7. Marketing Email Campaign.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "## Goal of Analysis:\n",
    "\n",
    "### 1. What percentage of users opened the email and what percentage clicked on the link within the email\n",
    "\n",
    "### 2. build a model to optimize in future email campaigns to maximize the probability of users clicking on the link inside the email\n",
    "\n",
    "### 3. By how much do you think your model would improve click through rate ( defined as # of users who click on the link / total users who received the email). How would you test that?\n",
    "\n",
    "### 4. Did you find any interesting pattern on how the email campaign performed for different segments of users? Explain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aaa55b23",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "09514234",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>email_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>284534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>609056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>220820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>905936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>164034</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id\n",
       "0    284534\n",
       "1    609056\n",
       "2    220820\n",
       "3    905936\n",
       "4    164034"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "email_opened_table = pd.read_csv('email_opened_table.csv')\n",
    "email_opened_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "259fe9cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>short_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>US</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>UK</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>11</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>US</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>short_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>6</td>\n",
       "      <td>Monday</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>long_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>US</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id   email_text email_version  hour    weekday user_country  \\\n",
       "0     85120  short_email  personalized     2     Sunday           US   \n",
       "1    966622   long_email  personalized    12     Sunday           UK   \n",
       "2    777221   long_email  personalized    11  Wednesday           US   \n",
       "3    493711  short_email       generic     6     Monday           UK   \n",
       "4    106887   long_email       generic    14     Monday           US   \n",
       "\n",
       "   user_past_purchases  \n",
       "0                    5  \n",
       "1                    2  \n",
       "2                    2  \n",
       "3                    1  \n",
       "4                    6  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "email_table = pd.read_csv('email_table.csv')\n",
    "email_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "04ebe053",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>email_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>609056</td>\n",
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       "      <td>870980</td>\n",
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       "      <td>935124</td>\n",
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       "      <td>158501</td>\n",
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      ],
      "text/plain": [
       "   email_id\n",
       "0    609056\n",
       "1    870980\n",
       "2    935124\n",
       "3    158501\n",
       "4    177561"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "link_clicked_table = pd.read_csv('link_clicked_table.csv')\n",
    "link_clicked_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "63f16edb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((10345, 1), (100000, 7), (2119, 1))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "email_opened_table.shape, email_table.shape, link_clicked_table.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ada47c2",
   "metadata": {},
   "source": [
    "## Part 1: Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f71442a",
   "metadata": {},
   "source": [
    "#### First, I will add a column to indicate those IDs are marked as open or click"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "41639143",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>email_id</th>\n",
       "      <th>email_open</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>284534</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>609056</td>\n",
       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>220820</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>905936</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>164034</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   email_id email_open\n",
       "0    284534          1\n",
       "1    609056          1\n",
       "2    220820          1\n",
       "3    905936          1\n",
       "4    164034          1"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "email_opened_table['email_open'] = '1'\n",
    "email_opened_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b0e5325b",
   "metadata": {},
   "outputs": [
    {
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      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>email_id</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>609056</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>870980</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>935124</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>158501</td>\n",
       "      <td>1</td>\n",
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       "      <th>4</th>\n",
       "      <td>177561</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   email_id link_click\n",
       "0    609056          1\n",
       "1    870980          1\n",
       "2    935124          1\n",
       "3    158501          1\n",
       "4    177561          1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "link_clicked_table['link_click'] = '1'\n",
    "link_clicked_table.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c076798",
   "metadata": {},
   "source": [
    "#### Next, merge three tables together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a3922bb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "      <th>email_open</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>short_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>US</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>UK</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>11</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>US</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>short_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>6</td>\n",
