapWVNVNdMXp1nSzcZ9Jshg4Ddimr/9lVfXjNku5CJhXVUU3Y7gwyUbArnQzeCvjrUmuAS6hm/HccoQ+veLuCuC/gc/2xTa8EKTF8pxWML4QOL/NJo51nv2eD7ymHfNS4HGjxNVbXrs18ALg8202OsA/JLkW+A7wRH63PPrW3sw13T8uzOsb79NMoOCUJEmS9FDOdE7c9cA+o2zLGPvd3/d6Rd/7FTw4/zVsvwIOoVuauz3dPxAsHWXc5X1jHUu3ZHUpcFpVPTBKXNcD2ydZq7e89rcn0y2RfR6wa1X9X5Jz6WYNh/t1Vc0fti/Ar0Y6YJvJPBf4Y7oZz5PbprHO80HDA2+pqm+Nsn2kY17cZjU3Af6k/XeHqlqW5La+8xqez/X73l8E7JnkX6pqtNgkSZIkjcCZzok7G1gvyYG9hiQ7JdkDOB/YN8naSTYBng1cNsnxX55krXav5ebAjcCGwFArCvcH1h5vkKq6nW7J7WHAcWP0u5luhvLINgtIki2TvLgd955WcG4NPGOS5zKWL9It+30W0CseRzvPXwKP7tv3W8Cbksxp8W6V5FGMocW/NvCzdpw7W8G5J7DZBGP+LPAN4LS2lFiSJEnSBFl0TlBburo3sFfvK0boHuZzO91Tba8FrqErTt9VVT+Z5CFupFuW+03goDaj9ingtUkuAbZilBnEEZxE98CbG8bp9wbgCcCP2tLWz7Tz+S9gnbYM9e/plthOlbPoivLvVNVvWtto53kt8ED76pND6J62ewNwVZLr6Ja9jlQErt++MmURcArw2nbv6knAjkmuAPYDfjDRoKvqX4GrgBPaQ4UkSZIkTUC6WkrTqT3F9cyq+tIUjfcJ4Oqq+uy4nTWlTjzxxFq4cOGo230YQMc8dMxDZ6UfJHTU4QOIZvqsu/AgPw/4dwHmoMc8dAach7FuEZOmjEsFZ5gkV9LNFL5jumORJEmSJIvO1UBVHTCFY+0wvC3JpXTfa9lv/6paPFXHlSRJkqSRWHTOAlW1y3THIEmSJGl2suiUJK2RNjv0yOkOYUoNDQ1NdwiSJA2ET+GUJEmSJA2MRackSZIkaWAsOiVJkiRJA+M9nZKkNdJM/J5OSZJmImc6JUmSJEkDY9EpSZIkSRoYi05JkiRJ0sBYdEqSJEmSBsaiU5IkSZI0MBadkiRJkqSBsejUGiHJE5J8McnNSW5I8o0kW013XJIkSZLGZtGp1V6SAGcA51bVFlW1DfC3wKbTG5kkSZKk8Vh0ak2wJ7Csqo7uNVTVIuCCJEcluS7J4iT7AiRZK8mnklyf5Mw2K7pP23ZbkiOTXNX22bq1PzbJV5Jcm+SSJE9t7XskWdR+rk7y6If97CVJkqQ12DrTHYA0AdsBV47Q/lJgPrA9sDFweZLzgd2AecAfAY8Hvg98rm+/u6rq6Un+Cngn8AbgSODqqnpJkucAn29jvxP466q6MMkGwNKxAl22bBlDQ0MrvX22MA8d89AxDx3z0DEP5qDHPHQGmYe5c+cOZFxpOItOrcl2B06uquXAHUnOA3Zq7adV1QrgJ0nOGbbf6e2/V9IVrr2xXgZQVWcneVySDYELgX9NchJwelX9eKyA5syZM+YFfGhoyAs85qHHPHRWNg9LBhDLdBrv+jFb+HdhDnrMQ8c8aCZwea3WBNcDO4zQnlH6j9bec3/773J+9w8vI+1TVfUhupnQ9YFLestxJUmSJE2MRafWBGcD6yU5sNeQZCfgHmDfJGsn2QR4NnAZcAHwsnZv56bAggkc43xgvzb2AroluPcm2aKqFlfVPwFXABadkiRJ0iS4vFarvaqqJHsDH03ybrr7Km8D3gZsAFwDFPCuqvpJki8DzwWuA34IXAr8YpzDHAEcm+Ra4P+A17b2tyXZk25W9Abgm1N3ZpIkSdLMZ9GpNUJV3Q68YoRNh7af/r4rkryzqu5L8ji62c/Fbdu8vn5X0GZBq+pu4MUjHPctU3QKkiRJ0qxk0amZ6swkGwHrAn9fVT+Z5ngkSZKkWcmiUzNSVS2Y7hgkSZIk+SAhSZIkSdIAOdMpSVojbXbokdMdwpQa1Je/S5I03ZzplCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGhgfJCRJWiMtOerw6Q5hSq278KDpDkGSpIFwplOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0TmDJVmeZFGSa5JcleSZqzDWuUl2HKfPi5Jc3Y53Q5K/XNnjPRySfDXJxRPoNy/Jqx+OmCRJkqSZxq9Mmdl+XVXzAZL8MfCPwB6DOFCSOcB/ADtX1Y+TrAfMm4Jx166q5as6zgjjbgQ8HbgvyR9U1a1jdJ8HvBr4wlTHIUmSJM10znTOHr8H3AOQZIMk322zn4uTvLi1z0vy/SSfSXJ9krOSrN8/SJK1khyf5APDxn803T9i/Aygqu6vqhvbPpsk+XKSy9vPbn1xHNtiuDbJy1r7fUnen+RSYNckC5Nc1mZtP51k7dbvBe0crmnns1aSm5Js0hfrj5JsPEI+XgZ8Hfgi8Mq+83tyku/0zQ5vAXwIeFY7/iGr8DuQJEmSZh2Lzplt/VYo/QA4Bvj71r4U2Luqng7sCfxLkrRtWwKfrKptgZ/TFWc96wAnAT+sqsP6D1RVdwNfA5YkOTnJfkl6n69/Az5SVTu18Y5p7X8H/KKq/qiqngqc3dofBVxXVbvQFbH7Aru1WdvlwH6tsPwM8LKq2h54eVWtAE4E9mvjPA+4pqruGiE3rwJObj+v6ms/qZ3/9sAzgSHg3cD3qmp+VX1khLEkSZIkjcLltTNb//LaXYHPJ9kOCPAPSZ4NrACeCGza9rm1qha111fy4CWynwZOraoPjnSwqnpDkj+iK/beCewFHNDeb/O7upbfS/Lo1v7Kvv3vaS+XA19ur58L7ABc3vZfH7gTeAZwfm9ZbCt6AT4HfBX4KPB64NjhcSbZFHgycEFVVZIHWl6WAE+sqjPamEtb/5FOd0TLli1jaGhopbfPFuahYx465qFjHjrmwRz0mIfOIPMwd+7cgYwrDWfROUtU1cVtmekmwJ+0/+5QVcuS3AY8onW9v2+35XRFXs9FwJ5J/qVXkI1wnMXA4iQnALfSFZ1rAbtW1a/7+7bZ1RphmKV993EGOL6q3jNs3z8fad+q+p8kdyR5DrALv5v17Lcv8Bjg1lZQ/h5d8fvPI53TZMyZM2fMC/jQ0JAXeMxDj3norGwelgwgluk03vVjtvDvwhz0mIeOedBM4PLaWSLJ1sDadMtVNwTubAXnnsBmExzms8A3gNOSPOgfLNr9mQv6mubzu/8nPAt4c1/f+aO0P2aEY34X2CfJ41ufxybZDLgY2CPJH/Ta+/Y5hm6Z7amjPIToVcALqmpeVc2jm0l9ZVXdC/w4yUvamOsleSTwS7p7ViVJkiRNkkXnzNa7p3MRcArw2laEnQTsmOQKupnAH0x0wKr6V+Aq4IS+ezahm5F8V5Ib2/GOpJvlBHhrO961SW4ADmrtHwAek+S6JNfQ3V86/Hg3AIcBZyW5Fvg2MLeqfgq8ETi97XtK325fAzZg5KW184AnAZf0HeNW4N4kuwD7A29tx7oIeAJwLfBAe7iQDxKSJEmSJsHltTNYVa09SvtdwK6j7LZdX78P971e0Pf68BHG/CXdst3RjrfvCO33Aa8doX2DYe9P4cFFZa/9m8A3Rzjk9nQPEHpIMV1Vt9Hdwzq8/el9b58zwpjPHaFNkiRJ0jgsOjWjJHk38CZGvpdTkiRJ0sPM5bWaUarqQ1W1WVVdMN2xSJIkSbLolCRJkiQNkEWnJEmSJGlgvKdTkrRG2uzQI6c7hCk1qC9/lyRpujnTKUmSJEkaGItOSZIkSdLAWHRKkiRJkgbGolOSJEmSNDA+SEiSNO2WHHX4dIcw7dZdeNB0hyBJ0kA40ylJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDYxF52ogyX0DGnejJH/V9/73k3xpio+xYZLPJ7m5/Xw+yYbj7DMvyXUjtC9IcuYUxXVAkk9MoN/OSc5PcmOSHyQ5Jskj+7Z/NcnFUxGTJEmSNBtZdM5sGwG/LTqr6vaq2meKj/FZ4Jaq2qKqtgBuBY6Z4mMMRJJNgdOAv6mqPwSeAvwX8Oi2fSPg6cBGSf5guuKUJEmS1mTrTHcAGlmS+cDRwCOBm4HXV9U9SZ7c2jcBlgMvB+4Avgo8BpgDHFZVXwU+BGyRZBHwbeCTwJlVtV2SRwD/DuwIPAC8varOSXIA8OftuFsAZ1TVu0aJ8cnADsC+fc3vB36UZIsx4uofY3Pgy8Abh7XvDHwUWB/4NfC6qrpxrPiSvA54DzAE/BC4f6wcA38NHF9VFwNUVQH9M8EvA77ezuOVwD+OMx7Lli1jaGhopbfPFuahYx46y5Ytm+4QVgt+HjrmwRz0mIfOIPMwd+7cgYwrDWfRufr6PPCWqjovyfuBw4G3AScBH6qqM1rhuBbwG2Dvqro3ycbAJUm+Brwb2K6q5kO3rLVv/L8GqKo/SrI1cFaSrdq2+cDT6Iq2G5N8vKr+Z4QYtwEWVdXyXkNVLW9F7rbAklHiosXzh8AX6QrKRUkW9I39A+DZVfVAkucB/0BXBI4YH13hfCRdEfwL4Bzg6jHyC7AdcPwY21/VxryDrhgdt+icM2fOmBfwoaEhL/CYhx7z0BkaGuI30x3EamC868ds4d+FOegxDx3zoJnAonM11O6J3KiqzmtNxwOnJXk08MSqOgOgqpa2/nOAf0jybGAF8ERg03EOszvw8TbOD5IsAXpF53er6hdt7BuAzYCRis4ANUZ7xohrE7pZ0JdV1fUjjLEhcHySLdtYc/q2jRTfxsC5VfXT1n5K3/lMWlt6+2TggqqqJA8k2a6qHnIvqiRJkqTReU/nmiWjtO9HV8Tt0GY17wAesZJjwYOXpS5n9H+cuB54WpLffo7a6+2B748T1y/oCtndRhn774Fzqmo74M948PmMFt9IBfBYrqebGR3JvnTLgm9Nchswj26JrSRJkqRJsOhcDbVZvHuSPKs17Q+cV1X3Aj9O8hKAJOu1J61uCNxZVcuS7Ek38wfwS9pDcUZwPl1RSFtW+yTgxknG+SO6JayH9TUfBlzVto0WF3RLgl8CvCbJq0cYfkPgf9vrAyYQzqXAgiSPazO/L+9tSLJ3kpGWxn4CeG2SXfr6LkzyBLqltS+oqnlVNY+uOLXolCRJkibJonP18MgkP+77eTvwWuCoJNfS3cP4/tZ3f+Ctrf0i4Al093numOQKukLyBwBV9TPgwiTXJTlq2DE/BaydZDFwCnBAVY334J2R/AWwVZIfJbmZbknrX7RtI8bVU1W/Al4EHJLkxcPG/WfgH5NcCKw9XhBVNQQcAVwMfAe4qm/zFsC9I+zTe0DQh9tXpnwfeBbwWLoi/JK+vrcC9/YXqJIkSZLG5z2dq4GqGq34f8YIfW8CnjNC311HGXv4LOJ2rX0pI8wgVtVxwHF97180Smy97fcAC0fZdtdocfXF8XNgp772c1v7xTz4nsy/Gy++qjoWOHaEY80HDhklxovpCs3hnjhC36ePNIYkSZKk0Vl0asarqhGLYkmSJEmDZ9GpCUlyKbDesOb9q2rxdMQjSZIkac1g0akJqSrvZZQkSZI0aRadkqRpt9mhR053CNNuaGhoukOQJGkgfHqtJEmSJGlgLDolSZIkSQNj0SlJkiRJGhjv6ZQkDdySow4fe/vDFMfqbN2FB013CJIkDYQznZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwMyKojPJE5J8McnNSW5I8o0kW013XCsryW1JFidZ1H4+NoF9npHkmrbf8WP0W5DkzAmMt2mSLyS5JcmVSS5Osvc4+8xLct1kjtO379VJ5rfX6yT5VZKFfduvTPL0JO9P8ryJjitJkiRpsGb893QmCXAGcHxVvbK1zQc2BX44jaGtqj2r6q5J9P8g8LaqOifJH6zKgVtOv0KX01e3ts2AP1+VccdxEfBMYBGwPXBje39ikkcBmwPXVNVVU3GwJOtU1QNTMZYkSZI0m82Gmc49gWVVdXSvoaoWVdX30jkqyXVtBnBf+O0s3HlJTk3ywyQfSrJfkstavy1av+OSHJ3ke63fi1r7vNZ2Vft5Zt+45yb5UpIfJDmpxfDcJGf04kuyV5LTpzgPvwH+v3b+t67iWM8BfjMsp0uq6uMw+vmPJsljk3wlybVJLkny1BG6XUhXZNL+ezQwv73fGbiqqpa338k+bdzbkhzZYlicZOvW/qgkn0tyeZtBfXFrPyDJaUm+DpyV5ITetrb9pCSDLKwlSZKkGWfGz3QC2wFXjrLtpXSFy/bAxsDlSc5v27YHngLcDdwCHFNVOyc5GHgL8LbWbx6wB7AFcE6SJwN3AntV1dIkWwInAzu2/k8DtgVupyukdgPOBj6ZZJOq+inwOuDYcc7rnCTL2+vjq+oj4/S/GfjHJN+vqivG6TuebYGxZhTHOv+RHAlcXVUvSfIc4PP8rqDsuQj4QHv9zLbPq5I8ur2/cJSx76qqpyf5K+CdwBuA9wJnV9Xrk2wEXJbkO63/rsBTq+ruJHsAhwBfTbJhO85rxzgPli1bxtDQ0Epvny3MQ8c8qJ+fh455MAc95qEzyDzMnTt3IONKw82GonMsuwMnV9Vy4I4k5wE7AfcCl1fVEECSm4Gz2j6L6WZPe06tqhXATUluAbYGbgU+0ZbxLgf67x+9rKp+3MZdBMyrqguSnAAsTHIsXeHzmnFin/Dy2jZbtyHwQuDLSf4U+DnwjaraaSJjjDP+J+ly+Zs23hxGP/+R7A68DKCqzk7yuCQbVtUveh2q6rYk6yZ5Al2ObwQuB3ahKwY/PsrYvRnjK+n+kQHg+cCfJ3lne/8I4Ent9ber6u52zPOSfDLJ49u+Xx5vye2cOXPGvIAPDQ15gcc89MymPCyZ7gDWAONdP2aL2fR3MRpz0DEPHfOgmWA2FJ3XA/uMsi1j7Hd/3+sVfe9X8OC81bD9im527A662dK1gKWjjLu8b6xjga+3vqdN8f2Efwx8t6oWJ/kL4KvAacApKzne9bQiEaCq/jrJxkBvBnWs8x/JSL+H4XkFuJjudzlUVZXkErqZ4p2BS0YZu5fv/lwHeFlV3figIJJdgF8N2/8EYD/glcDrxzkPSZIkScPMhns6zwbWS3JgryHJTm3p5PnAvknWTrIJ8GzgskmO//Ika7X7PDenm4HbkK4wWgHsD6w93iBVdTvdktvDgOMmGcN4rqY7z0dU1ffoHqz0XrplryvjbOARSd7U1/bIvteTPf/z6Qo7kiygWxJ77wj9LqQraC9u7y+mmxH+SVX9fBLxfwt4S3sgEkmeNkbf42hLqavq+kkcQ5IkSRKzoOisqgL2BvZK95Up1wNH0BV4ZwDXAtfQFVLvqqqfTPIQNwLnAd8EDqqqpcCngNe2mbiteOjs2WhOAv6nqm6YQN9z8ruvTPk8QJKDkhw0Qt/P0i0LXpTkCmAu3f2NX0ryyGF916HNDibZMckxwwdrOX0JsEeSW5NcBhwP/E3rMtnzPwLYMcm1wIcY/b7JC+kK+4tbHEN0Be1F44w/3N/TLQG+Nt1XuPz9aB2r6g7g+4x/j60kSZKkEaSrH7QykhwHnFlVX5qi8T5B90Cdz07FeCsZw8HAE6vqXdMVw+qkFeWLgaf332M6mhNPPLEWLlw46nbvy+iYh85sysOSow6f7hBWe+suPGjWfB7GMpv+LkZjDjrmoTPgPIx1q5k0ZWbDPZ1rhCRX0s0IvmMaY/gs3dN+XzFdMaxOkjwP+BzwrxMpOCVJkiQ9lEXnKqiqA6ZwrB2GtyW5FFhvWPP+VbV4qo47LIa/GMS4a6qq+g6/e6qtJEmSpJVg0bkaq6pdpjsGSZIkSVoVFp2SpIHb7NAjR93mfVudQX35uyRJ023GP71WkiRJkjR9LDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwPggIUnSlFty1OGT6z+gONYk6y48aLpDkCRpIJzplCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwFh0arWQ5L1Jrk9ybZJFSXaZ4H6/n+RL4/TZKMlfTWYfSZIkSVPDr0zRtEuyK/Ai4OlVdX+SjYF1J7DfOlV1O7DPOF03Av4K+BTABPeRJEmSNAWc6dTqYC5wV1XdD1BVd1XV7Ul2SnJRkmuSXJbk0UkOSHJakq8DZyWZl+Q6gLbtq0n+K8mNSXpfFPghYIs2g3rUCPuc3va5Kck/94JK8hdJfpjk3CSfSfKJhzctkiRJ0prPmU6tDs4C3pfkh8B3gFOAi9t/962qy5P8HvDr1n9X4KlVdXeSecPG2hnYDvg/4PIk/wm8G9iuquYDjLDPfOBpwP3AjUk+DiwH/g54OvBL4GzgmvFOZNmyZQwNDa309tnCPHTMg/r5eeiYB3PQYx46g8zD3LlzBzKuNJxFp6ZdVd2XZAfgWcCedMXmB4Ghqrq89bkXIAnAt6vq7lGG+3ZV/az1PR3YHfjKOCF8t6p+0fa5AdgM2Bg4r3ecJKcBW413LnPmzBnzAj40NOQFHvPQM5PzsGS6A1gDjXf9mC1m8t/FRJmDjnnomAfNBBadWi1U1XLgXODcJIuBvwZqlO6/Gmuocd6P5P6+18vp/i4ygf0kSZIkjcN7OjXtkvxhki37muYD3wd+P8lOrc+jk0zkH0n2SvLYJOsDLwEupFse++hJhnUZsEeSx7TjvmyS+0uSJEnCmU6tHjYAPp5kI+AB4EfAG4FjW/v6dPdzPm8CY10AnAA8GfhCVV0BkOTC9vCgbwKfHG+QqvrfJP8AXArcDtwA/GKS5yVJkiTNehadmnZVdSXwzBE23QU8Y1jbce2nt+9tdA8O6rmzqt48wjFePaxpu9Y+fLwX9fX5QlX9R5vpPIPugUeSJEmSJsHltdLojkiyCLgOuJXxH0gkSZIkaRhnOjVjDJ+1nILx3jlVY0mSJEmzlTOdkiRJkqSBseiUJEmSJA2My2slSVNus0OPnHBfv/i8MzQ0NN0hSJI0EM50SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDYwPEpIkTdiSow4fzLgDGXXNsu7Cg6Y7BEmSBsKZTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDcxKF51JlidZlOS6JKcleeRUBjYVkhyR5J3THUe/JAck+f1J7jMl55HkG0k2Won9DkjyiVU9/qpKckySbVZy3wVJntn3/qAkr5m66CRJkiSNZFVmOn9dVfOrajvgN8CDnvWeZO1VimzmOgCYVNE5VarqT6rq59Nx7KlQVW+oqhtWcvcFwG+Lzqo6uqo+PyWBSZIkSRrVVC2v/R7w5DabdE6SLwCLk6yd5Kgklye5NslfjrRzkk2SfLn1uzzJbq39iCTHJzkryW1JXprkn5MsTvJfSea0frcl+ackl7WfJ49wjPlJLmlxnJHkMUm2SHJVX58tk1zZN+Y/JLk4yRVJnp7kW0luTnJQ3z6H9p3fka1tXpLvJ/lMkutb/Osn2QfYETipzRKvPyzGc5N8NMlFbQZ5577N27TttyR5a+v/90kO7tv/g0nemmRukvP7ZqKf1XdOG7fXr2kxX5PkhNb2Z0kuTXJ1ku8k2XSsX3qSRyX5XDv/q5O8uLV/LMn72us/brGsNdr4k/g9n5tkx/b6vna+17Tfa2+shxwjyTy6fxQ5pOXkWembPR7ps9F3vN7n6oe9PEqSJEmauHVWdYAk6wAvBP6rNe0MbFdVtyZ5I/CLqtopyXrAhUnOqqpbhw3zb8BHquqCJE8CvgU8pW3bAtgT2Aa4GHhZVb0ryRnAnwJfaf3uraqd0y2Z/CjwomHH+Dzwlqo6L8n7gcOr6m1JfpFkflUtAl4HHNe3z/9U1a5JPtLadwMeAVwPHJ3k+cCW7ZwDfC3Js4H/bu2vqqoDk5za4j4xyZuBd1bVFaOk9FFV9cw2zueA7Vr71i0PjwZuTPLvwGeB04F/S7IW8MoWywHAt6rqg+lmnB+09DnJtsB7gd2q6q4kj22bLgCeUVWV5A3Au4B3jBInbYyzq+r16ZbtXpbkO8C7gcuTfA/4GPAnVbUiyVjjT/T3/Ns8AZdU1XuT/DNwIPCBkc6hqt6R5Gjgvqr6cMvBc/vGeshnA3hb27ZO+1z9SWt/3hj5YNmyZQwNDa309tnCPHTMg/r5eeiYB3PQYx46g8zD3LlzBzKuNNyqFJ3rJ1nUXn+PrgB6JnBZX1H5fOCpbYYPYEO6Ymx40fk8upm83vvfS/Lo9vqbVbUsyWJgbX5X3C4G5vWNcXLffz/SP3iSDYGNquq81nQ8cFp7fQzwuiRvB/alK9p6vtZ3rA2q6pfAL5MsbUXW89vP1a3fBu38/hu4tRWyAFcOi3UsJwNU1flJfi+/uwfzP6vqfuD+JHcCm1bVbUl+luRpwKbA1VX1sySXA59rM4Rf6Yuj5znAl6rqrnasu1v7/weckmQusC4P/T0N93zgz/O7+00fATypqr6f5EDgfOCQqrp5AuNP9Pfc8xvgzPb6SmCvlTmHcT4b0BX1vWOMFMeDzJkzZ8wL+NDQkBd4zEPPmpiHJdMdwAw23vVjtlgT/y6mmjnomIeOedBMsCpF56+ran5/Qysaf9XfRDeD9K1h/T5IN3tFG2MtYNeq+vUI493f+q1Isqyqqm1eMSz+GuX1eL5MN4N1NnBlVf2sb9v9fce6v6+9d+wA/1hVnx4W97xh/ZcDD1pKO4bhsffeDx+vd+7H0M1sPoFuZrRXsD6bLscnJDlq2P2LGeE4AB8H/rWqvpZkAXDEOLGGbkbyxhG2/RHwMx58/+pY40/099zT36c/H5M9h/H08t5/DEmSJEkTNOivTPkW8Ka+e/K2SvKoqnpvewjR/NbvLODNvZ2SzH/ISOPbt++/F/dvqKpfAPf03ZO3P3Be27a0xfnvwLGTPOa3gNcn2aDF/cQkjx9nn1/SLZEdzb5trN3plib/YpzxzgBeAOzU4iHJZsCdVfUZuhnopw/b57vAK5I8rvXvLa/dEPjf9vq14xyXdry3pP3rQJtx7R3/HcDTgBcm2WUlx18Zox1jxLyP9dmQJEmStOoGPXNzDN2SxKtaYfJT4CUj9Hsr8Mkk17aYzmfY03AnYL0kl9IV0q8aYftr6e7DfCRwC939mz0nAS+lK34nrKrOSvIU4OJWd90HLKSbFRvNcS2OXzPC7C5dAXQR8HvA6ycQw2+SnAP8vKp6x10AHJpkWYvpNcP2ub7NNp+XZDnd8uAD6GYFT0vyv8AlwB+Mc/i/p7t/9tr2+70tyZ/RFbrvrKrbk/wFcFySnVZi/JUx2jG+Dnwp3cOO3jJsn7E+G5IkSZJWQX63QnHNleQ2YMfePYorsf87gQ2r6u+mNLDJx3EuYz9kaKR91gKuAl5eVTcNKjZNzIknnlgLFy4cdbv3ZXTMQ2dNzMOSow6f7hBmrHUXHrTGfR4GYU38u5hq5qBjHjoDzkPG7yKtull/j1p7OuoWdA/XWaMk2YbuYTpnWHBKkiRJWh3NiKKzquatwr57T2Eoq6SqFkyy/w3A5oOJRpIkSZJW3aAfJCRJkiRJmsUsOiVJkiRJAzMjltdKkh4emx165JSP6cNCOkNDQ9MdgiRJA+FMpyRJkiRpYCw6JUmSJEkDY9EpSZIkSRoY7+mUJLHkqMOn9/jTevTVw7oLD5ruECRJGghnOiVJkiRJA2PRKUmSJEkaGItOSZIkSdLAWHRKkiRJkgbGolOSJEmSNDAWnZIkSZKkgbHonKWSPCHJF5PcnOSGJN9IstV0xzVZSY5L8pfD2l7SzmfHJB+brtgkSZIkWXTOSkkCnAGcW1VbVNU2wN8Cm05vZCvlZOCVw9peCZxcVVdU1VunISZJkiRJjUXn7LQnsKyqju41VNUi4IIkRyW5LsniJPsCJFmQ5Lwkpyb5YZIPJdkvyWWt3xat33FJjk7yvdbvRa19Xmu7qv08s2/cc5N8KckPkpyUznOTnNGLLcleSU4f5Vy+A2ydZG7r+0jgecBX2vhnJlkryW1JNuob80dJNm0x79PXft9Ysa166iVJkqTZZZ3pDkDTYjvgyhHaXwrMB7YHNgYuT3J+27Y98BTgbuAW4Jiq2jnJwcBbgLe1fvOAPYAtgHOSPBm4E9irqpYm2ZJudnLH1v9pwLbA7cCFwG7A2cAnk2xSVT8FXgccO9KJVNXyVpC+Avg34M+Bc6rql70asapWJPkqsDdwbJJdgNuq6o5x6siRYrtgrB2WLVvG0NDQSm+fLcxDxzyon5+HjnkwBz3moTPIPMydO3cg40rDWXSq3+50y1KXA3ckOQ/YCbgXuLyqhgCS3Ayc1fZZTDdz2nNqVa0AbkpyC7A1cCvwiSTzgeVA/72jl1XVj9u4i4B5VXVBkhOAhUmOBXYFXjNG3CcDR9EVna8EPj9Cn1OA99EVr69s78fzkNgYp+icM2fOmBfwoaEhL/CYh57VKQ9LpjsAjXv9mC1Wp7+L6WIOOuahYx40E1h0zk7XA/uM0D7WtN/9fa9X9L1fwYM/RzVsvwIOAe6gmy1dC1g6yrjL+8Y6Fvh663taVT0wRmwXAnOTbA88k4fe4wlwMfDkJJsALwE+0NofaDH17nVddwKxSZIkSZog7+mcnc4G1ktyYK8hyU7APcC+SdZuxdmzgcsmOfbL2z2UWwCbAzcCGwJDbQZ0f2Dt8QapqtvplrUeBhw3Tt8CTgWOB75RVUtH6XMG8K/A96vqZ23TbcAO7fWLgTnjxSZJkiRp4iw6Z6FWgO0N7NW+MuV64AjgC8C1wDV0hem7quonkxz+RuA84JvAQa0A/BTw2iSX0C2t/dUExzoJ+J+qumECfU+mm0n94hh9TgEW8uCltZ8B9khyGbDLJGKTJEmSNAEuF5yl2kziK0bYdGj76e97LnBu3/sFo20DLqyqQ4btfxPw1L6m94wy7puHxbI7XVE4rqq6mmHLg0cY/4oR+twBPGMlYpMkSZI0ARadWi0luZJu1vEd0x2LJEmSpJVn0akpU1UHTOFYOwxvS3IpsN6w5v2ravFUHVeSJEnS1LLo1BqjqnaZ7hgkSZIkTY5FpySJzQ49ctqO7XfQdQb15e+SJE03n14rSZIkSRoYi05JkiRJ0sBYdEqSJEmSBsaiU5IkSZI0MD5ISJJmmSVHHT7dITzEkukOYDWw7sKDpjsESZIGwplOSZIkSdLAWHRKkiRJkgbGolOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgxi06kzwhyReT3JzkhiTfSLLVwxHcICS5LcniJIvaz8dWcpxzk+w41fH1jb8gyZkTPW6SnZOcn+TGJD9IckySR05BHBsk+XT7/V/fjrFL2/be1nZty2Wv/UVJrk5yTfvM/OUoY78wyRVJvt9i/vCqxitJkiRp9TLm93QmCXAGcHxVvbK1zQc2BX448OgGZ8+qumu6gwBIsnZVLV/FMTYFTgNeWVUXt9/by4BHA/+3iiEeA9wKbFlVK5JsDjwlya7Ai4CnV9X9STYG1k0yB/gPYOeq+nGS9YB5I8S8HfAJ4E+r6gdJ1gHeuIqxSpIkSVrNjFl0AnsCy6rq6F5DVS2C3xak/wy8ECjgA1V1SpIFwJHAHcB84HRgMXAwsD7wkqq6OclxwFJgW7oi9u1VdWaSecAJwKPaId9cVRe1cY8A7gK2A64EFgLPaX32bnHtBbypql460SQkeQpdYb1zez8P+FpVPTXJc4EPt1xd3sa+v2/fNwF/UFXvau8PAHaoqrckWQi8FVgXuBT4q6panuQ+4F+BPwbeAVww0VhH8dct/osBqqqAL41zzhsAXwUeA8wBDquqrw7rswWwC7BfVa1oY98C3JLkpcBdvVz0ivgkj6XL1c9a+/3AjSOE8C7gg1X1g9bvAeBTbYzNgM8BmwA/BV5XVf/dPjO/BrYGNgNeB7wW2BW4tKoOaPvfB3ya7vN7D10x/tMkB9IVtusCPwL2r6r/a+PeC+wIPAF4V1V9KckJwJd6eUlyEnBKVX1ttLwuW7aMoaGh0TaPu322MA8d86B+fh465sEc9JiHziDzMHfu3IGMKw03XtHZK+5G8lK6onJ7YGPg8iTnt23bA08B7gZuAY6pqp2THAy8BXhb6zcP2APYAjgnyZOBO4G9qmppki2Bk+mKAYCn0RWptwMXArsBZwOfTLJJVf2UrhA5dpzzOidJb3bx+Kr6SJJ1k2zeiqp9gVOTPAI4DnhuVf0wyeeBNwEf7RvrS8DFdEUUbd8PtkJ2X2C3qlqW5FPAfsDn6Qrq66rqfePEOVHbAcdPcp+lwN5VdW+bpbwkyddawdqzLbBolJnYs4D3Jfkh8B26Yuy8qro7ydeAJUm+C5wJnNwrWofF/C+jxPYJ4PNVdXyS1wMfA17Stj2G7h8a/hz4Ot1n4A10n7/57R9FHgVcVVXvSPI+4HDgzcDpVfUZgCQfAP4C+Hgbdy6wO11B+zW63+sxwCHAV5NsCDyTrsgd1Zw5c8a8gA8NDXmBxzz0TFceljzsR9REjHf9mC28PpiDHvPQMQ+aCVblQUK70xUTy6vqDuA8YKe27fKqGmqzXDfTFSjQzXjO6xvj1KpaUVU30RWnW9PNun0myWK6JaPb9PW/rKp+3AqYRcC8ViSdACxMshHdrNc3x4l9z6qa334+0osFeEV7vS9wCvCHwK1V1VtKfDzw7P6BWqF7S5JnJHlc2+dC4LnADnTF0KL2fvO223Lgy+PEOGgB/iHJtXRF4xPpZpwnpKruozu/N9LNRp7SZnmpqjfQne9lwDvpZi0nY1fgC+31CXSftZ6vt9/5YuCOqlrcPg/X87vP1gq63x/AiX37b5fke+2ztR9dUd3zlfZZvIGWh6o6D3hykscDrwK+3GZkJUmSJE3QeDOd1wP7jLItY+x3f9/rFX3vVww7Zv+sWu/9IXRLc7enK4qXjjLu8r6xjqWb9VoKnLaShcEpwGlJTqdboXpTu391ovu+AvgBcEZVVVt+fHxVvWeE/ktX9T7OYa6nKwC/Ol7HPvvRLV/doc3E3gY8YoRxt0+y1ggzlbRzOBc4txVyr6WbGaaqFgOL2xLVW4EDRon5mgnE2v856f8sDf+cjfZ57u1/HN3y7mtagbxghHHhwZ/tE+hy9Urg9ROIVZIkSVKf8WY6zwbWa/fCAZBkpyR7AOcD+yZZO8kmdDOAl03y+C9Psla7d3Bzunv/NgSGWpGzP7D2eINU1e10S24PoxU9k1VVN9MVsn/H72bJfgDMa8t+afGcN8Lup9Mt/3xV377fBfZps2QkeWy7V3EQPgG8tvf02Ha8hemePLxzWxY83IbAna3g3JPuHskHaTm5AjiyFdEk2TLJi5P8YVv+3DOfbkntBu3+2we1j3D8o4C/TXsScvscvL1tu4iuyIOu4JvsPa9r8bt/LHl13/6PBobaw472m+BYx9GWg1fV9ZOMQ5IkSZr1xpzpbDN2ewMfTfJuupnE2+j+J/x8umWQ19DNJL2rqn6SZOtJHP9GuiJuU+Cgdh/np4AvJ3k5cA7wqwmOdRKwSVseOZ7+ezqvrarXtNen0BVDfwDQ4nkd3Qxo70FCRw8frKruSXIDsE1VXdbabkhyGHBWkrWAZXQP/HlQAZbkoNb/IeMCz03y4773L2///c8ky9rri6vq5UleCXy4Fbkr6H4/pwNPonv4znAnAV9PcgXdUuUfjNAHuvsl/wX4UZL/o3tA0KHABsDH25LmB+gezPNGulnCdyX5dDvur3joLCdVdW2StwEnp/tqlwL+s21+K/C5JIfSHiQ0Smyj+RWwbZIrgV/QLZeG7h8ULqX7HSymK0LHVFV3JPk+8JVJxiBJkiQJyIOfG/MwHrh7YuiZVTXmU1YnMd4ngKur6rNTMd5MkeQo4ISquna6Y3m4JLmvqjaYorEeSVegPr2qfjFe/xNPPLEWLlw46nYfBtAxD51pe5DQUYc/7MfU+NZdeJB/F3h9AHPQYx46A87DWLfLSVNmVR4ktNpoM1pPpXtojPpU1aGzqeCcSkmeRzcD/PGJFJySJEmSHmq8BwkNTO87FadorB2GtyW5FFhvWPP+7QE3msGmapazqr5DtzxZkiRJ0kqatqJz0Kpql/F7SZIkSZIGacYWnZKkkW126JHTHcKDeN9WZ2hoaLpDkCRpIGbEPZ2SJEmSpNWTRackSZIkaWAsOiVJkiRJA2PRKUmSJEkaGB8kJEmzzJKjDp/uEB5iyXQHsBpYd+FB0x2CJEkD4UynJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxqJTM16S9ya5Psm1SRYl2SXJi5JcneSaJDck+cvW94gk72yvn5Hk0rbP95McMa0nIkmSJK2B/MoUzWhJdgVeBDy9qu5PsjHwKOAMYOeq+nGS9YB5I+x+PPCKqromydrAHz5ccUuSJEkzhUWnZrq5wF1VdT9AVd2VZAXdZ/9nre1+4MYR9n08MNT6LAdueFgiliRJkmYQi07NdGcB70vyQ+A7wClVdV6SrwFLknwXOBM4uapWDNv3I8CNSc4F/gs4vqqWjnWwZcuWMTQ0tNLbZwvz0DEP6ufnoWMezEGPeegMMg9z584dyLjScBadmtGq6r4kOwDPAvYETkny7qp6Q5I/Ap4HvBPYCzhg2L7vT3IS8Hzg1cCrgAVjHW/OnDljXsCHhoa8wGMeeqYrD0se9iNqIsa7fswWXh/MQY956JgHzQQ+SEgzXlUtr6pzq+pw4M3Ay1r74qr6CF3B+bJR9r25qv4deC6wfZLHPVxxS5IkSTOBRadmtCR/mGTLvqb5wB1JFgxre8jkT5I/TZL2dktgOfDzQcQpSZIkzVQur9VMtwHw8SQbAQ8APwIOBj6d5NPAr4FfMWxpbbM/8JEk/9f23a89UEiSJEnSBFl0akarqiuBZ46w6U9G6X9E3+tXDigsSZIkadZwea0kSZIkaWAsOiVJkiRJA2PRKUmSJEkaGO/plKRZZrNDj5zuEB7E76DrDOrL3yVJmm7OdEqSJEmSBsaiU5IkSZI0MBadkiRJkqSBseiUJEmSJA2MDxKSpFlgyVGHT3cIY1oy3QGsBtZdeNB0hyBJ0kA40ylJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6NSUSTIvyXXD2o5I8s5x9tsxycfa6wVJnjlKv1G3TTC2V490TEmSJEmD41emaNpV1RXAFe3tAuA+4KIRuo61bTzzgFcDXxjhmJIkSZIGxJlOPWySnJvkn5JcluSHSZ7V2hckOTPJPOAg4JAki3rbW5+HbEuySZIvJ7m8/ezW+u7R+ixKcnWSRwMfAp7V2g7pHbP1PyLJ51p8tyR5a99x/y7JD5J8O8nJ483aSpIkSXowZzr1cFunqnZO8ifA4cDzehuq6rYkRwP3VdWH+3caaVuSLwAfqaoLkjwJ+BbwFOCdwF9X1YVJNgCWAu8G3llVL2r7LhgW19bAnsCjgRuT/DuwPfAy4Gl0fytXAVdOXSokSZKkmc+iU1OpJtB+evvvlXRLXlfF84BtkvTe/16b1bwQ+NckJwGnV9WP+/qM5j+r6n7g/iR3ApsCuwNfrapfAyT5+niDLFu2jKGhoZXePluYh455UD8/Dx3zYA56zENnkHmYO3fuQMaVhrPo1FT6GfCYYW2PBW7te39/++9yVv3ztxawa68o7POhJP8J/AlwSZLnPXTXh7i/73UvtnEr1eHmzJkz5gV8aGjICzzmoefhzMOSh+UoWhXjXT9mC68P5qDHPHTMg2YC7+nUlKmq+4ChJM8FSPJY4AXABZMY5pd0S1wnsu0s4M29N0nmt/9uUVWLq+qf6B4WtPU4447mAuDPkjyiLdP900nuL0mSJM16Fp2aaq8BDkuyCDgbOLKqbp7E/l8H9h7+IKFRtr0V2DHJtUluoHvQEMDbklyX5Brg18A3gWuBB5Jck+SQiQRSVZcDXwOuoVsWfAXwi0mciyRJkjTrubxWU6qqbqB7IM9I2xb0vb6Ldk9nVZ0LnNte/xB46ij7j7Rt3xH6vWWU8J477H3vmEcM23+7vrcfrqojkjwSOB/4l1HGliRJkjQCi05pbP+RZBvgEcDxVXXVdAckSZIkrUksOqUxVNWrpzsGSZIkaU3mPZ2SJEmSpIGx6JQkSZIkDYzLayVpFtjs0COnO4RR+R10nUF9+bskSdPNmU5JkiRJ0sBYdEqSJEmSBsaiU5IkSZI0MBadkiRJkqSB8UFCkjQDLTnq8OkOYVKWTHcAq4F1Fx403SFIkjQQznRKkiRJkgbGolOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDq1WkjyhCRfTHJzkhuSfCPJVkmuG8Cx3p/keVM9riRJkqSH8itTNO2SBDgDOL6qXtna5gObDuJ4VfW+QYwrSZIk6aGc6dTqYE9gWVUd3WuoqkXA//TeJ1k7yVFJLk9ybZK/bO0bJPlukquSLE7y4tY+L8n3k3wmyfVJzkqyftt2XJJ92uvbkhzZt//WrX2TJN9u7Z9OsiTJxg9bRiRJkqQZwplOrQ62A64cp89fAL+oqp2SrAdcmOQsusJ076q6txWFlyT5WttnS+BVVXVgklOBlwEnjjD2XVX19CR/BbwTeANwOHB2Vf1jkhcAb5zIiSxbtoyhoaGV3j5bmIeOeVA/Pw8d82AOesxDZ5B5mDt37kDGlYaz6NSa4vnAU3szlMCGdEXlj4F/SPJsYAXwRH63LPfWNmMKXVE7b5SxT+/r89L2endgb4Cq+q8k90wkyDlz5ox5AR8aGvICj3noGWQelgxkVA3SeNeP2cLrgznoMQ8d86CZwKJTq4PrgX3G6RPgLVX1rQc1JgcAmwA7VNWyJLcBj2ib7+/ruhxYf5Sx7+/r0/ubyIQilyRJkjQm7+nU6uBsYL0kB/YakuwEbNbX51vAm5LMadu3SvIouhnPO1vBueewfVbFBcAr2rGeDzxmisaVJEmSZhWLTk27qiq6pax7ta9MuR44Ari9r9sxwA3AVe1rVD5NNyt5ErBjkiuA/YAfTFFYRwLPT3IV8EJgCPjlFI0tSZIkzRour9Vqoapup80sDrNd274C+Nv2M9yuowy7Xd/4H+57fUDf63l9r68AFrS3vwD+uKoeSLIrsGdV9S/XlSRJkjQBFp3SyJ4EnJpkLeA3wIHj9JckSZI0AotOaQRVdRPwtOmOQ5IkSVrTeU+nJEmSJGlgLDolSZIkSQPj8lpJmoE2O/TI6Q5hwvzi887Q0NB0hyBJ0kA40ylJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxns6JelhsuSowx/aNg1xrI7MA6y78KDpDkGSpIFwplOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwFh0rmaSPCHJF5PcnOSGJN9IstV0x7UyktyWZONhbX+e5N0rOd4RSf43yaIk1yX586mJVJIkSdKgrDPdAeh3kgQ4Azi+ql7Z2uYDmwI/nMbQpkxVfQ342ioM8ZGq+nCSpwDfS/L4qlox3k5J1q6q5atwXEmSJEkrwaJz9bInsKyqju41VNWidI4CXggU8IGqOiXJAuBI4A5gPnA6sBg4GFgfeElV3ZzkOGApsC1dAfv2qjozyTzgBOBR7XBvrqqL2rhHAHcB2wFXAguB57Q+ewMk2Qt4U1W9dKInmOQAYEfgvcA1wOZVtSLJI4Ebgc2BJwGfBDYB/g84sKp+0D9OVX0/yQPAxq0wPxJYD7gZeF1V3ZfkNuBzwPOBTyR5PHAQ8ABwQ1W9MsljW5/N27HeWFXXJjmixdGL56NV9bHxzm/ZsmUMDQ2t9PbZwjxID+XfRcc8mIMe89AZZB7mzp07kHGl4Sw6Vy+9Am+4l9IVldsDGwOXJzm/bdseeApwN3ALcExV7ZzkYOAtwNtav3nAHsAWwDlJngzcCexVVUuTbAmcTFcQAjyNrki9HbgQ2A04G/hkkk2q6qfA64BjV+ZEq+oXSa5pMZ0D/BnwrapaluQ/gIOq6qYkuwCfoit4f6u1r6Arwg8DnldVv0ryN8Dbgfe3rkurave2z+3AH1TV/Uk2atuPBK6uqpckeQ7webpcA2xN9w8BjwZuTPLvVbVsrPOaM2fOmBfwoaEhL/DM3jwsme4AtFob7/oxW8zW60M/c9AxDx3zoJnAonPNsDtwclseekeS84CdgHuBy6tqCCDJzcBZbZ/FdAVTz6ltGepNSW6hK6hupZsBnA8sB/rvHb2sqn7cxl0EzKuqC5KcACxMciywK/CaVTivU4B96YrOVwKfSrIB8EzgtG61MdDNYPYckmQh8Mu27y7ANsCFrf+6wMXDjtFzLXBSkq8AX2ltuwMvA6iqs5M8LsmGbdt/VtX9wP1J7qSbJf7xKpyvJEmSNOtYdK5ergf2GaE9I7T13N/3ekXf+xU8+Pdbw/Yr4BC6pbnb0z1Uauko4y7vG+tY4Out72lV9cAYsY3na8A/tiWuO9DNpD4K+HlVzR9ln49U1Yd7b5L8GfDtqnrVKP1/1ff6T4FnA38O/F2SbRk5t71cjZYDSZIkSRPk02tXL2cD6yU5sNeQZCfgHmDfJGsn2YSucLpskmO/PMlaSbagu0/xRmBDYKjNgO4PrD3eIFV1O92S28OA4yYZw/Cx7qM7j38Dzqyq5VV1L3BrkpdD93ClJNuPMcwlwG5tuTBJHjnS036TrAX8v6o6B3gXsBGwAXA+sF/rswC4q8UgSZIkaQo4c7MaqapKsjfw0fa1IkuB2+juy9yA7sE7Bbyrqn6SZOtJDH8jcB7dEtGD2n2cnwK+3Aq8c3jwrOBYTgI2qaobJtD32iS9p8ueSrfEtd8pwGnAgr62/YB/T3IYMAf4It25P0RV/bQ9nOjkJL1luIfx0Kf9rg2c2JbOhm7G9OftgUHHJrmW7kFCr53AOUmSJEmaIIvO1UybSXzFCJsObT/9fc8Fzu17v2C0bcCFVXXIsP1vAp7a1/SeUcZ987BYdgc+M9Z5tP3mjbLpuL4+X2LYEtequhV4wQjjHTHKcc6mu8d11OO3BwDtPkKfu4EXj3esqtpupGNLkiRJGptFpyYlyZV0M6LvmO5YJEmSJK3+LDpngao6YArH2mF4W5JLefATZgH2r6rFU3VcSZIkSWsmi06tsqraZbpjkNYEmx165IPe+91rHfPQGdSXv0uSNN18eq0kSZIkaWAsOiVJkiRJA2PRKUmSJEkaGItOSZIkSdLA+CAhSZoiS446fPL7DCCONZF5gHUXHjTdIUiSNBDOdEqSJEmSBsaiU5IkSZI0MBadkiRJkqSBseiUJEmSJA2MRackSZIkaWAsOiVJkiRJA2PROYskeUKSLya5OckNSb6RZKvpjmtlJHl9ksVJrk1yXZIXj9P//Ume93DFJ0mSJKnj93TOEkkCnAEcX1WvbG3zgU2BH05jaJOW5P8D3gs8vap+kWQDYJOx9qmq903yGOtU1QOrEKYkSZIknOmcTfYEllXV0b2GqloEXJDkqDZbuDjJvgBJFiQ5L8mpSX6Y5ENJ9ktyWeu3Ret3XJKjk3yv9XtRa5/X2q5qP8/sG/fcJF9K8oMkJ6Xz3CRn9GJLsleS00c5l8cDvwTua+dxX1Xd2vabn+SSNgN6RpLH9MW5T3u9Qzu3K5N8K8nc1n5ukn9Ich5wcHv/T+2cf5jkWVP225AkSZJmCWc6Z4/tgCtHaH8pMB/YHtgYuDzJ+W3b9sBTgLuBW4BjqmrnJAcDbwHe1vrNA/YAtgDOSfJk4E5gr6pammRL4GRgx9b/acC2wO3AhcBuwNnAJ5NsUlU/BV4HHDvKuVwD3AHcmuS7wOlV9fW27fPAW6rqvCTvBw7vi5Mkc4CPAy+uqp+2IvuDwOtbl42qao/W98+Addo5/0kba8wlusuWLWNoaGilt88W5kF6KP8uOubBHPSYh84g8zB37tyBjCsNZ9Gp3YGTq2o5cEeb5dsJuBe4vKqGAJLcDJzV9llMN3Pac2pVrQBuSnILsDVwK/CJtoR3OdB/7+hlVfXjNu4iYF5VXZDkBGBhkmOBXYHXjBRwVS1P8oIW53OBjyTZAfgIXdF4Xut6PHDasN3/kK4A/3a34pi1gf4r+SnD+vdmW6+kK67HNGfOnDEv4ENDQ17gmbl5WDLdAWiNNt71Y7aYqdeHyTAHHfPQMQ+aCSw6Z4/rgX1GaM8Y+9zf93pF3/sVPPizU8P2K+AQutnI7emWcS8dZdzlfWMdC3y99T1trHsqq6qAy4DLkny77fuRMc6lJ8D1VbXrKNt/Nex9L9b+OCVJkiRNkPd0zh5nA+slObDXkGQn4B5g3yRrJ9kEeDZdMTcZL0+yVrvPc3PgRmBDYKjNgO5PN6M4pqq6nW7J7WHAcaP1S/L7SZ7e1zQfWFJVvwDu6bv3cn/gvGG73whskmTXNtacJNuOf4qSJEmSVoYzN7NEVVWSvYGPJnk33WzibXT3O25Ad59kAe+qqp8k2XoSw99IV9xtChzU7uP8FPDlJC8HzuGhM4ijOQnYpKpuGKPPHODDSX6/ncdPgYPattcCRyd5JN19qK/r26+q6jftgUIfS7Ih3d/AR+lmgiVJkiRNMYvOWaTNJL5ihE2Htp/+vucC5/a9XzDaNuDCqjpk2P43AU/ta3rPKOO+eVgsuwOfGec8lgDPGWXbIuAZI2x6HN0DkXp9nj3CvgtGe19VdzGBezolSZIkPZhFp1YbSa6kmxF9xxSP+zngkcAFUzmuJEmSpPFZdGqVVNUBUzjWDsPbklwKrDesef+qWjyJcV8/fi9JkiRJg2DRqdVaVe0y3TFIkiRJWnkWnZI0RTY79MhJ9fe71zrmoTOoL3+XJGm6+ZUpkiRJkqSBseiUJEmSJA2MRackSZIkaWAsOiVJkiRJA+ODhCRpFS056vCV33cK41iTmQdYd+FB0x2CJEkD4UynJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp0zWJInJPlikpuT3JDkG0m2mu64VkaSDZJ8up3L9UnOT7LLJMd4XJJF7ecnSf637/26I/Q/N8mOU3cWkiRJ0uzj93TOUEkCnAEcX1WvbG3zgU2BH05jaCvrGOBWYMuqWpFkc+Apkxmgqn4GzAdIcgRwX1V9eIrjlCRJktTHonPm2hNYVlVH9xqqalE6RwEvBAr4QFWdkmQBcCRwB11hdjqwGDgYWB94SVXdnOQ4YCmwLV0B+/aqOjPJPOAE4FHtcG+uqovauEcAdwHbAVcCC4HntD57AyTZC3hTVb10+Ikk2QLYBdivqla0c7kFuKVtfzvw+tb9mKr66FjtI4y/A/CvwAYtzgOqaqhv+1rAscD/VNVhI43Rs2zZMoaGhlZ6+2xhHqSH8u+iYx7MQY956AwyD3Pnzh3IuNJwFp0zV6/AG+6ldEXl9sDGwOVJzm/btqebPbybrqA7pqp2TnIw8Bbgba3fPGAPYAvgnCRPBu4E9qqqpUm2BE4GektTn0ZXpN4OXAjsBpwNfDLJJlX1U+B1dIXdSLYFFlXV8uEbWsH4OrqiNMClSc6jWzr+kPaqunrY/nOAjwMvrqqfJtkX+CC/K1bXAU4CrquqD44S32/NmTNnzAv40NCQF3hmXh6WTHcAmhHGu37MFjPt+rAyzEHHPHTMg2YCi87ZZ3fg5FbA3dEKtJ2Ae4HLezN8SW4Gzmr7LKabOe05tc043pTkFmBruqWvn2hLeJcD/feOXlZVP27jLgLmVdUFSU4AFiY5FtgVeM1Kns8ZVfWrNv7pwLPoCs2R2q8etv8f0hXo3+5WJLM20P/PiZ9u5ztuwSlJkiTpoSw6Z67rgX1GaM8Y+9zf93pF3/sVPPizUsP2K+AQuqW529PNMi4dZdzlfWMdC3y99T2tqh4YJa7rge2TrNVbXttntPMZ6zyH97u+qnYdZftFwJ5J/qWqlo7SR5IkSdIofHrtzHU2sF6SA3sNSXYC7gH2TbJ2kk2AZwOXTXLslydZq91ruTlwI7AhMNSKwv3pZgzHVFW30y25PQw4box+NwNXAEe2BySRZMskLwbOB16S5JFJHgXsDXxvjPbhbgQ2SbJrG3dOkm37tn8W+AZwWhL/kUaSJEmaJP8neoaqqkqyN/DRJO+mm028je6+zA2Aa+hmKN9VVT9JsvUkhr8ROI/uQUIHtfs4PwV8OcnLgXOAX01wrJOATarqhnH6vQH4F+BHSf4P+BlwaFVd1R5u1Cucj+ndtzlae7+q+k2SfYCPJdmQ7m/io3Szq70+/9q2nZBkvxFmWyVJkiSNwqJzBmszia8YYdOh7ae/77nAuX3vF4y2Dbiwqg4Ztv9NwFP7mt4zyrhvHhbL7sBnxjqPtt+9wIGjbPtXuqfPTqi9bTui7/Uiuhnf4X0W9L0+fLwYJUmSJD2URaemTZIr6WZE3zHdsUiSJEkaDItOTUpVHTCFY+0wvC3JpcB6w5r3r6rFU3VcSZIkSQ8fi06tVqpql+mOQZIkSdLUseiUpFW02aFHrtR+fuF3xzx0hoaGxu8kSdIayK9MkSRJkiQNjEWnJEmSJGlgLDolSZIkSQPjPZ2SNElLjpq6r21dMmUjrdnMA6y78KDpDkGSpIFwplOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGhiLzmmSZNMkX0hyS5Irk1ycZO8BHOe2JBtPov+cJB9KclOS65JcluSFKzPWGMeYl+S6Udp/nWRRkhuSHJ1krdH6j7Dvq4e1nZzk2iSHrGrMkiRJklaO39M5DZIE+ApwfFW9urVtBvz5dMbV/D0wF9iuqu5Psimwx8N4/Juran6SdYCzgZcAV01gv3nAq4EvACR5AvDMqtpsogdOsk5VPTDpiCVJkiSNypnO6fEc4DdVdXSvoaqWVNXHAZI8IsmxSRYnuTrJnuO0PzLJqW1W75QklybZcfhBkyxsM5eLknw6ydrDtj8SOBB4S1Xd3+K6o6pOHWGst7eZ0OuSvK21PWhGMsk7kxzRXu+Q5JokFwN/PV6CWvF3EfDkYcedl+R7Sa5qP89smz4EPKud2yHAWcDj2/tnJZmf5JKWozOSPKaNd26Sf0hyHnBwe/+RJOcn+X6SnZKc3mZ+PzBe3JIkSZIezJnO6bEtY8/e/TVAVf1Rkq2Bs5JsNUb7XwH3VNVTk2wHLBo+YJKnAPsCu1XVsiSfAvYDPt/X7cnAf1fVvWMFn2QH4HXALkCAS1vRds8Yux1LV8yel+SoscZvx3gk8FzgfcM23QnsVVVLk2wJnAzsCLwbeGdVvajtfwZwZlXNb++v7Tv++4HDgbe1MTeqqj1avz+j+weBZyc5GPgqsANwN3Bzko9U1c9Gi3vZsmUMDQ2Nel7jbZ8tzIP0UP5ddMyDOegxD51B5mHu3LkDGVcazqJzNZDkk8DudMXOTu31xwGq6gdJlgBbjdP+b639ulZgDfdcuuLp8m51L+vTFXArY3fgjKr6VYv/dOBZwNdGOb8N6Qq781rTCcALRxl7iySLgAK+WlXfTDKvb/sc4BNJ5gPL6c5/TCMc/3jgtL4upwzbpXcei4Hrq2qojXML8P+AUYvOOXPmjHkBHxoa8gLPmp+HJdMdgGak8a4fs8Wafn2YCuagYx465kEzgUXn9LgeeFnvTVX9dXtAzxWtKaPsN9n24X2Or6r3jNHnR8CTkjy6qn45zlgjeYAHL9l+RF//mkCM0O7pHGP7IcAdwPbtWEsnOO5YfjXs/f3tvyv6Xvfe+zcjSZIkTYL3dE6Ps4FHJHlTX9sj+16fT7f0lbZ89knAjWO0XwC8orVvA/zRCMf8LrBPkse3fo9tDy/6rar6P+CzwMeSrNv6zU2ycNhY5wMvafeSPgrYG/geXTH4+CSPS7Ie8KI27s+BXyTZve2/37gZGt2GwFBVrQD2B3r3pf4SePRIO1TVL4B7kjyrNe0PnDdSX0mSJElTy6JzGlRV0T2VdY8ktya5jG7J59+0Lp8C1k6ymG7p5wHtwT5jtW/SltX+DXAt8Ithx7wBOIzuPtBrgW/TPaV2uMOAnwI3tIcCfaW97x/rKuA44DLgUuCYqrq6qpYB729tZwI/6NvtdcAn24OEfj3xbD3Ep4DXJrmEbmltb5byWuCB9rCikb4i5bXAUe3c57c4JUmSJA1YuvpHa7L2FNo57eE6W9DNam5VVb+Z5tBmnRNPPLEWLhw+Mfw73pfRWdPzsOSow6c7BM1A6y48aI3+u5gqa/r1YSqYg4556Aw4DxO5RUtaZd6fNjM8EjgnyRy6i8ebLDglSZIkrQ4sOmeA9tCfh3wvpyRJkiRNN+/plCRJkiQNjDOdkjRJmx165JSM4/1KHfPQGdSXv0uSNN2c6ZQkSZIkDYxFpyRJkiRpYCw6JUmSJEkDY9EpSZIkSRoYHyQkSSNYctThD89xHpajrP7MA6y78KDpDkGSpIFwplOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQNj0SlJkiRJGpgZX3QmeUKSLya5OckNSb6RZKvpjmtlJdkgyb+387k6yZVJDpziY2yU5K/63i9IcuYE931/kue11+cmmTfB/f6w9V+U5PtJ/mOlgn/ouL+NPckRSd45FeNKkiRJmpgZ/T2dSQKcARxfVa9sbfOBTYEfTmNoq+IY4BZgy6pakWQT4PVTfIyNgL8CPjWZnZKsXVXvW8ljfgz4SFV9tY31Rys5jiRJkqTVyIwuOoE9gWVVdXSvoaoWwW8L0n8GXggU8IGqOiXJAuBI4A5gPnA6sBg4GFgfeElV3ZzkOGApsC1dEfv2qjqzzeydADyqHfLNVXVRG/cI4C5gO+BKYCHwnNZn7xbXXsCbquqlw08myRbAzsCrq2pFO5+fAv/Utm8AfBV4DDAHOKyqvprk74G7qurfWr8PtvP73Ej9gQ8BWyRZBHwb+E9ggyRf6o+9qirJbW2c5wOfSPIC4Myq+hJwN7A8ydrAZ4EdW64/V1UfGXZ6c4Ef9/2eFrdYJ5XPFtMLgI+2bVcNO872Sc4G/h/wz1X1mTE+Cx9reXt/kj8G3gss6OV+JMuWLWNoaGi0zeNuny3Mg/RQ/l10zIM56DEPnUHmYe7cuQMZVxpuphedvWJkJC+lKyq3BzYGLk9yftu2PfAUuqLpFuCYqto5ycHAW4C3tX7zgD2ALYBzkjwZuBPYq6qWJtkSOJmu2AJ4Gl2RejtwIbAbcDbwySSbtALydcCxo8S8LXDNGEXPUmDvqro3ycbAJUm+RlfwnQ78W5K1gFfSFa+j9X83sF1VzYduieoosV/QO25V7d76vqAXTK9wTrID8MSq2q6932iE2D8CnJ3kIuAs4Niq+vlk85nkCuAzdMX8j4BThh3nqcAz6IrYq5P8J7ArI38W3t1ef49uJvZPxio4AebMmTPmBXxoaMgLPGtGHpZMdwCadca7fswWa8L1YdDMQcc8dMyDZoIZf0/nGHYHTq6q5VV1B3AesFPbdnlVDVXV/cDNdEUQdDOe8/rGOLWqVlTVTXTF6dZ0M4afSbIYOA3Ypq//ZVX141a4LALmVVXRzeQtbMXYrsA3J3ICSd7b7oG8vdcE/EOSa4HvAE8ENq2q24CfJXka3Yzk1VX1s9H6j3K4h8Tet214YTfcLcDmST7eitJ7h3eoqmPpCv3TgAV0BfB6TDKfdL+DW6vqppbbE4cd6qtV9euqugs4h674HvGzUFX/BxxIN9v7iaq6eZzzlCRJkjTMTJ/pvB7YZ5RtGWO/+/ter+h7v4IH56yG7VfAIXRLV7enK+qXjjLu8r6xjgW+3vqeVlUPjBLXDXTLQ9dqxe4HgQ8mua9t3w/YBNihqpa1pa+PaNuOAQ4AnkC3HHa8/sONFjvAr0bZB4CquifJ9sAfA38NvIIR7kOtqttbbJ9Lch3dTPWfMfl8Dv+9POgwI7wf67PwR8DPgN8fo48kSZKkUcz0mc6zgfX6n+6aZKckewDnA/smWbs9jOfZwGWTHP/lSdZq91puDtwIbAgMtdm3/YG1xxukFVu3A4cBx43R70fAFcAH2n2SJHkEvyuaNgTubAXknsBmfbufAbyAbjb3W+P0/yXw6PHinqi2dHetqvoy8HfA00fo84Ikc9rrJwCPA/6XyefzB8AftN8JwKuGbX9xkkckeRzdjOrljPJZSLIZ8A66ZbwvTLLLJE9dkiRJmvVm9Exne6jM3sBHk7ybbpbsNrp7Ms+nW8p6Dd1s17uq6idJtp7EIW6kW4q5KXBQu+/wU8CXk7ycbvnmmLOAfU4CNqmqG8bp9wbgKOBHSe4Gfg38Td8YX2/3NS6iK8AAqKrfJDkH+HlVLR+rf1X9LMmFbbbxm3QPEloVTwSObfeTArxnhD7Pp7vntDeTeWj7fUwqn+138EbgP5PcRXff6XZ9XS6jO58nAX9fVbcnOYNhnwW62dVvA+9sff4COC7JTlXVP9sqSZIkaQzpbnvTZLWn1/ae0joV432C7l7Lz07FeCOMvxbdk1xf3u5B1QCceOKJtXDhwlG3+zCAzpqQhyVHHT7dIWiWWXfhQav938XDYU24PgyaOeiYh86A8zDWLUbSlJnpy2vXCEmupHuq6vCH3kzV+NvQPcn1uxackiRJkh5OM3p57SBV1QFTONYOw9uSXAqsN6x5/973V05y/Bvo7jmVJEmSpIeVRedqqqp8aI0kSZKkNZ5FpySNYLNDjxz4MbxfqWMeOkNDQ9MdgiRJA+E9nZIkSZKkgbHolCRJkiQNjEWnJEmSJGlgLDolSZIkSQPjg4QkzXpLjjp8+o49bUdevZgHWHfhQdMdgiRJA+FMpyRJkiRpYCw6JUmSJEkDY9EpSZIkSRoYi05JkiRJ0sBYdEqSJEmSBsaiU5IkSZI0MBada5AkT0jyxSQ3J7khyTeSbDXdcU1WkkuTLEry30l+2l4vSjJvQMf722HvR8xjkjOSvKSv341JDut7/+UkLx1EjJIkSdJMZdG5hkgS4Azg3Kraoqq2Af4W2HR6I5u8qtqlquYD7wNOqar57ee2sfZLsrLfK/vbonOcPF4EPLP1exxwH7Br3zi7tj6SJEmSJmhl/ydeD789gWVVdXSvoaoWpXMU8EKggA9U1SlJFgBHAncA84HTgcXAwcD6wEuq6uYkxwFLgW3pCq+3V9WZbdbxBOBR7XBvrqqL2rhHAHcB2wFXAguB57Q+ewMk2Qt4U1VNaGYwyZ8BhwHrAj8D9quqO5IcAfw+MA+4K8nBwBeAxwGXAy8Adqiqu5IsBN7axrgU+Cvgg8D6SRYB1wOfHSmPLYblwD+35mcCZwIvbIXqPODXVfWTsc5j2bJlDA0NrfT22cI8SA/l30XHPJiDHvPQGWQe5s6dO5BxpeEsOtccvQJvuJfSFZXbAxsDlyc5v23bHngKcDdwC3BMVe3cCre3AG9r/eYBewBbAOckeTJwJ7BXVS1NsiVwMrBj6/80uiL1duBCYDfgbOCTSTapqp8CrwOOncT5XQA8o6oqyRuAdwHvaNt2AHavql8n+QRwdlX9Y5IXAG8ESPIUYF9gt6paluRTdIXru5O8uc2skuSto+SR1r5dknXpis7zgM1bDp/WznVMc+bMGfMCPjQ05AWe1S8PS6Y7AInxrx+zxep2fZgO5qBjHjrmQTOBReeab3fg5KpaDtyR5DxgJ+Be4PKqGgJIcjNwVttnMd3Mac+pVbUCuCnJLcDWwK3AJ5LMB5YD/feOXlZVP27jLgLmVdUFSU4AFiY5lm4p6msmcR7/H3BKkrl0M5W39m37WlX9uu989waoqv9Kck9rfy5dcXp5NzHJ+nSF84RV1f1JrgeeDjyDbtZzc7oC9Gm4tFaSJEmaNIvONcf1wD4jtGeMfe7ve72i7/0KHvy7r2H7FXAI3dLc7enu/V06yrjL+8Y6Fvh663taVT0wRmzDfRz416r6Wt8S3p5f9b0e7XwDHF9V7xnnOKPlseci4NnAo6vqniSXAG+mKzqPHmM/SZIkSSPwQUJrjrOB9ZIc2GtIshNwD7BvkrWTbEJXMF02ybFfnmStJFvQzezdCGwIDLUZ0P2BtccbpKpup1tyexhw3CRj2BD43/b6tWP0uwB4BUCS5wOPae3fBfZJ8vi27bFJNmvbliWZ016PmMcke7S3FwJ/CVzT3l9LN+v5JLqCVZIkSdIkWHSuIaqq6JaV7tW+6uN6utnAL9AVRtfQFVTvGu9hNyO4ke7+xW8CB1XVUuBTwGvbTN9WPHi2cSwnAf9TVTdMMoYjgNOSfI/uIUWjORJ4fpKr6B6eNAT8sh3vMOCsJNcC3wZ6N0D8B3BtkpPGyOPtre9FdIX3xQBttvZO4IpWgEuSJEmahHT/D67Zqj299syq+tIUjfcJ4Oqq+uxUjDfC+OsBy6vqgSS7Av/ee0jQ6uDEE0+shQsXjrrdhwF0Vrc8LDnq8OkOQWLdhQetVn8X02V1uz5MB3PQMQ+dAedhrNu0pCnjPZ2aMkmupJsRfcd4fVfBk4BTk6wF/AY4cJz+kiRJkqaRRecsV1UHTOFYOwxvS3IpsN6w5v2ravFKHuMmuof6SJIkSVoDWHRqoKpql+mOQZIkSdL0seiUNOttduiR03Jc71fqmIfO0NDQdIcgSdJA+PRaSZIkSdLAWHRKkiRJkgbGolOSJEmSNDDe0ylpVlpdvptzyXQHsJowD933dEqSNBM50ylJkiRJGhiLTkmSJEnSwFh0SpIkSZIGxqJTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDYxF5wyX5AlJvpjk5iQ3JPlGkq2mO66VkeS2JBuv5L7HJNmmvf7bqY1MkiRJ0mgsOmewJAHOAM6tqi2qahvgb4FNpzeyh19VvaGqbmhvLTolSZKkh4lF58y2J7Csqo7uNVTVIuCCJEcluS7J4iT7AiRZkOS8JKcm+WGSDyXZL8llrd8Wrd9xSY5O8r3W70WtfV5ru6r9PLNv3HOTfCnJD5KclM5zk5zRiy3JXklOH++k2nG+n+QzSa5PclaS9ZM8Jcllw/pd216fm2THJB8C1k+yKMlJbdtXklzZxnpj3/7PT3JxO5fTkmywKr8MSZIkaTZaZ7oD0EBtB1w5QvtLgfnA9sDGwOVJzm/btgeeAtwN3AIcU1U7JzkYeAvwttZvHrAHsAVwTpInA3cCe1XV0iRbAicDO7b+TwO2BW4HLgR2A84GPplkk6r6KfA64NgJntuWwKuq6sAkpwIvq6oTk6ybZPOqugXYFzi1f6eqeneSN1fV/L7m11fV3UnWb7n4MhDgMOB5VfWrJH8DvB14/1hBLVu2jKGhoZXePluYB+mh/LvomAdz0GMeOoPMw9y5cwcyrjScRefstDtwclUtB+5Ich6wE3AvcHlVDQEkuRk4q+2zmG7mtOfUqloB3JTkFmBr4FbgE0nmA8uB/ntHL6uqH7dxFwHzquqCJCcAC5McC+wKvGaC53Brm7WFrrCe14sLeAXwIbqic98JjPXWJHu31/+PrqDdGNgGuLBbpcy6wMXjDTRnzpwxL+BDQ0Ne4Fk98rBkWo8uPdR414/ZYnW4Pkw3c9AxDx3zoJnAonNmux7YZ4T2jLHP/X2vV/S9X8GDPy81bL8CDgHuoJstXQtYOsq4y/vGOhb4eut7WlU9MEZso8W5HFi/vT4FOK0t062qummsQZIsAJ4H7FpV/5fkXOARdDn6dlW9aoLxSJIkSRqB93TObGcD6yU5sNeQZCfgHmDfJGsn2QR4NnDZKGOM5uVJ1mr3eW4O3AhsCAy1GdD9gbXHG6SqbqdbcnsYcNwkYxhpvJvpitC/oytAR7IsyZz2ekPgnlZwbg08o7VfAuzWlg2T5JFr6lN/JUmSpOnkTOcMVlXVlo1+NMm76WYTb6O7L3MD4Bq6Gcp3VdVPWtE1UTcC59E9Cfegdh/np4AvJ3k5cA7wqwmOdRKwSd/TZVfVKcBRwB+Msv0/gGuTXAW8HjioPXDoRrpik6r6aZIDgJOTrNf2Owz44RTFKEmSJM0KFp0zXJtJfMUImw5tP/19zwXO7Xu/YLRtwIVVdciw/W8CntrX9J5Rxn3zsFh2Bz4z1nm0/ea1l3fRPSSp1/7hYf0+DAxv6z+XvwH+pm/zC0c53tl097pKkiRJWkkWnZpWSa6kmxF9x3THIkmSJGnqWXRq0qrqgCkca4fhbUkuBdYb1rx/VS2equNKkiRJenhYdGq1U1W7THcMkiRJkqaGRaekWWmzQ4+c7hD87rXGPHQG9eXvkiRNN78yRZIkSZI0MBadkiRJkqSBseiUJEmSJA2MRackSZIkaWB8kJCkGW3JUYdPdwhjWjLdAawmzAOsu/Cg6Q5BkqSBcKZTkiRJkjQwFp2SJEmSpIGx6JQkSZIkDYxFpyRJkiRpYCw6JUmSJEkDY9EpSZIkSRoYi85ZKskTknwxyc1JbkjyjSRbTXdcKyPJBkk+3c7l+iTnJ9mlbbtokmOdm2THwUQqSZIkzT5+T+cslCTAGcDxVfXK1jYf2BT44TSGtrKOAW4FtqyqFUk2B54CUFXPHN45ydpVtfxhjlGSJEmalSw6Z6c9gWVVdXSvoaoWpXMU8EKggA9U1SlJFgBHAncA84HTgcXAwcD6wEuq6uYkxwFLgW3pCti3V9WZSeYBJwCPaod7c1Vd1MY9ArgL2A64ElgIPKf12RsgyV7Am6rqpcNPJMkWwC7AflW1op3LLcAtbft9VbVBO9bhwBAwP8kfAf8E/HE7189U1ceHjf38dt7rATcDr6uq+8ZK7LJlyxgaGlrp7bOFeZAeyr+LjnkwBz3moTPIPMydO3cg40rDWXTOTr0Cb7iX0hWV2wMbA5cnOb9t255u9vBuuoLumKraOcnBwFuAt7V+84A9gC2Ac5I8GbgT2KuqlibZEjgZ6C1hfRpdkXo7cCGwG3A28Mkkm1TVT4HXAceOci7bAosmOHO5M7BdVd2a5E3AHwBPq6oHkjy2v2OSjYHDgOdV1a+S/A3wduD9Yx1gzpw5Y17Ah4aGvMDz8OZhycNyFGnVjXf9mC28TpqDHvPQMQ+aCbynU/12B06uquVVdQdwHrBT23Z5VQ1V1f10s35ntfbFdIVmz6lVtaKqbqIrTrcG5gCfSbIYOA3Ypq//ZVX14zZLuQiYV1VFNzO6MMlGwK7AN6fg/C6rqlvb6+cBR1fVAwBVdfewvs9ocV6YZBHwWmCzKYhBkiRJmlWc6Zydrgf2GaE9Y+xzf9/rFX3vV/Dgz1EN26+AQ+iW5m5P9w8dS0cZd3nfWMcCX299T+sVhyO4Htg+yVq95bVj+FXf64wQK8O2f7uqXjXOmJIkSZLG4Ezn7HQ2sF6SA3sNSXYC7gH2TbJ2kk2AZwOXTXLslydZq91ruTlwI7AhMNSKwv2BtccbpKpup1tyexhw3Bj9bgauAI5sD0giyZZJXjzOIc4CDkqyTtvnscO2XwLs1pYHk+SRa+rTfSVJkqTpZNE5C7Xlq3sDe/W+ZoTugT5fAK4FrqErTN9VVT+Z5PA30i3L/SZwUFUtBT4FvDbJJcBWPHjGcSwnAf9TVTeM0+8NwBOAH7UlvJ+hK1jHcgzw38C1Sa4BXt2/sd1LegBwcpJr6YrQrScYtyRJkqTG5bWzVJtJfMUImw5tP/19zwXO7Xu/YLRtwIVVdciw/W8CntrX9J5Rxn3zsFh2pysgx1RV9wIHjrJtg1GO9QDdg4HePqz/gr7XZ/O7e1olSZIkrQSLTq2WklxJNyP6jumORZIkSdLKs+jUlKmqA6ZwrB2GtyW5lO47M/vtX1WLp+q4kiRJkqaWRafWGFW1y3THIEmSJGlyLDolzWibHXrkdIcwKr/wu2MeOkNDQ9MdgiRJA+HTayVJkiRJA2PRKUmSJEkaGItOSZIkSdLAWHRKkiRJkgbGBwlJWmMsOerw6Q5hyi2Z7gBWE+YB1l140HSHIEnSQDjTKUmSJEkaGItOSZIkSdLAWHRKkiRJkgbGolOSJEmSNDAWnZIkSZKkgbHolCRJkiQNjEXnLJXkCUm+mOTmJDck+UaSraY7rpXRYt+ova4kJ/RtWyfJT5OcOckxfz/Jl9rr+Un+ZEqDliRJkmYJi85ZKEmAM4Bzq2qLqtoG+Ftg0+mNbOVU1Z9U1c/b218B2yVZv73fC/jfyYyXZJ2qur2q9mlN8wGLTkmSJGklrDPdAWha7Aksq6qjew1VtSido4AXAgV8oKpOSbIAOBK4g64AOx1YDBwMrA+8pKpuTnIcsBTYlq6AfXtVnZlkHnAC8Kh2uDdX1UVt3COAu4DtgCuBhcBzWp+9AZLsBbypql460skkuQ3Ysaruak3fBP4U+BLwKuBk4Fmt76OAjwN/RPf5P6KqvprkgLbPI4BHJXk9cCbwdOD9wPpJdgf+sapOGS2xy5YtY2hoaLTN426fLcyD9FD+XXTMgznoMQ+dQeZh7ty5AxlXGs6ic3bqFXjDvZSuqNwe2Bi4PMn5bdv2wFOAu4FbgGOqauckBwNvAd7W+s0D9gC2AM5J8mTgTmCvqlqaZEu6InDH1v9pdEXq7cCFwG7A2cAnk2xSVT8FXgccO4nz+yLwvrak9qnA52hFJ/Be4Oyqen1bkntZku+0bbsCT62qu1uhTFX9Jsn76IraN4934Dlz5ox5AR8aGvICz8rnYckAYpFWF+NdP2YLr5PmoMc8dMyDZgKX16rf7sDJVbW8qu4AzgN2atsur6qhqrofuBk4q7Uvpis0e06tqhVVdRNdcbo1MAf4TJLFwGnANn39L6uqH1fVCmARMK+qim5mdGErDHelm72ckKq6tsX0KuAbwzY/H3h3kkXAuXQzm09q275dVXdP9DiSJEmSxudM5+x0PbDPCO0ZY5/7+16v6Hu/ggd/jmrYfgUcQrc0d3u6f+hYOsq4y/vGOhb4eut7WlU9MEZsI/ka8GFgAfC4vvYAL6uqG/s7J9mF7n5QSZIkSVPImc7Z6WxgvSQH9hqS7ATcA+ybZO0kmwDPBi6b5NgvT7JWki2AzYEbgQ2BoTabuT+w9niDVNXtdEtuDwOOm2QM0C2pfX9VLR7W/i3gLe1hSiR52gTG+iXw6JWIQZIkSZr1LDpnobZ8dW9gr/aVKdfTPdDnC8C1wDV0hem7quonkxz+Rrplud8EDqqqpcCngNcmuQTYionPKJ4E/E9V3TDJGGhLdv9thE1/T7fc99ok17X34zkH2CbJoiT/f3v3HWdHVf9//PVOCKGXUKMoAQSRIqFL74iIFAEDEiBU+fpVASlf/YEYsFEEFRFREEITQpciTUjoEAikEDoBpOyX8gVEShCSz++Pc2529ua23ezdm82+n4/HfezcM2fOnDkzc+6cOWdmh3U2L2ZmZmZmfZmH1/ZRuSfxWxVmHZM/xbhjSc8/lr5vWW0ecF9EHFm2/LOkF/qU/LhKuuUv6tkUOLfWduTlhhSmF6owf+Z6IuIj4DsV4oyi0KMaES+SXrhEfs5z/fJlzMzMzMysPjc6bY4kaTypR/SoVufFzMzMzMy6zo1O6zYRMaIb01q3PEzSQ8DAsuB9Kzy3aWZmZmZmcwg3Oq3XiIgNW50Ha63ljzmx1VnoVv7fa4nLIWnWP383MzNrNb9IyMzMzMzMzJrGjU4zMzMzMzNrGjc6zczMzMzMrGnc6DQzMzMzM7Om8YuEzPqIl077aauz0MFLrc7AHMLlkLgcYN7hh7U6C2ZmZk3hnk4zMzMzMzNrGjc6zczMzMzMrGnc6DQzMzMzM7OmcaPTzMzMzMzMmsaNTjMzMzMzM2saNzrNzMzMzMysadzonAtIWlbS5ZKel/SEpL9LWqXV+eosSQ9JmiDpn5LezNMTJA2pEHeUpD26YZ1DJe1Y+L6zpB/NbrpmZmZmZpb4/3T2cpIEXAtcGBF75bChwDLAMy3MWqdFxIYAkkYA60XE93pgtUOB9YC/5zxcD1zfA+s1MzMzM+sT3NPZ+20FfBIR55QCImICcK+k0yQ9LmmypGEAkraUdJekKyQ9I+lkSftIGpfjrZTjjZJ0jqR7crydcviQHPZo/mxcSHespKskPSXpUiXbSLq2lDdJ20m6ptGNk7SSpFskjc/rXbVCnJ/l/PaT9KKkE3PeJpfiS9pA0v2SHst/vyhpXuAkYFjuUR0maYSks/Iyy0u6Q9Kk/Pfznd47ZmZmZmZ9nHs6e781gPEVwr9J6sVbC1gSeFjS3XneWsCXgLeBqcB5EbGBpMOB7wNH5HhDgC2AlYAxkr4AvAFsFxHTJK0MXEbqKQRYG1gdeA24D9gEuBP4g6SlIuJN4ADggk5s35+BwyLiWUkbAmcDW5dmSjoVWBQ4ICIidfzyVkSsI+m7wNHAwcBTwOYR8amkbYFfRsTukk6g0Kuae1lLzgIuiogLJR0InAnsWiuzn3zyCW1tbV2eb2Z9l+uHxOXgMihxOSTNLIfBgwc3JV2zcm50zr02BS6LiOnA65LuAtYH3gMejog2AEnPA7flZSaTek5LroiIGcCzkqYCqwIvAGflIbzTgeKzo+Mi4pWc7gRgSETcK+liYLikC4CNgP0a2QBJCwEbA1fmxiTAwEKUnwAPRcShZYuWelLHkxrfkBqmF+aGcgADGsjCRoXlLwZOrbfAgAEDalbgbW1tLavgX2rJWs2sUfXqj76ilfXknMJlkLgcEpeDzQ3c6Oz9pgCVXqijCmElHxemZxS+z6DjMRFlywVwJPA6qbe0HzCtSrrTC2ldANyQ414ZEZ/WyFtRP+DdiBhaZf7DwLqSBkXE2xXyUczDz4AxEbFbfjHR2AbzUFReHmZmZmZmVoef6ez97gQGSjqkFCBpfeAd0rOK/SUtBWwOjOtk2nvm5yRXAlYEnib1GLblHtB9gf71EomI10hDbo8HRjW68oh4D3hB0p6QXpokaa1ClFuAk4GbJC1cJ7lFgVfz9IhC+L+BasveD+yVp/cB7m0072ZmZmZmlrjR2ctFRAC7Advlf5kyBRgJ/BWYBEwkNUyPjYj/7WTyTwN3ATeTnqucRnqmcn9JD5KG1n7QYFqXAi9HxBOdzMM+wEGSJpJ6dXcpzoyIK4FzgeslzV8jnVOBX0m6j44N5THAaqUXCZUt8wPgAEmTSA3swzuZdzMzMzOzPk+pzWLWkaRRwI0RcVU3pXcW8FhE/KU70ptTXXLJJTF8+PCq81v6TOdpP23Jes2sMfMOP8zPbeHn18BlUOJySJpcDrUexzLrNn6m05pO0nhSj+hRrc6LmZmZmZn1LDc6raKIGNGNaa1bHibpITq+iRZg34iY3F3rNTMzMzOz1nOj01oiIjZsdR7MzMzMzKz53Og06yOWP+bEVmdhJj+nk7gcEpdD0qx//m5mZtZqfnutmZmZmZmZNY0bnWZmZmZmZtY0bnSamZmZmZlZ07jRaWZmZmZmZk3jFwmZzeVeOu2nrc5CRS+1OgNzCJdD4nKAeYcf1uosmJmZNYV7Os3MzMzMzKxp3Og0MzMzMzOzpnGj08zMzMzMzJrGjU4zMzMzMzNrGjc6zczMzMzMrGnc6DQzMzMzM7OmcaOzB0laVtLlkp6X9ISkv0tapdX56ipJC0n6U96eKZLulrRhq/MFIOlaSRMkPSfpX3l6gqSNO5HG+83Mo5mZmZlZX+D/09lDJAm4FrgwIvbKYUOBZYBnWpi12XEe8AKwckTMkLQi8KUW5wmAiNgNQNKWwNERsVNLM2RmZmZm1ke50dlztgI+iYhzSgERMQFmNkhPBb4GBPDziBidG0wnAq8DQ4FrgMnA4cD8wK4R8bykUcA0YHVSI/aHEXGjpCHAxcCCeZXfi4j7c7ojgbeANYDxwHBg6xyn1GDbDviviPhm+cZIWgnYENgnImbk7ZkKTM3zfwgcmKOfFxG/zfm5GbgX2Bh4FdgFGEJqjG+Qlx0CXB8RX5a0LnAGsFDO7wjgQ2AcsHNEPC3pMuDOiDi31g6QtBRwDvD5HHRERNwnaSHg98B6ufxPjIir8zK/AHYCPgJ2iYjXa63jk08+oa2trcvzzazvcv2QuBxcBiUuh6SZ5TB48OCmpGtWzo3OnlNq3FXyTVKjci1gSeBhSXfneWuReg/fJjXozouIDSQdDnwfOCLHGwJsAawEjJH0BeANYLuImCZpZeAyUsMKYG1SI/U14D5gE+BO4A+SloqIN4EDgAuq5Hl1YEJETC+fkRuKB5AapQIeknQX8A6wMrB3RBwi6Qpg94i4RNK8klbMDddhwBWSBpAag7tExJuShgG/iIgDJX0PGCXpd8Di9Rqc2e+A30TEvZI+D9yay/YnwL8iYs2c/8Vz/AWBByPiOEmnAocAP6+1ggEDBtSswNva2nq8gn+pR9dmZl1Vr/7oK1pRT85pXAaJyyFxOdjcwI3OOcOmwGW5Afd6bqCtD7wHPBwRbQCSngduy8tMJvWellyRexyflTQVWJU09PWsPIx3OlB8fnRcRLyS050ADMmNsYuB4ZIuADYC9uvi9lwbER/k9K8BNgOuB14o9fCSGuFDSvkHvgWcTGp0DgO+SGqs3546g+kPtAFExO2S9gT+QGqYN2JbYLWcFsAikhbO4XuVAiPinTz5H+DGQl63a3A9ZmZmZmaWudHZc6YAe1SZpyrhAB8XpmcUvs+g4/6LsuUCOJI0NHct0kujplVJd3ohrQuAG3LcKyPi0yr5mgKsJalfaXhtQaPbM500TBhgNHBlbqBGRDwraU1gSkRsVJ6IpH6kXsqPgEHAKzXWWdIP2CgiPipLS8xafpCGQ5fCi2VkZmZmZmYN8ttre86dwEBJh5QCJK0vaQvgbmCYpP75ucPNSc8sdsaekvrlZy1XBJ4GFgXacqNwX1JPYU0R8RppyO3xwKga8Z4HHgFOzI02JK0saZe8PbtKWkDSgsBuwD111vs8qWH3E1IDlLwNS0naKKc/QNLqed6RwJPA3sD5eShuPbcB3yt9yT3AlcIXx8zMzMzMuoUbnT0k95jtBmxX+hcjpJf5vEZ6q+0kYCKpcXpsRPxvJ1fxNHAX6UU9h0XENOBsYH9JD5KG1n7QYFqXAi9HxBN14h0MLAs8J2kycC7wWkQ8SmqwjgMeIj2H+lgD6x1NeqHRFQAR8R9S7/ApkiYCE4CN87+ZORg4KiLuITVyj28g/R8A60maJOkJ4LAc/nNgcUmP5/VsVTUFMzMzMzPrFLWPHrTeKr+99saIuKqb0jsLeCwi/tId6fUll1xySQwfPrzq/Ja8SOi0n/bo+sysa+YdfphfFoJfmgIugxKXQ9Lkcqj1SJRZt/EzataBpPGkHtGjWp0XMzMzMzPr/dzonAtExIhuTGvd8jBJDwEDy4L3jYjJ3bVeMzMzMzObO7nRaXVFxIatzoOZmZmZmfVObnSazeWWP+bEVmdhFn5OJ3E5JC6HpK2trdVZMDMzawq/vdbMzMzMzMyaxo1OMzMzMzMzaxo3Os3MzMzMzKxp/EynWS8zt/zfzZdanYE5hMshcTmk/9NpZmY2N3JPp5mZmZmZmTWNG51mZmZmZmbWNG50mpmZmZmZWdO40WlmZmZmZmZN40anmZmZmZmZNY0bnWZmZmZmZtY0bnTWIWlZSZdLel7SE5L+LmmVVuerKyQdLum3he9/kvSPwvfvSzqzJZmrQdKmksZJeip/Di3MGylpRJ4eJekFSRNyvKr/W0TSSZK27YHsm5mZmZn1af4/nTVIEnAtcGFE7JXDhgLLAM+0MGtddT+wT+H7UKCfpP4RMR3YGLiukYQkzRMRn3Z7Dmddz7LAX4FdI+JRSUsCt0p6NSJuqrDIMRFxlaT5gCckXRQRL5Sl2T8iTmh23s3MzMzMzD2d9WwFfBIR55QCImJCRNyj5DRJj0uaLGkYgKQtJd0l6QpJz0g6WdI+uadusqSVcrxRks6RdE+Ot1MOH5LDHs2fjQvpjpV0Ve7FuzTnYRtJ15byJ2k7SddU2Z7HgFUkzS9pUeBDYAKwZp6/MXC/pEMkPSxpoqSrJS1QyPMZksYAp+Tvf5Q0RtJUSVtIOl/Sk5JGFfL0R0mPSJoi6cRC+IuSTszbOVnSqhXy/N/AqIh4NJf/W8CxwI/y/PeBjyosN1/++0FhXSdIuhfYM+d9jzxv3bzPxku6VdLgHD5W0il53z0jabMq5WpmZmZmZlW4p7O2NYDxVeZ9k9RTuBawJPCwpLvzvLWALwFvA1OB8yJiA0mHA98HjsjxhgBbACsBYyR9AXgD2C4ipklaGbgMWC/HXxtYHXgNuA/YBLgT+IOkpSLiTeAA4IJKGY6ITyVNANYH5gceAp4FNpb0BqCIeFnSNRFxLoCknwMHAb/PyawCbBsR03PDcnFga2Bn4Iacp4NzeQyNiAnAcRHxtqT+wB2SvhwRk3J6b0XEOpK+Cxydly1aHbiwLOyRHE5E/Lps3mmSjge+AJwZEW8U5k2LiE3zdu2Q/w7I27ZLRLyZbx78AjgwLzNP3nc7Aj8Fag7J/eSTT2hra+vyfDPru1w/JC4Hl0GJyyFpZjkMHjy4KemalXOjs+s2BS7Lw1Jfl3QXqTH3HvBwRLQBSHoeuC0vM5nUe1pyRUTMAJ6VNBVYFXgBOCsP451OauSVjIuIV3K6E4AhEXGvpIuB4ZIuADYC9quR7/tIPZrzAw+QGp3/D3iTNPwWYI3c2FwMWAi4tbD8lXmbS26IiJA0GXg9Iibn/E0hNaonAN9Seg5zHmAwsBpQanSWemXHkxry5QREhfBKYdA+vHYhUgN344gobdfoCvG/SLq5cHsaTU1/oFizF/M3pMo6ZxowYEDNCrytrW22K/iXZmtpM5tT1as/+oruqCd7O5dB4nJIXA42N3Cjs7YpwB5V5qnGch8XpmcUvs+gY5mXN5wCOBJ4ndRb2g+YViXd6YW0LiD1Mk4jNQprPWt5P/Ad0vDTP5Aam6vlv/flOKNIz1BOVHpJz5aF5T8oS6+4beXbPY+kFUg9mOtHxDu5d3S+CssXt6doCqmn9/pC2LrAEzW2kYh4X9JY0s2BUqOzPO+Q9uOUiNioSlL18mdmZmZmZjX4mc7a7gQGSjqkFCBpfUlbAHcDwyT1l7QUsDkwrpPp7ympX37Oc0XgaWBRoC33gO5L6nmrKSJeIw25PZ7UYKzlfuArwFIR8UZEBKnBuQvtjbOFgbY89HSfysk0bBFSY+9fkpYBvtbJ5f8AjMg9v0haAjgFOLXWQpLmATYEnq+T/tPAUpI2yssNkLR6J/NoZmZmZmZVuNFZQ26Q7QZsp/QvU6YAI0kNvGtJQ0Qnkhqnx0bE/3ZyFU8DdwE3A4dFxDTgbGB/SQ+ShtZW6p2r5FLg5Yio1wP4DqmROaUQ/ACwNGlbAH5Cet7zduCpBtdfbX0TSS8wmgKcT3tvaqPLtwHDgXMlPUVqGJ8fETdUWeS0PPR4Emk4c7WXKpXS/w+pN/sUSRNJw4E37kwezczMzMysOqV2lfW0PMz0xoi4qpvSOwt4LCL+0h3pWddccsklMXz48Krzu+WZztOq/vtRM+vF5h1+mJ/bws+vgcugxOWQNLkcaj0uZtZt/IzaXEDSeFKP6FGtzouZmZmZmVmRG50tEhEjujGtdcvDJD0EDCwL3rf0dlkzMzMzM7Oe4EbnXCoiNmx1HszMzMzMzNzoNOtllj/mxFZnYbb5OZ3E5ZC4HJJm/fN3MzOzVvPba83MzMzMzKxp3Og0MzMzMzOzpvG/TDHrRqeffvqbwEs1oiwJvNVD2ZmTuRwSl0PickhcDonLwWVQ4nJImlkObx111FE7NClts3YR4Y8//vTQ59e//vUjrc7DnPBxObgcXA4uB5eDy8Dl4HLwp+98PLzWzMzMzMzMmsaNTjMzMzMzM2saNzrNetafW52BOYTLIXE5JC6HxOWQuBxcBiUuh8TlYL2eXyRkZmZmZmZmTeOeTjMzMzMzM2saNzrNOknSaZKekjRJ0rWSFivM+7Gk5yQ9LemrhfB1JU3O886UpBw+UNLoHP6QpCGFZfaX9Gz+7F8IXyHHfTYvO2/PbHlHkvaUNEXSDEnrFcKHSPpI0oT8Oacwr8+UQ57XZ46HIkkjJb1aOAZ2LMxrepn0NpJ2yOXxnKQftTo/3UHSi3l/TpD0SA4bJOn2vL9ul7R4IX63HRetJOl8SW9IerwQ1iPbPSedD1XKoc/VC5I+J2mMpCeVficOz+F97pgwa/nrc/3xp7d9gO2BefL0KcApeXo1YCIwEFgBeB7on+eNAzYCBNwMfC2Hfxc4J0/vBYzO04OAqfnv4nl68TzvCmCvPH0O8F8tKocvAV8ExgLrFcKHAI9XWaYvlUOfOh7KymQkcHSF8B4pk970AfrnclgRmDeXz2qtzlc3bNeLwJJlYacCP8rTP6IJdWerP8DmwDoU6sCe2O457XyoUg59rl4ABgPr5OmFgWfy9va5Y8Iff9zTadZJEXFbRHyavz4ILJendwEuj4iPI+IF4DlgA0mDgUUi4oGICOAiYNfCMhfm6auAbfLdy68Ct0fE2xHxDnA7sEOet3WOS162lFaPiognI+LpRuP3wXLoU8dDg5peJj24Ld1lA+C5iJgaEf8BLidt89youC+Lx2p3HhctFRF3A2+XBffEds9R50OVcqhmbi6Htoh4NE//G3gS+Cx98Jgwc6PTbPYcSLrjCOmH5OXCvFdy2GfzdHl4h2VyQ/ZfwBI10loCeLfQ6C2mNSdZQdJjku6StFkO62vl0NePh+8pDUE/vzB0rCfKpLeZW7ajXAC3SRov6dActkxEtEG6GAeWzuHdeVzMiXpiu3vLcdRn64U87HVt4CF8TFgfNE+rM2A2J5L0D2DZCrOOi4i/5TjHAZ8Cl5YWqxA/aoR3ZZlaaXW7Rsqhgjbg8xHxf5LWBa6TtDp9rxzmuuOhqFaZAH8Efpbz8jPgdNINmp4ok95mbtmOcptExGuSlgZul/RUjbjdeVz0Jn3tfOiz9YKkhYCrgSMi4r0anfJzfVlY3+VGp1kFEbFtrfn5gfydgG3yUBdIdxE/V4i2HPBaDl+uQnhxmVckzQMsShqS9AqwZdkyY4G3gMUkzZPvaBbT6nb1yqHKMh8DH+fp8ZKeB1ahj5UDc+HxUNRomUg6F7gxf+2JMultqpVJrxYRr+W/b0i6ljSM+HVJgyOiLQ8XfCNH787jYk7UE9s9x58PEfF6abov1QuSBpAanJdGxDU52MeE9TkeXmvWSZJ2AP4H2DkiPizMuh7YK79JbgVgZWBcHjrzb0lfyc9Z7Af8rbDM/nl6D+DO3Ii9Fdhe0uJ5CNL2wK153pgcl7xstZ62