       "      <td>Monday</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>long_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>US</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id   email_text email_version  hour    weekday user_country  \\\n",
       "0     85120  short_email  personalized     2     Sunday           US   \n",
       "1    966622   long_email  personalized    12     Sunday           UK   \n",
       "2    777221   long_email  personalized    11  Wednesday           US   \n",
       "3    493711  short_email       generic     6     Monday           UK   \n",
       "4    106887   long_email       generic    14     Monday           US   \n",
       "\n",
       "   user_past_purchases email_open link_click  \n",
       "0                    5        NaN        NaN  \n",
       "1                    2          1          1  \n",
       "2                    2        NaN        NaN  \n",
       "3                    1        NaN        NaN  \n",
       "4                    6        NaN        NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.merge(left = email_table, right = email_opened_table, on = 'email_id', how = 'left')\n",
    "full_data = pd.merge(left = data, right = link_clicked_table, on = 'email_id', how = 'left')\n",
    "full_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d41d9ec4",
   "metadata": {},
   "source": [
    "#### in this dataset, the null value means those email_id has not open the email or click the link within the emal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbcad9e1",
   "metadata": {},
   "source": [
    "## Part 2: calculate % of users opened the email and % clicked on the link"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5e7e8ac1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.35%\n"
     ]
    }
   ],
   "source": [
    "email_open_rate = 1-(full_data['email_open'].isnull().sum() / len(full_data))\n",
    "\n",
    "print('{percent:.2%}'.format(percent=email_open_rate))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8e1143e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.12%\n"
     ]
    }
   ],
   "source": [
    "link_click_rate = 1-(full_data['link_click'].isnull().sum() / len(full_data))\n",
    "\n",
    "print('{percent:.2%}'.format(percent=link_click_rate))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ff2447e",
   "metadata": {},
   "source": [
    "#### Since the email open rate and link click rate are both quite low, I also want to know, the % of people click the link among the people who open the email"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3131e523",
   "metadata": {},
   "outputs": [],
   "source": [
    "link_click_when_open = full_data[~full_data['email_open'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "33e1f467",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20.00%\n"
     ]
    }
   ],
   "source": [
    "link_click_rate_on_open = 1-(link_click_when_open['link_click'].isnull().sum() / len(link_click_when_open))\n",
    "\n",
    "print('{percent:.2%}'.format(percent=link_click_rate_on_open))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89d51047",
   "metadata": {},
   "source": [
    "#### within the people who open the email, around 20% of them click the link, not that bad"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4126185",
   "metadata": {},
   "source": [
    "## Part 3: build a model to maximize the probability of users clicking the link"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fb2679b7",
   "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>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "      <th>email_open</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>short_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>US</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>UK</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>11</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>US</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>short_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>6</td>\n",
       "      <td>Monday</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>long_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>US</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id   email_text email_version  hour    weekday user_country  \\\n",
       "0     85120  short_email  personalized     2     Sunday           US   \n",
       "1    966622   long_email  personalized    12     Sunday           UK   \n",
       "2    777221   long_email  personalized    11  Wednesday           US   \n",
       "3    493711  short_email       generic     6     Monday           UK   \n",
       "4    106887   long_email       generic    14     Monday           US   \n",
       "\n",
       "   user_past_purchases email_open link_click  \n",
       "0                    5        NaN        NaN  \n",
       "1                    2          1          1  \n",
       "2                    2        NaN        NaN  \n",
       "3                    1        NaN        NaN  \n",
       "4                    6        NaN        NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b41aac94",
   "metadata": {},
   "source": [
    "#### first, let me check how many unique values in each columns to see what feature engineering I can do"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e7b94edf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "email_id               100000\n",
       "email_text                  2\n",
       "email_version               2\n",
       "hour                       24\n",
       "weekday                     7\n",
       "user_country                4\n",
       "user_past_purchases        23\n",
       "email_open                  1\n",
       "link_click                  1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e2000d48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['short_email', 'long_email'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.email_text.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f188c8c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['personalized', 'generic'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.email_version.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cf50b4dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "email_id                   0\n",
       "email_text                 0\n",
       "email_version              0\n",
       "hour                       0\n",
       "weekday                    0\n",
       "user_country               0\n",
       "user_past_purchases        0\n",
       "email_open             89655\n",
       "link_click             97881\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8868c9a2",
   "metadata": {},
   "source": [
    "#### we need to find out what features contribte most to clicking the link, so I plan to use decision tree model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "149472c6",
   "metadata": {},
   "source": [
    "I first replace all the null value in email_open and linl_click as 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6338f815",
   "metadata": {},
   "outputs": [],
   "source": [
    "full_data = full_data.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "eaa27f8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "email_id               0\n",
       "email_text             0\n",
       "email_version          0\n",
       "hour                   0\n",
       "weekday                0\n",
       "user_country           0\n",
       "user_past_purchases    0\n",
       "email_open             0\n",
       "link_click             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ef4fffe9",
   "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>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "      <th>email_open</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>short_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>US</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>UK</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>11</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>US</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>short_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>6</td>\n",
       "      <td>Monday</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>long_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>US</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id   email_text email_version  hour    weekday user_country  \\\n",
       "0     85120  short_email  personalized     2     Sunday           US   \n",
       "1    966622   long_email  personalized    12     Sunday           UK   \n",
       "2    777221   long_email  personalized    11  Wednesday           US   \n",
       "3    493711  short_email       generic     6     Monday           UK   \n",
       "4    106887   long_email       generic    14     Monday           US   \n",
       "\n",
       "   user_past_purchases email_open link_click  \n",
       "0                    5          0          0  \n",
       "1                    2          1          1  \n",
       "2                    2          0          0  \n",
       "3                    1          0          0  \n",
       "4                    6          0          0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5565d585",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "le = preprocessing.LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "aca50785",
   "metadata": {},
   "outputs": [],
   "source": [
    "email_text_label = le.fit_transform(full_data['email_text'])\n",
    "email_version_label = le.fit_transform(full_data['email_version'])\n",
    "weekday_label = le.fit_transform(full_data['weekday'])\n",
    "user_country_label = le.fit_transform(full_data['user_country'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e7e42eca",
   "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>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "      <th>email_open</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id  email_text  email_version  hour  weekday  user_country  \\\n",
       "0     85120           1              1     2        3             3   \n",
       "1    966622           0              1    12        3             2   \n",
       "2    777221           0              1    11        6             3   \n",
       "3    493711           1              0     6        1             2   \n",
       "4    106887           0              0    14        1             3   \n",
       "\n",
       "   user_past_purchases  email_open  link_click  \n",
       "0                    5           0           0  \n",
       "1                    2           1           1  \n",
       "2                    2           0           0  \n",
       "3                    1           0           0  \n",
       "4                    6           0           0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "label_data = pd.DataFrame()\n",
    "label_data['email_id'] = full_data['email_id']\n",
    "label_data['email_text'] = email_text_label\n",
    "label_data['email_version'] = email_version_label\n",
    "label_data['hour'] = full_data['hour']\n",
    "label_data['weekday'] = weekday_label\n",
    "label_data['user_country'] = user_country_label\n",
    "label_data['user_past_purchases'] = full_data['user_past_purchases']\n",
    "label_data['email_open'] = full_data['email_open'].astype('int')\n",
    "label_data['link_click'] = full_data['link_click'].astype('int')\n",
    "label_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1662c35b",
   "metadata": {},
   "source": [
    "#### fit a decision tree model to see the featue importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "014bf753",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = label_data.drop(['email_id', 'link_click', 'email_open'], axis=1)\n",
    "Y = label_data['link_click'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "12b496bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import tree\n",
    "\n",
    "clf = tree.DecisionTreeClassifier()\n",
    "clf = clf.fit(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6a036210",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.1012786 , 0.01524751, 0.33280846, 0.19217639, 0.12199782,\n",
       "       0.23649123])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "96a0f728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWts2uwCOnh2n7cjuXbs3uwwAgMNmZhUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCY1rbNLoCj58uXXJJLb33rzS4DANiiTv/Qhza7BDOrAADMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrx0jb09u+e7PrAADYSoTVLaztts2uAQDgaBJWj62T2v5R2/e0Pa/tddvuaPvWthe3fVnbb0iSthe03blsn9L20mX7kW1f0vavkpy3ebcCAHD0CavH1rcl+YMxxu2TfCrJg5M8J8kvjjHumOSSJL+yjuvcI8kjxhjfd7QKBQCYgbB6bH1ojHHRsr0nybckOXmM8bpl37OT3Hsd1zl/jPHJ/R1o+5i2u9vu/sSVV264YACAzSSsHluXr9q+MsnJV3PuV/LVP5/rrDn2+QM1GmOcO8bYOcbYeZOTTjqsIgEAZiGsbq5PJ9nb9l7L+7OT7JtlvTTJXZbtM49xXQAAU/Bt8s33iCTPaHu9JB9M8qhl/28neXHbs5O8drOKAwDYTB1jbHYNHCV3vPa1x8tvcYvNLgMA2KJO/9CHjllfbfeMMXau3W8ZAAAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrbNrsAjp5r3eEOOX337s0uAwDgsJlZBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMK2OMTa7Bo6SbaduG9vP2r7ZZQBsyN5deze7BOAYaLtnjLFz7X4zqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJq0dZ2wva7jzIOY9s+7RjVRMAwFYhrAIAMC1hdY22T2j7+GV7V9vXLtvf3