lpC0lKT+eXpFUjlM7WvlQB8+HvJFVMluQOkNlk0vk6ZuWHM8DKys9BbieUkvArm+xXmaLZIWlLRwaZq0bx6n474sHqvdeVzMiXpiu+f486Ev1gs5338BnoyIMwqzfExY3xNzwNuM/PGnN31ID/a/DEzIn3MK844jvW3uafKb5XL4eqQf2OeBswDl8PmAK3Oa44AVC8scmMOfAw4ohK+Y4z6Xlx3YonLYjXQn9WPgdVIjCGB3YArpDXyPAt/oi+XQ146HsjK5GJgMTCJdEA3uyTLpbR9gR9JbLZ8nDdlueZ5mc3tWzOf/xFwXHJfDlwDuAJ7Nfwc147ho8bZfRnrE4JNcLxzUU9s9J50PVcqhz9ULwKakIa2TaL9m2LEvHhP++FM6YM3MzMzMzMy6nYfXmpmZmZmZWdO40WlmZmZmZmZN40anmZmZmZmZNY0bnWZmZmZmZtY0bnSamZmZmZlZ07jRaWZmvZak4yRNkTRJ0gRJG9aJP0rSHrXidDEfIyW9mvPwrKRrJK1WmH9e6bukPSU9KWlM/n5Zzv+R3Z2v7iJpV0kn5OlZylDS+/lvP0lnSnpc0mRJD+f/N4ikF3PYZElPSPq5pIF53lKSbunp7TIzs54xT6szYGZm1hWSNgJ2AtaJiI8lLQnM283rmCciPm0w+m8i4td5uWHAnZLWjIg3I+LgQryDgO9GxBhJywIbR8TyTcpTdzkW2LmBeMOAzwBfjogZkpYDPijM3yoi3pK0EPDn/Nk/It6U1CZpk4i4r9tzb2ZmLeWeTjMz660GA29FxMcAEfFWRLwGIOmE3Mv2uKQ/S1L5wtXiSBor6ZeS7gKOk/SCpAF53iK5x25ArYxFxGjgNuDbhTTXy72FmwLnSDotx1k695BuJmklSbdIGi/pHkmr5uVHSToj946eUifemZLulzS12CMp6djcyzhR0sk5rGI6ZeW0CvBxRLzV4D5pi4gZuRxeiYh3KpTP+8BhwK6SBuXg64B9GliHmZn1Mm50mplZb3Ub8DlJz0g6W9IWhXlnRcT6EbEGMD+pR7RcrTiLRcQWEXEiMBb4eg7fC7g6Ij5pIH+PAh0acRFxEvAIsE9EHEPqPXw+IoZGxD2knr/vR8S6wNHA2YXFVwG2jYij6sQbTGrY7gSUGpdfA3YFNoyItYBTc9xa6ZRskrelEVcA38iN6NMlrV0tYkS8B7wArJyDHgE2a3A9ZmbWi3h4rZmZ9UoR8b6kdUkNla2A0ZJ+FBGjgK0kHQssAAwCpgA3lCVRK87oQrzzSMNLrwMOAA5pMIuz9K7WjJyGnG4MXFnomB1YiHJlRExvIN51uafxCUnL5LBtgQsi4kOAiHi7gXRKBgNvFr5HhTiR031F0heBrfPnDkl7RsQd1Ta7MP0GaWiumZnNZdzoNDOzXisippN6IsdKmgzsL+lyUo/dehHxsqSRwHzF5STNVyfOzOcQI+I+SUNyT2r/iHi8weytTeq9a1Q/4N2IGFpl/gcNxvu4MK3C3/LGYr10Sj4CFi18/z9g8ZkrSMNjZw69zcOdbwZulvQ6qYd1lkanpIWBIcAzOWi+vC4zM5vLeHitmZn1SpK+KGnlQtBQ4CXaG4+lF9ZUelttI3GKLgIuAy5oMG+7A9vnZRpSGm4qac+chiSt1dV4ZW4DDpS0QF5mUCfSeRL4QuH7WGCYpNJLm0YApTfxriPpM3m6H/Bl0j7pIJf52aRe2dIzn6sAjTbozcysF3Gj08zMequFgAuV/v3GJGA1YGREvAucC0wmDYl9uHzBRuKUuZTUu1erEXlkfpbxWWA4sHVEvFkjfiX7AAdJmkga7rvLbMYDICJuAa4HHpE0gfT8ZqPp3A2sXXrRUkTcCNwDjM9pbQL8T467NHCDpMeBScCnwFmFtMbkeeOAfwLfKczbCrip1naYmVnvpIhKj2aYmZlZSX4L7C4RsW+r89IKkn4H3BAR/2jiOu4mlfEsb7s1M7Pezc90mpmZ1SDp98DXgB1bnZcW+iWwYbMSl7QUcIYbnGZmcyf3dJqZmZmZmVnT+JlOMzMzMzMzaxo3Os3MzMzMzKxp3Og0MzMzMzOzpnGj08zMzMzMzJrGjU4zMzMzMzNrGjc6zczMzMzMrGnc6DQzMzMzM7OmcaPTzMzMzMzMmsaNTjMzMzMzM2saNzrNzMzMzMysadzoNDMzMzMzs6Zxo9PMzMzMzMyaxo1OMzMzMzMzaxo3Os3MzMzMzKxp3Og0MzMzMzOzpnGj08zMzMzMzJrGjU4zMzMzMzNrGjc6zczMzMzMrGnc6DQzMzMzM7OmmWsanZJC0umF70dLGllnmV0lrdaNeRglaY88fV4pbUl7SnpS0pj8/TJJkyQd2V3r7k6Sdpb0oyamP7OcujndwyTt181pbinpxjpxhkrasfC9W8ovr3vj2Vlmdsta0vtdXbaBtIdIejxPryfpzGatq0YeRkg6q4fXWfH8l7S5pEclfVrcZ5K2kjSh8Jkmadc871JJT0t6XNL5kgZUWN8SksZIer98WyWtK2mypOcknSlJOXygpNE5/CFJQyqkO3P/FcJGSjo6T38lLzsh138jc/gISW9KekzSs5JurXacS1oqp/GYpM0aKuAmkLRb/o1ZdTbTqfgb0eCyFesiSQvk42ByPg7ulbRQjXS6XE/mff7twvea5215/GapVE9J+oykq5q83g51f9m87SSNz/tlvKStC/NukTRR0hRJ50jq3035KZ5/oyR9KGnhwvzf5eN4yU6k2anjtLDc3yQ9UC1/PaGR3+86yy8r6XJJz0t6QtLfJa1SmH9kro8XnY113J//lp9b3fbblMv91VwXPyvpmuI+rbePc14+02j82chnvXyMlbTebKTflGvPLuSjVdc7s/xm93Sac02jE/gY+GZnKlNgV6DbTxyAiDg4Ip7IXw8CvhsRW0laFtg4Ir4cEb9pJC1J8zQjj9VExPURcXJPrrOWRrc/Is6JiIualX4NQ4GZFx7dWH5bAp1qdHZxmZaLiEci4getzkc9s3us1Dn//wmMAP5aDIyIMRExNCKGAlsDHwK35dmXAqsCawLzAwdXWO004CdApYu9PwKHAivnzw45/CDgnYj4AvAb4JTGt3KmC4FDc77XAK4ozBsdEWtHxMrAycA1kr5UIY1tgKdy3HsaWWl3XcCX2Ru4F9iruxIs+42YHYcDr0fEmhGxBmnffVJjvV2qJ7MhwMwL4wbO2w7xu5uSitcxEfFaRDT7AnMohbq/zFvANyJiTWB/4OLCvG9FxFqk82IpYM8m5e85YBeAXE5bAa92JoGuHKeSFgPWARaTtEJnlp1TSBJwLTA2IlaKiNWA/wcsU4i2N/AwsFtX1xMRpd/rITTxXAF+k39HVgZGA3dKWirnod4+HgHMbHR2Y93VQbPSnZNImqe3XO80w9zU6PwU+DMwS++hpOUl3aHUu3CHpM8r3VnfGTgt3/1ZKX9uyXcl76l3Vzv/4J2V74DdBCxdmDc23804AdgUOEfSaaSLxaXzOjerts58R+YMpd7RU+rEO1PS/ZKmqmMPybFKd1knSjo5h9XdxuIdtlrpF+IvKOmmvJ7HJQ3L4SdIejiH/TlX4uXLVoyTy++Xku4CjpP0gnIvjqRFJL2osl4ddbzL+4O8XyZJurzKNl4p6QbgtrwN5+e8PCZplwrLbJDL4bH894uS5gVOAoblfTqsVH6SFs357JeXX0DSy5IG1NsPSj1LhwFHFo6VWY7jesvkWZtXOT6Oyds7SdKJ5dtbiHe6Ug/cHco/UpIOyctOlHS1pAVy+J55X06UdHcO6y/ptMK6vlNhHTPvSOf9eH4+BqZK+kEh3nBJ4/L2/UkVGhiSTi7s+1/nsG+ovcfsH5KWqbBcxTg5P3+WdBtwUd5fQwvL3Sfpy2VpzSfpAqXz7zFJW+VZHc7/4jIR8WJETAJmVNsXwB7AzRHxYV7m75EB44DlyheIiA8i4l5S47OYx8HAIhHxQF7+ItKNOEgXqhfm6auAbUrnZicsDbTlPEyvdjEREWNIdfehZfkbCpwK7JjLa35Je6u9R++UQtz3JZ0k6SFgo7J0qh2rdeu2HG8hYBNSY26vQviWku6WdG0+3s4pnOvvVzpvytKdedde0vaSHsjxr8zrRNIOkp6SdC/wzSrlPJhCQyIino6Ij/Py++XzYKKki3NYsZ7s7O/KycBmeX8cWXbebqH23vjHlHrYOsQv2/6zJe2cp6+VdH6ePkjSz/P0D/O+flzSETlsiFLP+dnAo8DnCmkumcvx6+o4kmKEUu/OLUo9PacWljlI0jN5f5yrCr1LarDuLy4TEY9FxGv56xRgPkkD87z3cvg8wLxA5PXUqoOq1YnHKY12+AfwxbKsXwaU8rUlcB/pWqm0bCP1afE4fV/SL/Lx9KAq1KPZ7sANwOVUuVFT57z8o9LojKn5uDo/7/NRheU7dc5U2odV8l6yFfBJRJxTCoiICaWbX5JWAhYCjic1PittYyPHeKmXvtK58plKx2zZOupeZ5WLiNGk36Jv5zRK16v9c/k/rlTPHql07q8HXKr2erjuMaFUtzyY83ZSaTtV1vusdK00ol4+CtnfMx+zzyj/hqrKNYaSitfoZWU4Sz0oaZ6c3pY5zq8k/SJPvyjplJyPcZK+kMOXysfyw/mzSQ4vv4Yo1psVrz1Vu87aIR/3EyXdUSudamqU2Wh1HLk3StLu1eJ3WkTMFR/gfWAR4EVgUdJd/ZF53g3A/nn6QOC6PD0K2KOQxh3Aynl6Q+DOPL0zcFKFdX4TuB3oT7oL9G4pPWAssF6F6SHA4w2scxRwI9C/gXhXkm4grAY8l8O/BtwPLJC/D6qVTtl2jQDOqpV+WfzdgXML3xctrjNPX0y669uh3GvEGQucXZh3AbBrnj4UOL1CPkYCR+fp14CBeXqxKtv4SqFcfgkML8UHngEWJP1Q35jDFwHmydPbAleXl1eF8vsbsFWeHgac14n9MHN7ah3HdZapdnxsT7rQV553I7B5hfQC2CdPn1DYriUKcX4OfD9PTwY+Wyz3vL+Oz9MDgUeAFSicC2XlPJJ07A4ElgT+DxgAfCmXwYAc72xgv7L8DgKeBlSWh8ULYQeTj5+yfVUtzkhgPDB//r4/8Ns8vQrwSIVyOwq4IE+vSurFnI+y879KXTaKQr1UNu9OYKcK4QNIF+Cb1Uh35rbm7+sB/yh836ywDx4HlivMex5Ysiy9WbaFjufgCcA7pN6C7wDzVcpHDtuV1JiuVRd9JpfjUqSL9TtprxOC1HtUaburHaujqFO35XjDgb/k6fuBdQrH7DRgRdJvwO2012vVzptRlP1GkI7xu4EFc/j/5GXmA14m9UCL1FN8Y4X8DQXeAB7I21eqV1YnnQtLls6NCvuos78rWxbzQMfz9gZgkzy9UN5HHeKX5Xsv4LQ8PQ54ME9fAHwVWJdUnyyY05sCrE067mYAXymk9T6pB+ohYLvy45N0HE0lXRvMB7xEaqx+hnTNMIh0Dt1D2bGZl2+o7q9x7u1B4VzLYbeSzo+/0v47X6sOqlQnlspogZzH5wr7dlRe74M53XOBiGmLogAADfpJREFULfL2LkkD9WnxOC0c16Xf6FPJ9XqFZf5Bqk9WASZVqR9qnZeXk475XYD3SCM5+pHq4aF04Zyptg9r7LMfkHoHq80/njSCpF8u06U7e4yXjt0q59YIKhyzFdZR8RqqLM7Mci+EHQH8sawuWhe4vRBnseL8zhwTpGuKvfP0YTW28yxgRCfyUTondiSfU1S/xqh6jV5WFtXqwdWBJ4HtgMeAeXP4i8BxeXo/2o+xvwKb5unPA08Wyr94DbFlYZlq154V9z/p9+9lYIXi/q+WTtl2DqG9TqxWZrsBF+bwefO65q8Rf2aajXx6dNhms0XEe5IuIlUWHxVmbUT7Ha+LSSdGB0p3yTYGrizcKCrdlbweuL7CKjcHLouI6cBrku7sTH5rrTO7MiKmNxDvuoiYATyh9juP25Iueks9Im83kE41ldIvmgz8Wqnn4cZoHwa3laRjST+Ig0gXDTeULVsrzuhCvPOAY4HrgAOAQ+rkeRLpztx1eZlKbo+It/P09sDOan/eZD5SpVG0KHChpJVJFe0sz89VMJrU2BxD+gE6ezb2Q93juIpK+2/7/Hksf1+I9EN9d9myM2jfD5cA1+TpNZTu1C6Wl701h98HjJJ0RSHu9sCX1d5bsmhe1zM18nxTpN6ajyW9Qbqg3Ib0Y/RwLrf5SRfbRe+RGgLn5TubpTuqywGjlXr35gVeqLDOWnGuj4hSnXIl8BNJx5Aa/6MqpLUp8HuAiHhK0kukC7D3KsRtSM7XmrSXddHZwN3R4BDUUpIVwqKBedW+dwiPiJMkXUra/98m9QZs2Ym8lFufNNTtTYCc9uak83s6cHWV5aodq1C/biPn+7d5+vL8/dH8fVxETM35uYy036+i+nlTyVdIDbv78nE9L6kBuSrwQkQ8m9O/hLLeYEi9L5JWJJXztqTzYyPSUOyrIuKtHO/t4nJd/F2p5T7gjLxfromIV1S70+Ue4AilZ7ieABbPx/hGpN/wA4FrI+KDnN9rSA2Z64GXIuLBQloDSBeO/x0Rd1VZ3x0R8a+c1hPA8qTGy12lspF0Jek8LdeVup+c5uqk4enbF8Mj4quS5iMNkd+adHFcqw6qVCduRiqjD/O6Kl2nXEP67dmQdPOnpJH6tNx/aK9Tx5Muxsu3dxngC8C9ERFKz6ivERHlz33VOi9vyMtOJg0dn5zTnkK6yF2Ozp8zXd6HVewF7BYRM/KxuSfwh7I49Y7xeiodsy+XxWnkOquSSifnVGBFSb8HbqL9MY5aqh0TG9E+cuavwK8bSKuRfJTq0vGkYwGqX2PUvUavc+0/RWmEyA3ARhHxn8KilxX+/iZPbwusVkhnEbU/U128hiiqde1Zaf8vTvqtfyHnsd417JMV1lmKX6nMbgbOVBqVsUNe10eSunIdN4u5qtGZ/ZZ0QXBBjTiVLpb6Ae9Gev6oM6pdeDWi3jo/aDDex4VpFf6W562r21gp/Zki4hlJ65LuPP1KaQjBqaQL4fUi4mWll4jMV1wu/+DWilPafiLiPqXhUluQ7grXe3D566QKZ2dSA2H1iPi0LM4HhWkBu0fE02V5LF5s/QwYExG7KQ1lHVsnD5AukH4laRDpB/5O0l2sruyHco0ee9WOj19FxJ+6uM5RpF6miUpDY7YEiIjDJG1IKv8JSkMkRbqL3aGxpAovp6mS5+mkukqkO3A/rpq5iE8lbUC6oNoL+B7pgu73wBkRcb3ScJmRFRavFad4LH4o6XbSXfhvke7MluvsUNRGfIt0gdnheT1JPyXd/ezscJdX6DgcdznSCIHSvM8Bryg9x7oo8HbHxfk/0g9g0SAKF8oR8TzwR0nnAm9KWqJKXtam+o9jSa0ynZYvLCoZRYVjNatZt+X8bk26QA7SHfPIF3nQyYZ4FSLdAOswRC+fOw2d4xHxPuli7BpJM0h18Sd1lu/K70qtPJycb/TsCDwoads68V+VtDj5woZ07HyL1CPyb9VusX5Q9v1T0kXoV4Fqjc5qdUojulL3I2k5Uk//fvlc6CAipuWG4i6kRmetOqhS/qH+MXI56ZrowtxAmpk96tSnFXwSuaujLA9Fw0j1wgt5XYuQ6uLjy+KNov55OYOO2z0jr3M6nT9nOrsPp5B6imeh9DjFysDthUbvVMoanfWO8Trrh+r7vJSPetdQtaxN6q0q5vcdSWuRzqP/znk9sE46jRwTRZ/S8dG+WfJbJx+lMimuq9o1xo7UPz/q1YNrknpIy2+8RYXpfqTGaYfGZT5GyuusmbOpfO25IdXrrErbVDGdGiqWWV73WFLZD6O9cd2V67hZzE3PdAIzW/1XkJ6/Kbmf9ucK9iG9EALg38DCebn3SJXknjBzLPhadVZ3N7CX0ljnwaRnADqT14bW2cW83QYcqPbnJAZ1MZ26lN5q9mFEXEK6m7UO7RXJW/lOUqXKu5E4RReRToBaNxRQeq7qc5GeFTuW9juptdwKfL90oSNp7QpxFqX92akRhfCZx1G5fDE4DvgdqRd4eif2Q3m61Y7jWstUcyvp+Cg9B/NZSZWed+hH+375dmGdCwNtSs/V7lOKLGmliHgoIk4gvUjjc3ld/6X2Z3JXkbRgA3ksdwewRymfkgZJWr4YIW/PohHxd9LwoaF5VnHf7V8l/UbilJwHnAk8XN6DlN1NLheltx1+njTUcXbsTfsPADntg0k/DnvnXqlS+AZKoz6qiog24N9Kb5kVaZjQ3/Ls62kvgz1Iw42ibPn3ScfANnmdg0gXV/fm718vNBxWJv1ovluej3wj6VDS8L9aHgK2UHpurz+pPKo1MIoqHqsN2gO4KCKWj4ghEfE5UqN60zx/A0kr5DpnGO3nR7XzppIHgU3U/lzQAvmYeQpYQenZMaj+3Ngm+cIWpecMVyMNxboD+FapoZ/3z0xd/D2oWr/kc39yRJxCuphdtVb87AHSeXo3qVfo6PyXHLZrLo8FScO+qvXkB+midFV17s3h40jH1OJKN1d2rxKv03W/0st0bgJ+HBH3FcIXytcL5HXuSNrX5eupVwdBKqPdlJ6zWxj4RnmEiPgncBypcVJUtz7tor2BHfL5MoR0s7XSc52zc1525ZypuA/zb98dFdZxJzBQ0iGFuOvn+mpv0uNbQ/LnM8Bnq5RfrWO8qNHf