/Z5be/f9i1t39H2JW1vsBy/S9vXtd3T9tVtb77mutdo++y2v768f1TbD7R9XZJ7rjrvh9q+re07276m7alL279ve9NV1/qHtqcco2EBANgUwurXe32Sey3bO5PcoO01k3xPkkuSPCnJfccYd06yO8l/Xo7/fpIzxxh3SfLMJL+x6prbkjw/yQfGGE9agux/y0pIvV+S2606941J7j7GuFOSFyV5whjjqiTPS/LQ5Zz7JnnXGONfj+ytAwDMZdtmFzChPUnu0nZ7ksuTvCMrofVeSV6elWD5prZJcq0kb0ny7Um+M8n5y/6TkvzTqmv+YZIXjzH2Bdi7JblgjPEvSdL2z5LcZjn2TUn+bAm010ryoWX/M5P8ZZLfSfLoJM/aX/FtH5PkMUnS7T3MIQAAmIOwusYY44q2lyZ5VJI3J7k4yfcm+ZasBMfzxxj/fnWbtndI8p4xxj0OcNk3J/netv9jjPGlfV0d4NzfT/LUMcbL294nyZOXuj7S9rK235eVsPvQ/TUeY5yb5Nwk2XbqtgP1AQCwJVgGsH+vT3LO8vMNSR6b5KIkb01yz7bfmiRtr9f2Nknen+Smbe+x7L9m29uvut6fJHllkpe03ZbkbUnu0/YmyxKCH1917o2S/OOy/Yg1df1xVpYDvHiMceWRulkAgFkJq/v3hiQ3T/KWMcZlSb6U5A3Lx/aPTPLCthdnJbzedozx5SRnJvnNtu/KSrA9Y/UFxxhPzcqSgucmuSwrM6ZvSfKaZf8+T85KqH1DkrVrUl+e5AY5wBIAAIDjTcfwSfFWsfy+1l1jjHsd9OSsLAPYftb2o1wVwNG1d9fezS4BOAba7hljfN3vprdmdYto+8QkP5UDrFUFADgeWQawRYwxnjLGuNUY442bXQsAwLEirAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCY1rbNLoCjZ8dpO7J71+7NLgMA4LCZWQUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACm1THGZtfAUbLt1G1j+1nbN7sM2HR7d+3d7BIAOIi2e8YYO9fuN7MKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrA6kbb/dbNrAACYibC6Rtttm9j9fsNqV/izAgBOOFs+ALU9ve27V70/p+2T2z6+7XvbXtz2Rcux67d9ZtsL276z7YOW/Y9s+5K2f5XkvKvp6wltL2n7rrZPWfbtaPvWpZ+Xtf2GZf8FbXcu26e0vXRVX3/R9lVt/77tf1/2PyXJddte1Pb5y339XdunJ3lHkv+77a5VtfyfbZ96RAcTAGAymzmLeLQ9McmtxxiXtz152fdLSV47xnj0su/tbV+zHLtHkjuOMT65v4u1fUCSH0lytzHGF9reeDn0nCQ/O8Z4XdtfTfIrSX7uILXtSHKnJJcneX/b3x9jPLHt48YYO5b+Tk/y7UkeNcb46bbXT3Jx2yeMMa5I8qgkP7n+4QAA2Hq2/Mzq1bg4yfPbPizJV5Z990/yxLYXJbkgyXWS3HI5dv6BgurivkmeNcb4QpKMMT7Z9kZJTh5jvG4559lJ7r2O2v5mjPHpMcaXkrw3ya0OcN6HxxhvXfr7fJLXJnlg29smueYY45K1Ddo+pu3utruv+uJV6ygFAGBex8PM6lfytaH7OsvPH8xKcPzhrHyEfvskTfLgMcb7V1+g7d2SfP4g/TTJOMy6rrPm2OWrtq/Mgf8c1tb0x1lZ1/q+JM/aX4MxxrlJzk2SbaduO5R6AQCmczzMrF6W5GZtb9L22kkemJX7Om2M8bdJnpDk5CQ3SPLqJD/btknS9k6H0M95SR7d9npL2xuPMT6dZG/bey3nnJ1k3yzrpUnusmyfuc4+rmh7zQMdHGO8LclpSc5K8sJDqB0AYEva8jOrY4wrlrWib0vyoazMOp6U5HnLx/RNsmuM8am2v5bkd7Ky9rNZCZQPXGc/r2q7I8nutl9O8sqszHI+IskzlhD7waysJU2S307y4rZnZ+Xj+/U4d6ntHVlZX7s/L06yY4yxd53XBADYsjqGT4q3kravyEr4/puDnbvt1G1j+1nbj0FVMLe9u/y/HcDs2u4ZY+xcu/94WAZwQmh7ctsPJPnieoIqAMDxYMsvAzjS2t4hyXPX7L58jHG3zahnnzHGp5LcZjNrAAA41oTVNZZfB7Vjs+sAAMAyAAAAJiasAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWts2uwCOnh2n7cjuXbs3uwwAgMNmZhUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0OsbY7Bo4Sradum1sP2v7ZpcBwFGwd9fezS4Bjqi2e8YYO9fuN7MKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwLWEVAIBpCasAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0jruw2vZH2t5uk/q+oO3OzegbAOB4dMzDatttR7mLH0ly1MJqVxx3IR8AYEYHDV1tT2/77lXvz2n75LaPb/vethe3fdFy7Pptn9n2wrbvbPugZf8j276k7V8lOe8A/dyn7evbvmy57jP2hcK2/2/b3W3f0/a/rWrzlFU1/HbbM5L8cJLfantR2285QF8XtP2dtm9u++62d132P7ntOavOe/dy/6e3/bu2T0/yjiSntX1C20vavqvtU1Zd/sfbvr3tB9rea9UYvqHtO5bXGcv+my/3fNHS177z79/2Lcu5L2l7g/3d78H+7AAAtrqNzHI+McmtxxiXtz152fdLSV47xnj0su/tbV+zHLtHkjuOMT55Nde8a1ZmRT+c5FVJfizJnyf5pTHGJ9uelORv2t4xyUeT/GiS244xRtuTxxifavvyJK8YY/z5Qeq//hjjjLb3TvLMJN95kPO/Pcmjxhg/3fYBWZnBvdsY4wttb7zqvG1jjLu2/YEkv5Lkvkk+nuR+Y4wvtf22JC9MsjPJWUlePcb4jeXertf2lCRPSnLfMcbn2/5ikv/c9mlr73d/RbZ9TJLHJEm39yC3BAAwt418nH1xkue3fViSryz77p/kiW0vSnJBkuskueVy7PyDBNUkefsY44NjjCuzEui+Z9n/79q+I8k7k9w+K4H2M0m+lOSP2/5Yki8cYv0vTJIxxuuT3PBA4W+VD48x3rps3zfJs8YYX1iusfq+/mL5uSfJ6cv2NZP8UdtLkrwkX12mcGGSR7V9cpI7jDE+m+Tuy/E3LeP4iCS3Wu/9jjHOHWPsHGPsvMZ1rVYAALa29aSZr6w57zrLzx9M8gdJ7pJkz7IWtUkePMbYsbxuOcb4u+X8z6+jr7H2fdtbJzknyfePMe6Y5K+TXGeM8ZWszMS+NCuznK9ax/Wvtq8c+F6Tr62/+2m/z+XLzyvz1Znrn09yWZLvysqM6rWS/x2U753kH5M8t+3Dl2ufv2oMbzfG+A9H4H4BALac9YTVy5LcrO1N2l47yQOXdqeNMf42yROSnJzkBkleneRn2zZJ2t7pEOu5a9tbL2tVH5LkjUlumJWg+Om2pyZ5wHLtGyS50RjjlUl+LsmO5RqfTbJ9HX09ZLnO9yT59Bjj00kuTXLnZf+dk9z6AG3PS/Lottdbzr3xAc7b50ZJ/mmMcVWSs5OctLS7VZKPjzH+KMmfLH2/Nck9237rcs712t7mau4XAOC4ddA1q2OMK9r+apK3JflQkvdlJWw9r+2NsjITuGtZL/prSX4nycVLYL00K+F2vd6S5ClJ7pDk9UleNsa4qu07k7wnyQeTvGk5d3uSv2x7naWGn1/2vygrH7k/PsmZY4z/dYC+9rZ9c1bC8KOXfS9N8vDl4/cLk3zgAGPyqrY7kuxu++Ukr0zyX6/mvp6e5KVtfzzJ3+ars7T3SfJ/tb0iyeeSPHyM8S9tH5nkhcv/HCQra1g/e4D7BQA4bnWMA32afWy1vU+Sc8YYhxJuD7evC5a+dh/tvjbTtlO3je1nrWeSGYCtZu+uvZtdAhxRbfeMMb7u99X7Bg4AANM62r+g/+u0vUOS567ZffkY425Z+Q0CR7KvP0hyzzW7f3eMcZ8j2Q8AAEfHMQ+rY4xLcoy+HDTG+Jlj0Q8AAEeHZQAAAExLWAUAYFrCKgAA0xJWAQCYlrAKAMC0hFUAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtIRVAACmJawCADAtYRUAgGkJqwAATEtYBQBgWsIqAADTElYBAJjWts0ugKNnx2k7snvX7s0uAwDgsJlZBQBgWsIqAADTElYBAJiWsAoAwLSEVQAApiWsAgAwrY4xNrsGjpK2n03y/s2uYws7Jcm/bnYRW5Sx2xjjtzHGb2OM38YYv8N3qzHGTdfu9HtWj2/vH2Ps3Owitqq2u43f4TF2G2P8Nsb4bYzx2xjjd+RZBgAAwLSEVQAApiWsHt/O3ewCtjjjd/iM3cYYv40xfhtj/DbG+B1hvmAFAMC0zKwCADAtYXULavtv276/7T+0feJ+jrft7y3HL2575/W2PRFscPwubXtJ24va7j62lc9hHeN327ZvaXt523MOpe2JYIPjd0I/f+sYu4cu/81e3PbNbb9rvW1PBBscvxP62UvWNX4PWsbuora7237PettyEGMMry30SnJSkv+V5JuTXCvJu5Lcbs05P5DkfyZpkrsnedt62x7vr42M33Ls0iSnbPZ9TD5+N0vy3Ul+I8k5h9L2eH9tZPyWYyfs87fOsTsjyTcs2w/wd9+RGb/l/Qn77B3C+N0gX11eecck71tvW6+rf5lZ3XrumuQfxhgfHGN8OcmLkjxozTkPSvKcseKtSU5ue/N1tj3ebWT8WMf4jTE+Psa4MMkVh9r2BLCR8TvRrWfs3jzG2Lu8fWuSb1pv2xPARsaP9Y3f58aSTpNcP8lYb1uunrC69fybJB9Z9f6jy771nLOetse7jYxfsvKXz3lt97R9zFGrcl4beYY8fxsfgxP5+TvUsfsPWfmE5HDaHo82Mn7Jif3sJescv7Y/2vZ9Sf46yaMPpS0H5l+w2nq6n31rf6XDgc5ZT9vj3UbGL0nuOcb4WNubJTm/7fvGGK8/ohXObSPPkOdv42NwIj9/6x67tt+blbC1b82gZ29j45ec2M9ess7xG2O8LMnL2t47ya8lue9623JgZla3no8mOW3V+29K8rF1nrOetse7jYxfxhj7fn48ycuy8vHOiWQjz5Dnb4NjcII/f+sau7Z3TPLHSR40xvjEobQ9zm1k/E70Zy85xGdoCfLf0vaUQ23L1xNWt54Lk3xb21u3vVaSn0jy8jXnvDzJw5dvtd89yafHGP+0zrbHu8Mev7bXb7s9SdpeP8n9k7z7WBY/gY08Q56/DYyB5+/gY9f2lkn+IsnZY4wPHErbE8Bhj59nL8n6xu9b23bZvnNWvkz1ifW05epZBrDFjDG+0vZxSV6dlW8YPnOM8Z62j12OPyPJK7PyjfZ/SPKFJI+6urabcBubZiPjl+TUrHy8k6z8t/OCMcarjvEtbKr1jF/bb0yyO8kNk1zV9uey8s3Xz3j+Dn/8kpySE/j5W+d/u7+c5CZJnr6M01fGGDv93bex8Yu/+9Y7fg/OykTHFUm+mOQhyxeuTvjnb6P8C1YAAEzLMgAAAKYlrAIAMC1hFQCAaQmrAABMS1gFAGBawioAANMSVgEAmJawCgDAtP5/htHMOfkfQT4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "values = clf.feature_importances_  \n",
    "idx = clf.feature_names_in_\n",
    "plt.figure(figsize=(10,8))\n",
    "clrs = ['green' if (x < max(values)) else 'red' for x in values ]\n",
    "sns.barplot(y=idx,x=values,palette=clrs).set(title='Important features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7cc9a840",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_predict = clf.predict(X)\n",
    "y_predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b1019221",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The precision for Tree is  0.9700374531835206\n",
      "The recall for Tree is  0.12222746578574799 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report, precision_score,recall_score\n",
    "\n",
    "print(\"The precision for Tree is \",precision_score(Y, y_predict)) \n",
    "print(\"The recall for Tree is \",recall_score(Y, y_predict),\"\\n\") "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36ad7c04",
   "metadata": {},
   "source": [
    "#### Apparently, hour, and user past purchases are the most important three factors that contributed to link clicking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29137555",
   "metadata": {},
   "source": [
    "## Part 4: factors relating to the click improve"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11aa3431",
   "metadata": {},
   "source": [
    "#### Next, I will also visualize the click vs email text and email version to see if there is any connections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5c63cb7b",
   "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>email_id</th>\n",
       "      <th>email_text</th>\n",
       "      <th>email_version</th>\n",
       "      <th>hour</th>\n",
       "      <th>weekday</th>\n",
       "      <th>user_country</th>\n",
       "      <th>user_past_purchases</th>\n",
       "      <th>email_open</th>\n",
       "      <th>link_click</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85120</td>\n",
       "      <td>short_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>US</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>966622</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>UK</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>777221</td>\n",
       "      <td>long_email</td>\n",
       "      <td>personalized</td>\n",
       "      <td>11</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>US</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>493711</td>\n",
       "      <td>short_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>6</td>\n",
       "      <td>Monday</td>\n",
       "      <td>UK</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>106887</td>\n",
       "      <td>long_email</td>\n",
       "      <td>generic</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>US</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   email_id   email_text email_version  hour    weekday user_country  \\\n",
       "0     85120  short_email  personalized     2     Sunday           US   \n",
       "1    966622   long_email  personalized    12     Sunday           UK   \n",
       "2    777221   long_email  personalized    11  Wednesday           US   \n",
       "3    493711  short_email       generic     6     Monday           UK   \n",
       "4    106887   long_email       generic    14     Monday           US   \n",
       "\n",
       "   user_past_purchases email_open link_click  \n",
       "0                    5          0          0  \n",
       "1                    2          1          1  \n",
       "2                    2          0          0  \n",
       "3                    1          0          0  \n",
       "4                    6          0          0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c32606ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='email_text', data=full_data, ax=ax[0])\n",
    "ax[0].set_xlabel('Email Text', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of Email Text', fontsize=16)\n",
    "\n",
    "sns.barplot(x='email_text', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('Email Text', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. Email Text', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7ae21332",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TdLJ6Lnac5i55I6OtvgPsluRRHfsfRTPy6zsdza4FnpxkvY56L6RZvHd1jHSm11/N9uNxJc1aOHt1FrY3zXg8D72++8YTS1X9BvghsGfnItFJHk/zjfN3Rmu7BngEK0/J2YfmG9SpdAJNEvCtNItvf35kFGD7/n2XZjHmi3t9Iz2RE1XVXVV1Gk2HbC6jf/P+HWDzJM/vKt+bZmTCFRM5ryRp6E2krzUe3wBeka67/fbSLpexS7udNMoNIwZhIv2ua2mm8Hbarev10nbbs6t8D/ozwGUhzXrO/9gxXXS8fanR+rln0MyAuGuUUXmjjYwEmrtj00x53afdfgN8aZS6K6rqAppZG+sATx3r2AP0CJqRep3eMA3nWdie6wPAM3joF9VX0iRnnzbKz2XUO5L3UlW3V9UXaW4s0/173uk7wA6dowzb/1+8BvhRtXdXlvptTfmjImkKVNW5Sd4GfCzJU2kWtb6OZpj6TjR3Ttub5o5i/0wzdP7sJB+m+bbqnTR/QD/YcdiTaO6Ie2yS42im+L4N6FwLbyJ+TtPB+qskt9F0pK6cyj+EVXV/kvfRfJP3OZppGfOAw2jWaPnvjuo/pUmUnkEzSvCGMdYB+ieaNUBOS/JJmnVnPkDzXnx0EiFvmqTX2jM3VtU1kzjuiDOAPZIcQTPy4Dk0Nzj51RQc+/eqammSb9FMGQ4PTi8e8TbgXODMJJ+lGSGwKc3ajrOq6pCxjp/kgzTrIH2bZgrN5jTXcUlVLR+l2XHAW2imCr2H5j8crwNeCvxt9zRmSZLGMsG+1ni8n3bqcJJ/pVmnbR6wc1W9vsf5v5tkZ5ppsV9MsldVdSdZ+mqC/a6TgPe2f5MvoLnj7Wu7jvdAkg8An07yGZq1CJ9Ac2fkO2i+jJzO66n2ek6jmTr6UcbflxoZmfb2JF8H7m+/BP08TfLr7CQfBX5MM5LyicCfA3v0WFqm2/E0MzH+CPhyVd01siPJK2j661+hGan4yDa+O2kSiyNfav8f8MGq+iCrNm+U/um1VdVreuxEnQG8M8m7aaZavxh49RQc9yGq6vtJrgL+gSYheWLHvkpyIHBqOxjiZJpRvY+lGQBwXVV9bKzjJzmGB9/nm2nudLwPD86i6eUImhvsnJXk/cCvae4C/WRWTphLfeMIQmmGqar/oLlr3K9o7pD1LZrO61OBvwW+2ta7lGaK5q9pEjkn0NxF70VV9eOO430beCPNEPmv0nRuXs9qJpeq6laaBNIzab49u4imkzWlquoYmj/Of0Sz/shHgLNoru+ujqoH0XwL+9U2lgVjHPMMmj/aG9F0II6mGYH2gnEsLj6Wl9N0Krq3d0zimJ0+TdNJfw3Nde5GM1J0dZO8Y1lIkxy8pKou69xRVRfTTIm5leYGM98A/pPmZ3TuOI59Ic2dDo+g+Vl+mHYk7GgN2pGLL2rPdTjN78IzgX3a3xFJkiZkvH2tcR7rGpo+1gXAh2iSJh+kWdtutDbn0fQdXgL8T+csj0GZQL/rQzR3fT2IJpn1VB56842R432GJqHz0vZ4B9B8wVdMT/+l+/xfo1nv8R3tjdbG25c6jWZdvTfT9OUuao/3O5qf2adp+pqn0yQN92vP0z2VtZcv0nzJ/gc0/fZOV9Gsj/lPNMnj/27rvrSqRta4DM2Ix/HmAPand//0deNsvyofpJkJ8g80a0s/g+Y9mg7H01z/19r/i/xeVZ1Oc9OQRwKfoVlH8CM07/P54zj2eTT/l/kkze/8e2iS5PuN1qD9f8MLaG6KcxRwCs109d3a/29IA5FmyrwkSZIkSWumJH9MM9Js36rqTpBJkibJBKEkSZIkaY3R3qziQJr1i39NM9Lw3TQj7Z4+jum4kqQJcg1CSZIkSdKa5Lc0N3nYl2Z9x9tp7jJ7iMlBSZoejiCUJElSX7Q3V/hPmnWwPlNVh3ftT7t/V+BuYP+qujjJw2nWKn0YzRfcp1TV+9s2m9CszbUVzd0o/7Kqbu/LBUmSJM0Q3qREkiRJ0y7JLJo7cO4CbAO8Nsk2XdV2Aea32wKaxduhueP9i6vqmcC2wM4dd9c8BDi7quYDZ7evJUmSNAFDPcV40003ra222mrQYUiSJPXdD3/4w1uqak4fT7k9sKSqrgZIchKwO/DTjjq7A8dXM8XlgiQbJZlbVcuAkTuhrttu1dFmx/b5QuAc4J1jBWIfUJIkDavR+oBDnSDcaqutWLx48aDDkCRJ6rsk1/b5lPOA6zteLwWeO44684Bl7QjEHwJPAj5RVRe2dR7bJhCpqmVJNut18iQLaEYlsuWWW9oHlCRJQ2m0PqBTjCVJktQP6VHWvRj2qHWq6v6q2hbYHNg+ydMncvKqOqaqtquq7ebM6efASUmSpDWfCUJJkiT1w1Jgi47XmwM3TLROVf2KZhrxzm3RTUnmArSPN09ZxJIkSUPCBKEkSZL64SJgfpKtk6wH7AUs6qqzCNg3jR2AO9ppw3OSbASQZH3gJcDPOtrs1z7fDzh1mq9DkiRpxhnqNQglSZLUH1W1IslBwJnALODYqro8yRvb/UcDpwO7AkuAu4E3tM3nAgvbdQjXAU6uqtPafYcDJyc5ALgO2LNf1yRJkjRTmCCUJElSX1TV6TRJwM6yozueF3Bgj3aXAs8a5Zi3AjtNbaSSJEnDxSnGkiRJkiRJ0hAzQShJkiRJkiQNMROEkiRJkiRJ0hAzQShJkiRJkiQNMROEkiRJkiRJ0hAzQShJkiRJkiQNMROEkiRJkiRJ0hAzQShJkiRJkiQNMROEkiRJkiRJ0hDrW4IwyTVJLktySZLFbdkmSc5KclX7uHFH/XclWZLkyiQv7yh/TnucJUmOTJK2/GFJvtiWX5hkq35dmyRJkqSZ7+CDD2bffffl4IMPHnQokiRNqdl9Pt+fVdUtHa8PAc6uqsOTHNK+fmeSbYC9gKcBjwO+meTJVXU/cBSwALgAOB3YGfg6cABwe1U9KclewIeB1/TrwiRpbXDdB/9o0CFI6mHL91026BAkjcONN97IL3/5y0GHIUnSlBv0FOPdgYXt84XAHh3lJ1XVvVX1C2AJsH2SucCGVXV+VRVwfFebkWOdAuw0MrpQkiRJkiRJUm/9TBAW8I0kP0yyoC17bFUtA2gfN2vL5wHXd7Rd2pbNa593lz+kTVWtAO4AHtMdRJIFSRYnWbx8+fIpuTBJkiRJkiRpbdXPKcbPr6obkmwGnJXkZ2PU7TXyr8YoH6vNQwuqjgGOAdhuu+1W2j/dnvOPx/f7lJLG4Yf/tu+gQ5AkSZIkaSD6NoKwqm5oH28GvgxsD9zUThumfby5rb4U2KKj+ebADW355j3KH9ImyWzg0cBt03EtkiRJkiRJ0kzRlwRhkkcmedTIc+BlwE+ARcB+bbX9gFPb54uAvdo7E28NzAd+0E5DvjPJDu36gvt2tRk51quBb7XrFEqSJEmSJEkaRb+mGD8W+HJ7z5DZwBeq6owkFwEnJzkAuA7YE6CqLk9yMvBTYAVwYHsHY4A3AccB69PcvfjrbflngROSLKEZObhXPy5MkiRJkiRJWpv1JUFYVVcDz+xRfiuw0yhtDgMO61G+GHh6j/J7aBOMkiRJkiRJksann3cxliRJkiRJkrSGMUEoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDbHZgw5AkiRJmume84/HDzoETYFH3XIns4DrbrnTn+kM8cN/23fQIUjSGsERhJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQmz3oACRJkiRpbfDAeo98yKMkSTOFCUJJkiRJGoffzH/ZoEOQJGlaOMVYkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJfZFk5yRXJlmS5JAe+5PkyHb/pUme3ZZvkeTbSa5IcnmSt3S0OTTJL5Nc0m679vOaJEmSZgLvYixJkqRpl2QW8AngpcBS4KIki6rqpx3VdgHmt9tzgaPaxxXA26vq4iSPAn6Y5KyOtkdU1b/361okSZJmGkcQSpIkqR+2B5ZU1dVVdR9wErB7V53dgeOrcQGwUZK5VbWsqi4GqKo7gSuAef0MXpIkaSYzQShJkqR+mAdc3/F6KSsn+VZZJ8lWwLOACzuKD2qnJB+bZOMpi1iSJGlImCCUJElSP6RHWU2kTpINgP8F3lpVv26LjwKeCGwLLAM+2vPkyYIki5MsXr58+QRDlyRJmtlMEEqSJKkflgJbdLzeHLhhvHWSrEuTHPx8VX1ppEJV3VRV91fVA8CnaaYyr6Sqjqmq7apquzlz5kz6YiRJkmYSE4SSJEnqh4uA+Um2TrIesBewqKvOImDf9m7GOwB3VNWyJAE+C1xRVR/rbJBkbsfLVwE/mb5LkCRJmpm8i7EkSZKmXVWtSHIQcCYwCzi2qi5P8sZ2/9HA6cCuwBLgbuANbfPnA/sAlyW5pC17d1WdDnwkybY0U5GvAf62LxckSZI0g5gglCRJUl+0Cb3Tu8qO7nhewIE92n2P3usTUlX7THGYkiRJQ8cpxpIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDbG+JgiTzEryoySnta83SXJWkqvax4076r4ryZIkVyZ5eUf5c5Jc1u47Mkna8ocl+WJbfmGSrfp5bZIkSZIkSdLaqN8jCN8CXNHx+hDg7KqaD5zdvibJNsBewNOAnYFPJpnVtjkKWADMb7ed2/IDgNur6knAEcCHp/dSJEmSJEmSpLVf3xKESTYHdgM+01G8O7Cwfb4Q2KOj/KSqureqfgEsAbZPMhfYsKrOr6oCju9qM3KsU4CdRkYXSpIkSZIkSeqtnyMI/wM4GHigo+yxVbUMoH3crC2fB1zfUW9pWzavfd5d/pA2VbUCuAN4THcQSRYkWZxk8fLlyyd5SZIkSZIkSdLarS8JwiSvAG6uqh+Ot0mPshqjfKw2Dy2oOqaqtquq7ebMmTPOcCRJkiRJkqSZaXafzvN84M+T7Ao8HNgwyeeAm5LMrapl7fThm9v6S4EtOtpvDtzQlm/eo7yzzdIks4FHA7dN1wVJkiRJkiRJM0FfRhBW1buqavOq2orm5iPfqqrXA4uA/dpq+wGnts8XAXu1dybemuZmJD9opyHfmWSHdn3BfbvajBzr1e05VhpBKEmSJEmSJOlB/RpBOJrDgZOTHABcB+wJUFWXJzkZ+CmwAjiwqu5v27wJOA5YH/h6uwF8FjghyRKakYN79esiJEmSJEmSpLVV3xOEVXUOcE77/FZgp1HqHQYc1qN8MfD0HuX30CYYJUmSJEmSJI1PP+9iLEmSJEmSJGkNY4JQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJkiRJkqQhZoJQkiRJkiRJGmImCCVJktQXSXZOcmWSJUkO6bE/SY5s91+a5Nlt+RZJvp3kiiSXJ3lLR5tNkpyV5Kr2ceN+XpMkSdJMYIJQkiRJ0y7JLOATwC7ANsBrk2zTVW0XYH67LQCOastXAG+vqqcCOwAHdrQ9BDi7quYDZ7evJUmSNAEmCCVJktQP2wNLqurqqroPOAnYvavO7sDx1bgA2CjJ3KpaVlUXA1TVncAVwLyONgvb5wuBPab5OiRJkmYcE4SSJEnqh3nA9R2vl/Jgkm/cdZJsBTwLuLAtemxVLQNoHzfrdfIkC5IsTrJ4+fLlq3sNkiRJM5IJQkmSJPVDepTVROok2QD4X+CtVfXriZy8qo6pqu2qars5c+ZMpKkkSdKMZ4JQkiRJ/bAU2KLj9ebADeOtk2RdmuTg56vqSx11bkoyt60zF7h5iuOWJEma8UwQSpIkqR8uAuYn2TrJesBewKKuOouAfdu7Ge8A3FFVy5IE+CxwRVV9rEeb/drn+wGnTt8lSJIkzUyzBx2AJEmS1h5JtgDmtTcRGbeqWpHkIOBMYBZwbFVdnuSN7f6jgdOBXYElwN3AG9rmzwf2AS5Lcklb9u6qOh04HDg5yQHAdcCek7k+SZKkYWSCUJIkSauUZEvgRGBbmnUBN0jyamDnqvrr8RyjTeid3lV2dMfzAg7s0e579F6fkKq6FdhpfFchSZKkXpxiLEmSpPH4FPA14FHA79qys4CXDiwiSZIkTQlHEEqSJGk8tgd2q6oHkhRAVd2R5NEDjkuSJEmT5AhCSZIkjcdNwJM6C5JsQ7PunyRJktZiJgglSZI0Hv8OnJbkDcDsJK8Fvgh8eLBhSZIkabKcYixJkqRVqqpjk9wGLACuB/YF/qmqvjLQwCRJkjRpJgglSZK0Skme2yYDv9JVvn1V/WAgQUmSJGlKOMVYkiRJ43HWKOVn9DUKSZIkTTlHEEqSJGlUSdYB0jxN2ucjngisGEhgkiRJmjImCCVJkjSWFUB1PO/0AHBYf8ORJEnSVDNBKEmSpLFsTTNq8DvACzvKC1heVb8dSFSSJEmaMiYIJUmSNKqqurZ9+viBBiJJkqRpY4JQkiRJ45Lkz4EXAZvSsRZhVe07sKAkSZI0ad7FWJIkSauU5P3Ap2j6j3sCtwIvB341wLAkSZI0BUwQSpIkaTz+CnhpVf0DcF/7+Epgq4FGJUmSpEkzQShJkqTx2KiqftI+vy/JulX1A5opx5IkSVqLuQahJEmSxuP/kjytqi4HfgK8KcntwO0DjkuSJEmTZIJQkiRJ4/Fe4DHt80OALwAbAAcOLCJJkiRNCROEkiRJWqWqOr3j+Q+AJwEkWXdgQUmSJGlKuAahJEmSJizJw5L8HXD1oGORJEnS5JgglCRJ0qiSPCXJd5PcmeTiJE9P8hc0icF9gLcPOERJkiRNklOMJUmSNJYjgSXAvwJ7A6cCvwX2q6pvDjIwSZIkTQ0ThJIkSRrLc4A/r6p7k5wL/Bp4fFUtHXBckiRJmiJOMZYkSdJY1quqewGq6jfAHSYHJUmSZhZHEEqSJGksD0vywY7X63e9pqre1+eYJEmSNIVMEEqSJGksXwC26Hh9Utfr6m84kiRJmmomCCVJkjSqqnrDoGOQJEnS9OrLGoRJHp7kB0l+nOTyJB9oyzdJclaSq9rHjTvavCvJkiRXJnl5R/lzklzW7jsySdryhyX5Ylt+YZKt+nFtkiRJkiRJ0tqsXzcpuRd4cVU9E9gW2DnJDsAhwNlVNR84u31Nkm2AvYCnATsDn0wyqz3WUcACYH677dyWHwDcXlVPAo4APtyH65IkSZIkSZLWan1JEFbjrvbluu1WwO7AwrZ8IbBH+3x34KSqureqfgEsAbZPMhfYsKrOr6oCju9qM3KsU4CdRkYXSpIkSZIkSeqtXyMISTIrySXAzcBZVXUh8NiqWgbQPm7WVp8HXN/RfGlbNq993l3+kDZVtQK4A3hMjzgWJFmcZPHy5cun6OokSZIkSZKktVPfblJSVfcD2ybZCPhykqePUb3XyL8ao3ysNt1xHAMcA7Dddtt51z1JkqRxSvIU4JnABp3lVXXsYCKSJEnSVOj7XYyr6ldJzqFZO/CmJHOralk7ffjmttpSYIuOZpsDN7Tlm/co72yzNMls4NHAbdN2IZIkSUMkybuB9wE/Bu7u2FWACUJJkqS1WL/uYjynHTlIkvWBlwA/AxYB+7XV9gNObZ8vAvZq70y8Nc3NSH7QTkO+M8kO7fqC+3a1GTnWq4FvtesUSpIkafLeCmxfVc+tqj/r2F486MAkSZI0Of0aQTgXWNjeiXgd4OSqOi3J+cDJSQ4ArgP2BKiqy5OcDPwUWAEc2E5RBngTcBywPvD1dgP4LHBCkiU0Iwf36suVSZIkDYff0nzBK0mSpBmmLwnCqroUeFaP8luBnUZpcxhwWI/yxcBK6xdW1T20CUZJkiRNXpLO2Sb/BPxXkkOBmzrrVdUD/YxLkiRJU6vvaxBKkiRprbGClW8I99cd+9Pun9XPoCRJkjS1TBBKkiRpNFsPOgBJkiRNPxOEkiRJ6qmqrh10DJIkSZp+404QJtmzqv6nR/mrq+qUqQ1LkiRJa5IkJ/DgdONO9wJLga9U1Y/7G5UkScPj4IMP5sYbb+QP/uAP+MhHPjLocDTDrLPqKr/32VHKj5mKQCRJkrRGuwPYnWbdwaXt458D9wNPBc5Psu/gwpMkaWa78cYb+eUvf8mNN9446FA0A61yBGGSJ7RP10myNQ8uUA3wBOCe6QhMkiRJa5QnA7tW1XkjBUn+BPhgVb00yc7AfwDHDyg+SZIkrabxTDFeQjOdJMD/de27ETh0imOSJEnSmue5wIVdZYuB7dvnZwKb9zUiSZIkTYlVTjGuqnWqahbw3fZ55/a4qnKKsSRJ0sx3CXBYkocDtI//DIysO7g1cNtgQpMkSdJkjHsNwqp60XQGIkmSpDXafsCfAr9OciPwa+CFbTnAJsCbBxSbJEmSJmEidzHeGjgM2BbYoHNfVW05tWFJkiRpTVJV1wDPS7IlMBdYVlXXdexfPKjYJEmSNDnjThACX6BZg/DtwN3TE44kSZLWRElGZp4sbbffl1XVA4OKS5IkSZM3kQTh04Dn2wGUJEkaSitoblzXy6x+BiJJkqSpNZEE4bnAs4AfTlMskiRJWnNt3fV6LnAI8NUBxCJJkqQpNJEE4TXAmUm+BNzYuaOq3jeVQUmSJGnNUlXXdhVdm2Q/4CLgswMISZIkSVNkIgnCR9J8Q7wusMX0hCNJkqS1yIbAnEEHIUmSpMkZd4Kwqt4wnYFIkiRpzZXkBB66BuEjgBcCnxtMRJIkSZoq66y6SiPJE0bbpjNASZIkrRGWAP/XsV0A7F1VfzfeAyTZOcmVSZYkOaTH/iQ5st1/aZJnd+w7NsnNSX7S1ebQJL9Mckm77braVyhJkjSkJjLFeAnNt8bpKBv5Ftk710mSJM1gVfWBybRPMgv4BPBSYClwUZJFVfXTjmq7APPb7bnAUe0jwHHAx4Hjexz+iKr698nEJ0kz2XUf/KNBh6ApsOK2TYDZrLjtWn+mM8SW77ts0CH83rhHEFbVOlU1q31cB3gccAywz7RFJ0mSpDVGkjck+VY7CvBbSSayBM32wJKqurqq7gNOAnbvqrM7cHw1LgA2SjIXoKrOBW6biuuQJEnSQ407Qditqm4E3gp8aMqikSRJ0hopyXuAQ2gSe3/fPh7clo/HPOD6jtdL27KJ1unloHZK8rFJNh4l/gVJFidZvHz58nGGLEmSNBxWO0HYegrNAtWSJEma2f4aeFlVHVNVZ1bVMcDOwIJxtk+PslqNOt2OAp4IbAssAz7aq1Ib93ZVtd2cOd54WZIkqdO41yBM8l1WvnPd04APTnVQkiRJWuM8EugeencrsP442y8Ftuh4vTlww2rUeYiqumnkeZJPA6eNMx5JkiS1JnKTks90vf4N8OOqumoK45EkSdKa6Qzg8+3dh68DHg8cBpw5zvYXAfOTbA38EtgL2LurziKa6cIn0dyc5I6qWjbWQZPM7ajzKuAnY9WXJEnSysadIKyqhdMZiCRJktZoB9HcRfjHwLrA74CTadYjXKWqWpHkIJqE4izg2Kq6PMkb2/1HA6cDuwJLgLuB398EJcmJwI7ApkmWAu+vqs8CH0myLc1Ml2uAv53shUqSJA2biUwxXhd4L81dix9HM93jBOCw9k50kiRJmoGSzALeQbPe4P7ApsAtVfXARI5TVafTJAE7y47ueF7AgaO0fe0o5ftMJAZJkiStbCI3KfkI8BLgjcAz28cXAx+ehrgkSZK0hqiq+2kSd/dV1QNVdfNEk4OSJElac01kDcI9gWdW1a3t6yuTXEwzzeQfpjwySZIkrUkW0nxB/MlBByJJkqSpNZEEYSZYLkmSpJlje+DvkhwMXE+z5h8AVfXCgUUlSZKkSZtIgvB/gK8m+QAP3rnuvW25JEmSZrZPt5skSZJmmIkkCA+mSQh+guYmJb8ETgT+ZRrikiRJ0hqkqhYOOgZJkiRNj1UmCJM8H/jzqnon8L52G9n3YeDZwAXTFqEkSZLWCEleBmwLbNBZXlXv69lAkiRJa4Xx3MX43cC5o+z7NvCeqQtHkiRJa6IkHwc+BzwH2KJrkyRJ0lpsPFOMtwXOGGXfN4FjpywaSZIkraleC2xbVdcPOhBJkobRpg9/AFjRPkpTazwJwg2B9YDf9ti3LvCoKY1IkiRJa6JbgV8NOghJkobVO57xq0GHoBlsPAnCnwEvA07tse9l7X5JkiTNMEme