7qLOXkMBIGl3Uk9X+e/JkkC/iLiaNHR4ndnI24O0n0/F/f8SqTdwoNJbf7epkL9q+aim2jVG3Wv0WvWgpG8CS5A6MM7M53TJsMLf0luabyPd6C5tx9A6+S7lvd61Z9EDpDprhRy/VK93Np1a12WXk0YUbkb7CIRuuY6b6xqd2emkYTMlPwAOkDQJ2Jf0tj9IBXuM0kO3K5EqvoMkTSTd5doFQOlfYJxUYT3XAs+Shpf+kcYugMpVXOdsxAMgIm4hXTg+ImkC7W+u7FQ6DVoTGJfXcxzw84h4l3QROZk0/O3hCnmsG6fMpaQ7qJfVidcfuERpaM5jpOcy3q2zzM9Iw20mKb184mcV4pxK6rW8L6+jZAypEp2gspdJZKNJz4UVhws3sh9uIF1QTFB6YL7acVxrmYoi4jbSkJcHcjldReUflQ+A1SWNJ/X4lM6Dn5AaAbfTfsEE6cVck3MZ3g1MJDXQngAezeF/ogujLCK9iOZ40oufJuV1Dy6LtjBwY55/F+0vFhtJGj5zD6kxXEkjcUp5GU8aKlvtBsjZQP9ctqNJz6x8XCUuMPOC5hXSMK0/KQ0lK80bQmrAl9cx55DuwD6Q9/kJOfzzFB4xkPQicAYwQtIran8t/X+R9s9zpOc2b87hfwGWkPQc8EOg2oX8fsDx+dy/Ezix0KOzL/B0nncx6RnHUm9k6eUrz5DeCLl7RNTs6cyN5B+TzreJwKMR8bday2TVjtVG7E2q54uupv0tkw+QXgDyOKkxWopb7byZRaThwiOAy/Jx+yCwakRMIzXGb1J6KcpLVZJYCbirUN89QnpebQrwizxvImn/l+vs78Ek4FOlF1gcWTbvCOWXiJGOvZvrxId08T1PRDxH6o0blMOIiEdJvWHjSPvvvIh4rEIa5PjTSRe3W0n6bp3tKC3zKulZqIdIzyE+AfyrQtSu1P3fIw0z/YnaX7C0NGmky/V5X08kDWktvaxmJA3WQTn/j5Lqlwmk47Jiozwi/lTe09pgfdopuZ76POkYLq3nBeA9pZ6boi6fl108Z6rtw8EUXq5UWEeQbnRsp/QvU6aQ9s9rpOOsvF64lsqN66rHeJl658osOnkNdWQ+Bp8lXY9sncux6LPA2FxnjyLVt+Tpc/Ly8zeSN1JD+4eSxpHK+F85zy+TOoYmka7pKp3T1fJRTbVrjEav0WepB3PD92TgoIh4hvTs6e8KywxUenHd4bRfZ/wAWE/pRTtPkJ5lraeRa8+Z8j47lDSqZSLt15WdSofa12W3kRra/4j2IcV1r+OU/k3V32uttPTAutkcT2ks+S4RsW+r82J9m1Lv/ljShU6tt822hNKbsi+O9DZcawKl4Y9HR8ROFea9HxH1RlfYHEDSQhHxvlKv47XA+RFR3qCwuZSk7wH/jPTuDusmSqPsPoqIkLQXaTROd3RytFy+ibte5OflrXFz4zOdNhdSeqD8a1T/n2hmPULSfqQepB/OiQ1OgIg4ptV5MOslRio9fzof6Q7/da3NjvWkiDir1XmYS60LnCVJpMcq6j0ban2AezrNzMzMzMysaebWZzrNzMzMzMxsDuBGp5mZmZmZmTWNG51mZmZmZmbWNG50mpmZmZmZWdO40WlmZmZmZmZN40anmZmZmZmZNc3/BzUzFVqx9BeUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 20))\n",
    "ax = sns.barplot(y=results.pvalues.index[1:][reject],x=results.params.values[1:][reject], order = order, color = light[8])\n",
    "ax.set_axisbelow(True)\n",
    "ax.set_xlabel('Salary Difference (USD)')\n",
    "txt = 'Note: difference in salary is relative to the baseline salary of 172,100 USD for an Applied Scientist working at 23andMe in Alameda, CA with a Distinguished experience level.'\n",
    "ax.text(.5, 48, txt, ha='center', color = dark_bright[0])\n",
    "\n",
    "ax.spines[\"bottom\"].set_color(light[0])\n",
    "ax.spines[\"left\"].set_color(light[0])\n",
    "ax.xaxis.label.set_color(dark_bright[0])\n",
    "ax.yaxis.label.set_color(dark_bright[0])\n",
    "ax.title.set_color(dark_bright[0])\n",
    "ax.tick_params(axis ='x', colors = light[0], labelcolor=dark_bright[0])\n",
    "ax.tick_params(axis='y', colors = light[0], labelcolor=dark_bright[0])\n",
    "ax.yaxis.set_ticks_position('none')\n",
    "ax.grid(color = grid[0])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f593b3f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistically significant predictors count:\n",
      "Company: 20\n",
      "Qualifications: 18\n",
      "Title: 5\n",
      "Location: 3\n",
      "Experience level: 0\n"
     ]
    }
   ],
   "source": [
    "company = 0\n",
    "title = 0\n",
    "location = 0\n",
    "levels = 0\n",
    "qualifications = 0\n",
    "for i in results.pvalues.index[1:][reject]:\n",
    "    if 'Company' in i:\n",
    "        company += 1\n",
    "    elif 'Title' in i:\n",
    "        title += 1\n",
    "    elif 'Location' in i:\n",
    "        location += 1\n",
    "    elif 'Levels' in i:\n",
    "        levels += 1\n",
    "    else:\n",
    "        qualifications += 1\n",
    "\n",
    "print('Statistically significant predictors count:')        \n",
    "print('Company: {}'.format(company))\n",
    "print('Qualifications: {}'.format(qualifications))\n",
    "print('Title: {}'.format(title))\n",
    "print('Location: {}'.format(location))\n",
    "print('Experience level: {}'.format(levels))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7dcaeca",
   "metadata": {},
   "source": [
    "Experience level predictors do not have a p-value that indicate statistical significance in predicting salary across California, because other predictors have a larger impact (i.e., company, location, and title). For instance, a senior level data scientist position in San Bernadino, CA and a senior level data scientist position in San Francisco, CA will have a large difference in salary regardless of seniority. Therefore, experience level is not a useful predictor for predicting salary across all of California."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ff5a2ef",
   "metadata": {},
   "source": [
    "## Assumptions of OLS\n",
    "\n",
    "1. linear relationship\n",
    "2. Multivariate normality\n",
    "3. No or little multicollinearity\n",
    "4. No auto-correlation\n",
    "5. Homoscedasticity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "469cf0d0",
   "metadata": {},
   "source": [
    "### Testing linearity and homoscedasticity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c5d434fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def linearity_test(model, y):\n",
    "    '''\n",
    "    Function for visually inspecting the assumption of linearity in a linear regression model.\n",
    "    It plots observed vs. predicted values and residuals vs. predicted values.\n",
    "    \n",
    "    Args:\n",
    "    * model - fitted OLS model from statsmodels\n",
    "    * y - observed values\n",
    "    '''\n",
    "    fitted_vals = model.predict()\n",
    "    resids = model.resid\n",
    "\n",
    "    fig, ax = plt.subplots(1,2, figsize=(14,5))\n",
    "    plt.subplots_adjust(hspace = 0.25, wspace = .5)\n",
    "    \n",
    "    sns.regplot(x=fitted_vals, y=y, lowess=True, ax=ax[0],\n",
    "                line_kws={'color': dark_bright[8]},\n",
    "                scatter_kws = {'color': medium[1], 'facecolors': 'none'})\n",
    "    ax[0].set(xlabel='Predicted', ylabel='Observed')\n",
    "    ax[0].spines[\"bottom\"].set_color(light[0])\n",
    "    ax[0].spines[\"left\"].set_color(light[0])\n",
    "    ax[0].xaxis.label.set_color(dark_bright[0])\n",
    "    ax[0].yaxis.label.set_color(dark_bright[0])\n",
    "    ax[0].title.set_color(dark_bright[0])\n",
    "    ax[0].tick_params(axis ='x', colors = light[0], labelcolor=dark_bright[0])\n",
    "    ax[0].tick_params(axis='y', colors = light[0], labelcolor=dark_bright[0])\n",
    "\n",
    "    sns.regplot(x=fitted_vals, y=resids, lowess=True, ax=ax[1],\n",
    "                line_kws={'color': dark_bright[8]},\n",
    "                scatter_kws = {'color': medium[1], 'facecolors': 'none'})\n",
    "    ax[1].set(xlabel='Predicted', ylabel='Residuals')\n",
    "    ax[1].spines[\"bottom\"].set_color(light[0])\n",
    "    ax[1].spines[\"left\"].set_color(light[0])\n",
    "    ax[1].xaxis.label.set_color(dark_bright[0])\n",
    "    ax[1].yaxis.label.set_color(dark_bright[0])\n",
    "    ax[1].title.set_color(dark_bright[0])\n",
    "    ax[1].tick_params(axis ='x', colors = light[0], labelcolor=dark_bright[0])\n",
    "    ax[1].tick_params(axis='y', colors = light[0], labelcolor=dark_bright[0])\n",
    "    \n",
    "linearity_test(results, y.astype(float))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12e61757",
   "metadata": {},
   "source": [
    "The right plot contains a red trend line which is horizontal at zero. The left plot demonstrates an almost linear relationship between the actual/observed and predicted values. This demonstrates linearity.\n",
    "\n",
    "The right plot has non-constant variance of the errors which means that the assumption of homooscedasticity does not hold."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e94f8ad9",
   "metadata": {},
   "source": [
    "### Testing independence\n",
    "\n",
    "Durbin-Watson test for independence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fb40ef5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8871027217462704"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "durbin_watson(results.resid, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e962195e",
   "metadata": {},
   "source": [
    "A Durbin-Watson statistic between 0 and 2 has slight positive autocorrelation. A Durbin-Watson statistic of 2 means there is no autocorrelation. Since the statistic is close to 2, independence is satisfied."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72f72eea",
   "metadata": {},
   "source": [
    "### Testing multicollinearity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "858dab80",
   "metadata": {},
   "source": [
    "Next, perform $\\chi^{2}$ tests to determine collinearity among variables. An explanation of contingency table creation and $\\chi^{2}$ is given in the diagram below."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "253e69c1",
   "metadata": {},
   "source": [
    "![alt text](images/chi-square-test.jpg \"Chi-square test\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8d717214",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Title and Company:\n",
      "p-value = 4.1871062576112276e-126\n",
      "Variables are dependent (reject H0)\n",
      "\n",
      "Title and Location:\n",
      "p-value = 3.313275575434028e-59\n",
      "Variables are dependent (reject H0)\n",
      "\n",
      "Title and Levels:\n",
      "p-value = 2.906697386608136e-82\n",
      "Variables are dependent (reject H0)\n",
      "\n",
      "Company and Location:\n",
      "p-value = 0.0\n",
      "Variables are dependent (reject H0)\n",
      "\n",
      "Company and Levels:\n",
      "p-value = 0.013575918831914615\n",
      "Variables are dependent (reject H0)\n",
      "\n",
      "Location and Levels:\n",
      "p-value = 0.0001587483525958263\n",
      "Variables are dependent (reject H0)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#perform chi-square tests between every variable except salary\n",
    "for i in range(len(df_1.columns)-1):\n",
    "    for j in range(len(df_1.columns)-1-i):\n",
    "        if df_1.columns[i] == 'Salary' or df_1.columns[j+i+1] == 'Salary':\n",
    "            pass\n",
    "        else:\n",
    "            contingency = pd.crosstab(df_1[df_1.columns[i]], df_1[df_1.columns[j+i+1]])\n",
    "            stat, p, dof, expected = chi2_contingency(contingency)\n",
    "\n",
    "            alpha = 0.05\n",
    "            print('{} and {}:'.format(df_1.columns[i], df_1.columns[j+i+1]))\n",
    "            print(\"p-value = \" + str(p))\n",
    "            if p <= alpha:\n",
    "                print('Variables are dependent (reject H0)\\n')\n",
    "            else:\n",
    "                print('Variables are independent (H0 holds true)\\n')\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "127a82db",
   "metadata": {},
   "source": [
    "With an $\\alpha$ of 0.05, all null hypotheses are rejected (where the null hypotheses are that the variables do not depend on each other)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "194ecff8",
   "metadata": {},
   "source": [
    "### Testing normality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d18b3462",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jarque-Bera test ---- statistic: 4342.2936, p-value: 0.0\n",
      "Shapiro-Wilk test ---- statistic: 0.7435, p-value: 0.0000\n",
      "Kolmogorov-Smirnov test ---- statistic: 0.2673, p-value: 0.0000\n",
      "Anderson-Darling test ---- statistic: 140.6420, 5% critical value: 0.7850\n",
      "If the returned AD statistic is larger than the critical value, then for the 5% significance level, the null hypothesis that the data come from the Normal distribution should be rejected. \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\malex\\anaconda3\\lib\\site-packages\\statsmodels\\graphics\\gofplots.py:993: UserWarning: marker is redundantly defined by the 'marker' keyword argument and the fmt string \"bo\" (-> marker='o'). The keyword argument will take precedence.\n",
      "  ax.plot(x, y, fmt, **plot_style)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def normality_of_residuals_test(model):\n",
    "    '''\n",
    "    Function for drawing the normal QQ-plot of the residuals and running 4 statistical tests to \n",
    "    investigate the normality of residuals.\n",
    "    \n",
    "    Arg:\n",
    "    * model - fitted OLS models from statsmodels\n",
    "    '''\n",
    "    fig, ax = plt.subplots()\n",
    "    plt.rc(\"figure\", figsize=(7,7))\n",
    "    sm.ProbPlot(model.resid).qqplot(line='s', marker='o', markerfacecolor='None', markeredgecolor= medium[1], ax=ax)\n",
    "    ax.set_title('Q-Q plot')\n",
    "    ax.spines[\"bottom\"].set_color(light[0])\n",
    "    ax.spines[\"left\"].set_color(light[0])\n",
    "    ax.xaxis.label.set_color(dark_bright[0])\n",
    "    ax.yaxis.label.set_color(dark_bright[0])\n",
    "    ax.title.set_color(dark_bright[0])\n",
    "    ax.tick_params(axis ='x', colors = light[0], labelcolor=dark_bright[0])\n",
    "    ax.tick_params(axis='y', colors = light[0], labelcolor=dark_bright[0])\n",
    "\n",
    "    jb = stats.jarque_bera(model.resid)\n",
    "    sw = stats.shapiro(model.resid)\n",
    "    ad = stats.anderson(model.resid, dist='norm')\n",
    "    ks = stats.kstest(model.resid, 'norm')\n",
    "    \n",
    "    print(f'Jarque-Bera test ---- statistic: {jb[0]:.4f}, p-value: {jb[1]}')\n",
    "    print(f'Shapiro-Wilk test ---- statistic: {sw[0]:.4f}, p-value: {sw[1]:.4f}')\n",
    "    print(f'Kolmogorov-Smirnov test ---- statistic: {ks.statistic:.4f}, p-value: {ks.pvalue:.4f}')\n",
    "    print(f'Anderson-Darling test ---- statistic: {ad.statistic:.4f}, 5% critical value: {ad.critical_values[2]:.4f}')\n",
    "    print('If the returned AD statistic is larger than the critical value, then for the 5% significance level, the null hypothesis that the data come from the Normal distribution should be rejected. ')\n",
    "    \n",
    "normality_of_residuals_test(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e6babc62",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_residuals(model, features, label):\n",
    "    \"\"\"\n",
    "    Creates predictions on the features with the model and calculates residuals\n",
    "    \"\"\"\n",
    "    predictions = model.predict(features)\n",
    "    df_results = pd.DataFrame({'Actual': label, 'Predicted': predictions})\n",
    "    df_results['Residuals'] = abs(df_results['Actual']) - abs(df_results['Predicted'])\n",
    "    \n",
    "    return df_results\n",
    "\n",
    "\n",
    "def normal_errors_assumption(model, features, label, p_value_thresh=0.05):\n",
    "    \"\"\"\n",
    "    Normality: Assumes that the error terms are normally distributed. If they are not,\n",
    "    nonlinear transformations of variables may solve this.\n",
    "               \n",
    "    This assumption being violated primarily causes issues with the confidence intervals\n",
    "    \"\"\"\n",
    "    from statsmodels.stats.diagnostic import normal_ad\n",
    "    print('Assumption 2: The error terms are normally distributed', '\\n')\n",
    "    \n",
    "    # Calculating residuals for the Anderson-Darling test\n",
    "    df_results = calculate_residuals(model, features, label)\n",
    "    \n",
    "    print('Using the Anderson-Darling test for normal distribution')\n",
    "\n",
    "    # Performing the test on the residuals\n",
    "    p_value = normal_ad(df_results['Residuals'])[1]\n",
    "    print('p-value from the test - below 0.05 generally means non-normal:', p_value)\n",
    "    \n",
    "    # Reporting the normality of the residuals\n",
    "    if p_value < p_value_thresh:\n",
    "        print('Residuals are not normally distributed')\n",
    "    else:\n",
    "        print('Residuals are normally distributed')\n",
    "    \n",
    "    # Plotting the residuals distribution\n",
    "    plt.subplots(figsize=(12, 6))\n",
    "    plt.title('Distribution of Residuals')\n",
    "    sns.distplot(df_results['Residuals'])\n",
    "    plt.show()\n",
    "    \n",
    "    print()\n",
    "    if p_value > p_value_thresh:\n",
    "        print('Assumption satisfied')\n",
    "    else:\n",
    "        print('Assumption not satisfied')\n",
    "        print()\n",
    "        print('Confidence intervals will likely be affected')\n",
    "        print('Try performing nonlinear transformations on variables')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ba8ead3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Assumption 2: The error terms are normally distributed \n",
      "\n",
      "Using the Anderson-Darling test for normal distribution\n",
      "p-value from the test - below 0.05 generally means non-normal: 0.0\n",
      "Residuals are not normally distributed\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\malex\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Assumption not satisfied\n",
      "\n",
      "Confidence intervals will likely be affected\n",
      "Try performing nonlinear transformations on variables\n"
     ]
    }
   ],
   "source": [
    "normal_errors_assumption(results, X_sm.astype(int), y.astype(float))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f7bbe45",
   "metadata": {},
   "source": [
    "## Assumptions do not hold\n",
    "\n",
    "The assumptions of normality, no multicollinearity, and homoscedasticity do not hold."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}