0PHyo8Dnk3wIuKmzXlVd3dfAJEmSNKXGkyA8AvhUklnAV6rqgSTrAHvQ3NH4bdMYnyRJkgZnSY+yV3S9LmBWH2KRJEnSNFllgrCqvpDkD4CFwMOS3AJsCtwDvL+qTpzmGCVJkjQAVTWeG9pJkiRpLTeeEYRU1ceSfAb4E+AxNGvQnF9Vv57O4CRJkjRYSS6rqj8adBySJEmaPuNKEAK0ycAzpzEWSZIkrXm2GnQAkiRJml5OG5EkSdJYatABSJIkaXqNewShJEmShtIjkpw7VoWqemG/gpEkSdLUM0EoSZKksfwO+Oygg5AkSdL0MUEoSZKksfyuqhYOOghJkiRNH9cglCRJ0lgy6AAkSZI0vUwQSpIkaSz/OugAJEmSNL1MEEqSJGlUVfWhQccgSZKk6WWCUJIkSZIkSRpiJgglSZIkSZKkIWaCUJIkSauU5HGjlD+r37FIkiRpapkglCRJ0nh8I8kmnQVJtgdOH1A8kiRJmiImCCVJkjQex9AkCTcASPI8YBFwwECjkiRJ0qTNHnQAkiRJWvNV1ZFJHg2cnuRDwHHA66rqm4ONTJIkSZNlglCSJEnjUlX/nGQj4IvAK6rq3AGHJEmSpClgglCSJEk9JbkeqK7iddrtc0kAqKot+xyaJEmSppAJQkmSJI3m9YMOQJIkSdPPBKEkSZJ6qqrvDDoGSZIkTT/vYixJkqRVSvKlJH/aVfanSU4ZVEySJEmaGiYIJUmSNB4vAr7fVXY+8GcDiEWSJElTyAShJEmSxuMe4JFdZRsAvxtALJIkSZpCfUkQJtkiybeTXJHk8iRvacs3SXJWkqvax4072rwryZIkVyZ5eUf5c5Jc1u47Mu3t85I8LMkX2/ILk2zVj2uTJEkaEmcCn0qyIUD7+HHgjIFGJUmSpEnr1wjCFcDbq+qpwA7AgUm2AQ4Bzq6q+cDZ7WvafXsBTwN2Bj6ZZFZ7rKOABcD8dtu5LT8AuL2qngQcAXy4HxcmSZI0JN4ObAjcluRm4Dbg0cBbBxmUJEmSJq8vCcKqWlZVF7fP7wSuAOYBuwML22oLgT3a57sDJ1XVvVX1C2AJsH2SucCGVXV+VRVwfFebkWOdAuw0MrpQkiRJk1NVt1fVbsAWwG7A5lX1yqr61WAjkyRJ0mTN7vcJ26m/zwIuBB5bVcugSSIm2aytNg+4oKPZ0rbsd+3z7vKRNte3x1qR5A7gMcAtXedfQDMCkS233HLKrkuSJGmmSZL2S1mSjHyxfFO7/b6sqh4YTISSJEmaCn29SUmSDYD/Bd5aVb8eq2qPshqjfKw2Dy2oOqaqtquq7ebMmbOqkCVJkobZHR3PV9B8Wdu5jZRJkiRpLda3EYRJ1qVJDn6+qr7UFt+UZG47enAucHNbvpRm+sqIzYEb2vLNe5R3tlmaZDbNmji3TcvFSJIkDYendTzfemBRSJIkaVr16y7GAT4LXFFVH+vYtQjYr32+H3BqR/le7Z2Jt6a5GckP2unIdybZoT3mvl1tRo71auBbI1NiJEmSNHFVdX3H82tH2wYZoyRJkiavXyMInw/sA1yW5JK27N3A4cDJSQ4ArgP2BKiqy5OcDPyUZurKgVV1f9vuTcBxwPrA19sNmgTkCUmW0Iwc3Guar0mSJGlGS3ICPZZs6VZV+/YhHEmSJE2TviQIq+p79F4jEGCnUdocBhzWo3wx8PQe5ffQJhglSZI0JZYMOgBJkiRNv77fxViSJElrh6r6wKBjkCRJ0vTr612MJUmStHZJ8rwkHx5l3+FJduh3TJIkSZpaJgglSZI0lvcA546y7zvtfkmSJK3FTBBKkiRpLNsCZ4yy7yzgOf0LRZIkSdPBBKEkSZLGsiGw3ij71gUe1cdYJEmSNA1MEEqSJGksPwNeNsq+l7X7JUmStBbzLsaSJEkayxHAp5LMAr5SVQ8kWQfYA/gE8LZBBidJkqTJcwShJEmSRlVVXwA+AiwE7klyA3APcBzwkao6cbzHSrJzkiuTLElySI/9SXJku//SJM/u2HdskpuT/KSrzSZJzkpyVfu48WpeqiRJ0tAyQShJkqQxVdXHgHnAK4F3tI+bV9UR4z1GOwLxE8AuwDbAa5Ns01VtF2B+uy0AjurYdxywc49DHwKcXVXzgbPb15IkSZoApxhLkiRplarq18CZkzjE9sCSqroaIMlJwO7ATzvq7A4cX1UFXJBkoyRzq2pZVZ2bZKsex90d2LF9vhA4B3jnJOKUJEkaOo4glCRJUj/MA67veL20LZtonW6PraplAO3jZpOMU5IkaeiYIJQkSVI/pEdZrUad1Tt5siDJ4iSLly9fPhWHlCRJmjFMEEqSJKkflgJbdLzeHLhhNep0uynJXID28eZelarqmKrarqq2mzNnzoQClyRJmulMEEqSJKkfLgLmJ9k6yXrAXsCirjqLgH3buxnvANwxMn14DIuA/drn+wGnTmXQkiRJw8AEoSRJkqZdVa0ADqK50ckVwMlVdXmSNyZ5Y1vtdOBqYAnwaeDNI+2TnAicDzwlydIkB7S7DgdemuQq4KXta0mSJE2AdzGWJElSX1TV6TRJwM6yozueF3DgKG1fO0r5rcBOUximJEnS0HEEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJkiRJQ8wEoSRJkiRJkjTE+pIgTHJskpuT/KSjbJMkZyW5qn3cuGPfu5IsSXJlkpd3lD8nyWXtviOTpC1/WJIvtuUXJtmqH9clSZIkSZIkre36NYLwOGDnrrJDgLOraj5wdvuaJNsAewFPa9t8Msmsts1RwAJgfruNHPMA4PaqehJwBPDhabsSSZIkSZIkaQbpS4Kwqs4Fbusq3h1Y2D5fCOzRUX5SVd1bVb8AlgDbJ5kLbFhV51dVAcd3tRk51inATiOjCyVJkiRJkiSNbpBrED62qpYBtI+bteXzgOs76i1ty+a1z7vLH9KmqlYAdwCP6XXSJAuSLE6yePny5VN0KZIkSZIkSdLaaU28SUmvkX81RvlYbVYurDqmqrarqu3mzJmzmiFKkiRJkiRJM8MgE4Q3tdOGaR9vbsuXAlt01NscuKEt37xH+UPaJJkNPJqVpzRLkiRJkiRJ6jLIBOEiYL/2+X7AqR3le7V3Jt6a5mYkP2inId+ZZId2fcF9u9qMHOvVwLfadQolSZIkSZIkjWF2P06S5ERgR2DTJEuB9wOHAycnOQC4DtgToKouT3Iy8FNgBXBgVd3fHupNNHdEXh/4ersBfBY4IckSmpGDe/XhsiRJkiRJkqS1Xl8ShFX12lF27TRK/cOAw3qULwae3qP8HtoEoyRJktZMSXYG/hOYBXymqg7v2p92/67A3cD+VXXxWG2THAr8DTBy97l3V9Xp0381kiRJM8eaeJMSSZIkzTBJZgGfAHYBtgFem2Sbrmq70CwvMx9YABw1zrZHVNW27WZyUJIkaYJMEEqSJKkftgeWVNXVVXUfcBKwe1ed3YHjq3EBsFF7M7vxtJUkSdJqMkEoSZKkfpgHXN/xemlbNp46q2p7UJJLkxybZONeJ0+yIMniJIuXL1/eq4okSdLQMkEoSZKkfkiPshpnnbHaHgU8EdgWWAZ8tNfJq+qYqtquqrabM2fOuAKWJEkaFn25SYkkSZKG3lJgi47XmwM3jLPOeqO1raqbRgqTfBo4bepCliRJGg6OIJQkSVI/XATMT7J1kvWAvYBFXXUWAfumsQNwR1UtG6ttu0bhiFcBP5nuC5EkSZppHEEoSZKkaVdVK5IcBJwJzAKOrarLk7yx3X80cDqwK7AEuBt4w1ht20N/JMm2NFOOrwH+tm8XJUmSNEOYIJQkSVJfVNXpNEnAzrKjO54XcOB427bl+0xxmJIkSUPHKcaSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEDNBKEmSJEmSJA0xE4SSJEmSJEnSEJtRCcIkOye5MsmSJIcMOh5JkiQ9aFV9tTSObPdfmuTZq2qbZJMkZyW5qn3cuF/XI0mSNFPMmARhklnAJ4BdgG2A1ybZZrBRSZIkCcbdV9sFmN9uC4CjxtH2EODsqpoPnN2+liRJ0gTMmAQhsD2wpKqurqr7gJOA3QcckyRJkhrj6avtDhxfjQuAjZLMXUXb3YGF7fOFwB7TfB2SJEkzzuxBBzCF5gHXd7xeCjy3u1KSBTTfSAPcleTKPsSmmWlT4JZBB6GpkX/fb9AhSBPlZ9BM8v4M4qyP7/P5xtNX61Vn3iraPraqlgFU1bIkm/U6uX1ATSE/f2cQ+4BaC/kZNJOsQX3AmZQg7PWu1koFVccAx0x/OJrpkiyuqu0GHYek4eRnkNZC4+mrjVZnXP28sdgH1FTx81fSIPkZpOkyk6YYLwW26Hi9OXDDgGKRJEnSQ42nrzZanbHa3tROQ6Z9vHkKY5YkSRoKMylBeBEwP8nWSdYD9gIWDTgmSZIkNcbTV1sE7NvezXgH4I52+vBYbRcBI3ME9wNOne4LkSRJmmlmzBTjqlqR5CDgTGAWcGxVXT7gsDSzOU1J0iD5GaS1ymh9tSRvbPcfDZwO7AosAe4G3jBW2/bQhwMnJzkAuA7Ys4+XpeHk56+kQfIzSNMiVRNavkWSJEmSJEnSDDKTphhLkiRJkiRJmiAThJIkSZIkSdIQM0EoTbMk5yTZrn1+epKNJnm8HZOcNiXBSRoKU/HZI0maGPuAkgbNPqAmYsbcpERaHUlmV9WKfp2vqnbt17kkKUlo1hv2s0eSOtgHlDST2QfU6nAEodZ6SbZK8rMkC5NcmuSUJI9I8pwk30nywyRnJpnb1j8nyb8m+Q7wliR7JvlJkh8nObet8/Ak/53ksiQ/SvJnbfn+Sb6U5IwkVyX5SEccRyVZnOTyJB8YJdZrkmya5I1JLmm3XyT5drv/ZUnOT3Jxkv9JskFbvnN7jd8D/t/0vqOSpluSf2r/TZ+V5MQk70jyxPaz5YdJvpvkD9u6xyU5Msn3k1yd5NUdx/nHJBe1n30faMu2SnJFkk8CFwNbjHz2tPv3bev/OMkJg7h+SZoK9gElrW3sA2pN5ghCzRRPAQ6oqvOSHAscCLwK2L2qlid5DXAY8Fdt/Y2q6kUASS4DXl5Vv8yDw68PBKiqP2o/oL+R5Mntvm2BZwH3Alcm+a+quh54T1XdlmQWcHaSZ1TVpb2CraqjgaOTrAt8C/hY+8H9XuAlVfWbJO8E3tZ2QD8NvBhYAnxxKt4wSYORZrrZX9B8jsym6cD9EDgGeGNVXZXkucAnaf7dA8wFXgD8IbAIOCXJy4D5wPZAgEVJXghcR/OZ+IaqenN7zpFzPw14D/D8qrolySbTf8WSNK3sA0paK9gH1JrOBKFmiuur6rz2+eeAdwNPB85qPxRnAcs66nd2sM4DjktyMvCltuwFwH8BVNXPklwLjHQOz66qOwCS/BR4PHA98JdJFtD8u5oLbAP07Bx2+E/gW1X11SSvaNuc18a8HnA+zR+DX1TVVe05PwcsGM+bImmN9ALg1Kr6LUCSrwIPB54H/M9IRw54WEebr1TVA8BPkzy2LXtZu/2ofb0BTWfxOuDaqrqgx7lfDJxSVbcAVNVtU3ZVkjQY9gElrS3sA2qNZoJQM0V1vb4TuLyq/mSU+r/5fcOqN7bf1OwGXJJkW5pvYkZzb8fz+4HZSbYG3gH8cVXdnuQ4mg/7USXZn6ZjedBIEXBWVb22q962rHx9ktZevT5f1gF+VVXbjtKm83MnHY8fqqpPPeTgyVZ0fMb1OLefJ5JmEvuAktYW9gG1RnMNQs0UWyYZ6Qi+FrgAmDNSlmTddlj1SpI8saourKr3AbcAWwDnAq9r9z8Z2BK4cozzb0jzYXxH+83OLmMFm+Q5NJ3J17ffCNHG/PwkT2rrPKI998+ArZM8seP6JK29vge8Ms06VxvQ/Mf0buAXSfaEZmHpJM9cxXHOBP4qD65TNS/JZqtoczbNSJfHtG2cXiJpbWcfUNLawj6g1miOINRMcQWwX5JPAVfRTA05EzgyyaNpftf/A7i8R9t/SzKf5luVs4Ef03TIjm7XplkB7F9V93YM+36Iqvpxkh+1x7+aZsrKWA4CNgG+3R5zcVX9dfuN8olJRoaVv7eqft5OW/laklto/rA8fVVviKQ1U1VdlGQRzWfNtcBi4A6a/5AeleS9wLrASW2d0Y7zjSRPBc5vP0fuAl5PM6pltDaXJzkM+E6S+2mmpuw/FdclSQNiH1DSWsE+oNZ0qXKUqdZu7VDq06rKDpOktUKSDarqriSPoBmtsqCqLh50XJK0NrEPKGltYx9QazJHEEqS1H/HJNmGZp2qhXYMJUmShoJ9QK2xHEEoSZIkSZIkDTFvUiJJkiRJkiQNMROEkiRJkiRJ0hAzQShJkiRJkiQNMROEkjRJSbZMcleSWe3rc5L89YBjel2SbwwyBkmSpJnMPqCkmcQEoaQZK8k1SX7bdtxGto9P9Xmq6rqq2qCq7l9FPK9tY0pX+ewkNyd5xRTG9PmqetlUHU+SJGltYR/QPqCkiTNBKGmme2XbcRvZDhpgLF8GNgJe1FW+M1DAGeM9UBp+hkuSJPVmH1CSJsAPFklDKcn+Sc5LckSSXyW5Osnz2vLr229z9+uov1uSHyX5dbv/0I59WyWpJLPHOmdV3QOcDOzbtWtf4PNVtSLJDkm+38b04yQ7dpznnCSHJTkPuBt4Qhvv1UnuTPKLJK/ruL7vdbR9XpKLktzRPj6v67j/3L4fdyb5RpJNV+NtlSRJWqPZB7QPKKk3E4SShtlzgUuBxwBfAE4C/hh4EvB64ONJNmjr/oamE7cRsBvwpiR7rMY5FwKvTrI+QJJHA68Ejk8yD/ga8C/AJsA7gP9NMqej/T7AAuBRwHLgSGCXqnoU8Dzgku4TJtmkPe6R7bV+DPhaksd0VNsbeAOwGbBee25JkqSZyD7gg+wDSgJMEEqa+b7SfhM7sv1Nx75fVNV/t+vGfBHYAvhgVd1bVd8A7qPpKFJV51TVZVX1QFVdCpzIytNEVqmqzgNuAl7VFv0l8POquoSmQ3p6VZ3enucsYDGwa8chjquqy6tqBbACeAB4epL1q2pZVV3e47S7AVdV1QlVtaKqTgR+RtMpHfHfVfXzqvotzTfc20702iRJktYg9gHtA0qaABOEkma6Papqo47t0x37bup4/luAquou2wAgyXOTfDvJ8iR3AG8EVncKxvE8OMVkH5pvlAEeD+zZ2ZkFXgDM7Wh7/ciTqvoN8Jo2lmVJvpbkD3uc73HAtV1l1wLzOl7f2PH8btrrliRJWkvZB7QPKGkCTBBK0vh8AVgEbFFVjwaOBjJ2k1EdD+yU5E+AHdpjQ9PxO6GrM/vIqjq8o211Hqiqzqyql9J0IH8GdHZ+R9xA0/HstCXwy9WMX5IkaVjYB5Q0FEwQStL4PAq4raruSbI9zXotq6WqrgW+RzNF5ayqGvnm9nPAK5O8PMmsJA9PsmOSzXsdJ8ljk/x5kkcC9wJ3Aff3qHo68OQkeyeZneQ1wDbAaat7DZIkSUPCPqCkoWCCUNJM99Ukd3VsX17N47wZ+GCSO4H30azRMhkLab7RPX6koKquB3YH3k2z+PT1wD8y+mf1OsDbab4dvo1mPZw3d1eqqluBV7R1bwUOBl5RVbdM8hokSZLWVPYB7QNKmoBU1aprSZIkSZIkSZqRHEEoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQ+//Va3Elruhk9wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='email_version', data=full_data, ax=ax[0])\n",
    "ax[0].set_xlabel('Email Version', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of Email Version', fontsize=16)\n",
    "\n",
    "sns.barplot(x='email_version', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('Email Version', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. Email Version', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "54d9419a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='hour', data=full_data, ax=ax[0])\n",
    "ax[0].set_xlabel('Email Sent Hour', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of Email Sent Hour', fontsize=16)\n",
    "\n",
    "sns.barplot(x='hour', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('Email Sent Hour', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. Email Sent Hour', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7d289f26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='weekday', data=data, ax=ax[0])\n",
    "ax[0].set_xlabel('Email Sent Weekday', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of Email Sent Weekday', fontsize=16)\n",
    "\n",
    "sns.barplot(x='weekday', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('Email Sent Weekday', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. Email Sent Weekday', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b93e5a15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='user_country', data=full_data, ax=ax[0])\n",
    "ax[0].set_xlabel('User Country', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of User Country', fontsize=16)\n",
    "\n",
    "sns.barplot(x='user_country', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('User Country', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. User Country', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "519a259b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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b0iSGurd9IgE83xj06TTvxZ8CG1fVwXXnBfL+C3gpzYEDT27rvbxdNhGDrqCZlrsOTfJwVZsInu8O/o+3/T0M2KKqHlxVX59He5PFoJf1uO60348kD6c59c+NNFPkd6cZ+49Y8/P9SprZWi+iSfJdlebcnBM7mbekORL3RtZ8rye+yxPv9UyxrMaM5yCUhqiqbktzIYYnp7erXl0DbDVJ+Vas+QNzE03A2m2Y54+4taqWz6L+xPin2r7ZtDXhWpqjyKZq8+o5tHk1zRSJ+0yx/D50jLWqrqIJeF6e5sIoh9Ccn2g18MG2vYuAZ0/R3sVdz2uW4/3FNO/DQcAnquqfJwo6Atw7O6z6IfDMdk/jrjTnMDohyUOq6iezHM+Ea2b4fMz2M9z9uvwGuGeSDXtMEk5nb5pzxzy7qv74z2L3kX1VdSvNeV3ekWQrYF+aK2puRJMonvi8PYXms9nt6radognyPpzmgjFPoTkn4Wdp/vGRJHWYQzzVi4lzts3kGpqpkacCn0ny3BrdlYO7fwtnE1vdTJNA6DRVgmiNI7nao5UGkUDojBXOSfJbmsTSK4F3tuUHASuq6tCO8axH7zHvbOOwbp+kSag8Pcm5NMmbQzor9DGOmkjm3CUGbdveko7z21XVhcDB7eyVhwCvAD6Q5OJqzp98ddvmq6fo74Ku57ONQX9Sd17FuHOsdwP2p5mu+96O8j/vrltVXwW+mmQDmindbwX+J8n2VTVVUnomV/QQg67xXUjXxeS6h9n1/Dc0O+b74Zk0Sd9ntHHmxHjuQcc5E6s5l+jrgdcnuR/N9Oy30xw1+Dqa9/ommqnGk7m8bWemWFZjxiMIpeF7O00A9s7JFqa5gt6D26dfB56WZNOO5ZvSnHC2c8/Xr4EHdh4WnmQPmpM4z8VEoL3htLXm5wKaoOagzsIkj6HZs9u5fbf0Mpaq+h3wfeDAzkPt2x/Ox3S12ZM22XQucEC6rm6X5mp19+fOqz53r3tBVb2BJjk0ETicQXPS8xuravkkt7kGP73YiGbvYacXTlW5qm6rqu/QnLNmHZqTG8NgPh/z/Qx/iebo0Zf0YSwTicDOwOyBNIHqpKpqVVV9lObiKBPv9Vk059a57xTv9UWTtHNtVX2W5qp4/Qo2JWkxmk081YsvAfum62q/k6mqrwFPbW/Hp+MqsSM2m9jq19z1d+ZpXc9XtrcDu8oPYDgHmhxLc/G8f+jYSbcRd53e/ALuepTdVLHKvOKwqvoVzTTVF7S33wGTzoiYJo7q1S9pXv9nTLJsX5qk1l1i0Gr8EPi7tqgzBv1T4JIptv2GWY6vVxvQvD/dMeihU61QVTdX1VdoLtCzMXdeWORm+v//yWTfhX1nsf6XgK3ao1vnayOaAxP+mIRM8kSmmaZfVb+uqnfRTFfufK/vBtx9ivf6LtOrp4hlNWYWyo+ZNDaq6htJ/g54d5I/oznZ7iU002P3pElwPJdmeurbaH6gzk7yDpofi9fR/Hi8taPZ44HDgI8nOYbmR/TvaM5DNxe/oAm+XpTkGpof4wv6GThUc/XWN9EcNXUczZSNbWhOJPxLmj3GE35Kkyg9gybZdvk05w35J5rze5ya5AM056R5C81r8a45DveNNMmeryT5EM3e112Af2zH9gmAJHen+VH9FHeeh2V/mvd24pwfn6JJyp2d5F00UwbWp7kq4H40F674/RzHOZMzgEOSnEcz7fUZdF1VL8m+NJ+lL9LsYd+Y5orPN9AExHDnFa1fm+R04PZZHj06mXl9hqvqq0k+T/O92o7mKtbr0Uyl+Z/2n7lefZnm8/+J9j3amuYzdAkdO9aSnEzz/v2A5nP5MJqjDz/cjulX7ff2/e3RpF+n2Zu7Hc30mo+24/4Id76+V9GcZ+YF3PmZkSR1mWU81Ys3004dTvIvNL+T2wB7V9XzJ+n/m0n2ppkW+9kkB3Ue8TMKs4ytjgf+Mckbaa66+hfAc7rauyPJW4D/TPJRmqmo9wcOp/l9nuo0Mv3anmq351SaU3G8iyaWOSDJ0W35I2jilOu6Vp8qVulHHPYJ4D+AP6e5mNwfrwzdSxzV7rj+FfDWqnorU2i3//XAJ9sY59M05zDelea8el+hOTUJbTL8vTSzD1bQJOQOpYlnvtI2eTTNUWHfbF+/C9rx/SnwF1W1/wzbPSdV9dsk36F5L66gOeLuRXQdsZvkpTRx22k05zPfguYouctpLsoBzft6z3bq9HLgpqo6b55DPJ4m/pz4TD2EaZKXkzgO+GuaI4r/lebAgk1ppku/p6p+Pou2zqCZXn9Mkv+iiQn/ia4pzEnOoTml0Xk004gf3477WGh2YiT5DHBiknfTTKG/g+ZCRPsAr6uqX8wUy2oM1QK4Uoo3b+N4o0nMfI5m+sbECX2/RDNtZZ2Oeo+iSVjcSLOX8mxgt0na+xua4O8PNOfFeQRTXwH2AV3rHkHXFX3b9i6kCSwKeMI023IMM1xRjK4r43WUP5/mh+lmmsPhPwls3VXnsTRHBt7EJFfdm6SvvWmCsD/QBLAnAzt11enpKsZdYzid5sfzVpp/Qt5Pe+W1ts4GND+o57fv1/U05wV5bldbd2tf85+3231NW+8I7ryC3BOY3ZWkZ6xPE2gd327DtTRB8iM73xeaEyB/liaovYlmavRpwKM62lmXJjC+iibYmPZ1pOMqezPUm/NnuF22hCaZ+wuao04nxr7TdK8Rk1/d8tnt+3NT+34eRPM5v7ijzmtp/qmaOBfWBe17uF5X+y9o6/2u/Vz8rP3sbNsuP4TmKs5XtZ+Hi2iC+Cmv4ufNmzdv3pobPcRTU/ydX+P3pS37E+AzNAmMm2nioKM7lh9DV7wDPJom1vgisH4P4z2Cma9i3MvvVAH/PEUfvcRWd6NJKF1Bk7z6LM25iSeL1V5Dc5TVTTRJmcfRxBFHTzLGGWPMKcZ8MVPECjQXmruC5sixdWhiuMuB39PsfHtY9/vJNLEKPcRhM4z1Hu16BTyla1kvcdT29BDPdtSfmDl0A01880uac8d1XsF6S5rk0C/a1+Wadp29Jhn70e34bmlfn28Cr5npvZxmfDPWb7f59HYbrqKJg55Gx/8YNN+lk2mSgze37/nn6IjhaRKan+HO0wpdPMPYpvyedNRZh+bCir9uX7szaf4WrPEeMf13dxOao5l/3b6uVwAn0l4Ve6rXiMn/B3tl+/78of1cPokmTvxaR513AP9H87fndzSJwldNsl2vpvlbcFNb90c0R2Xeva3TUyzrbXxuaT8YkiRJkiRNK8kjaY5IOriqPjnq8UiS+sMEoSRJkiTpLpLsQHPxtW/SzIz4M5rprbcAu9TgTosiSRoyz0EoSZIkSZrMH2jOu3wwzfTUa2lOfXO4yUFJWlw8glCSJEmSJEkaY+vMXEWSJEmSJEnSYjXWU4y32GKL2n777Uc9DEmSpAXj+9///m+qaumox9EPxnqSJElrmirWG+sE4fbbb8/y5ctHPQxJkqQFI8mvRz2GfjHWkyRJWtNUsZ5TjCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxNpQEYZKPJ7kqyU8mWfb3SSrJFh1lr0+yIskFSfbqKH9EkvPaZe9LkrZ8gySfbcvPTbL9MLZLkiRJkiRJWtsN6wjCY4C9uwuTbAc8Gbiko2xn4CDgQe06H0iybrv4g8BhwI7tbaLNFwPXVtUDgKOBdwxkKyRJkiRJkqRFZigJwqr6BnDNJIuOBpYB1VG2P3B8Vd1cVRcBK4DdkmwNbFZV51RVAZ8ADuhY59j28YnAnhNHF0qSJEmSJEma2sjOQZhkP+CyqvpR16JtgEs7nq9sy7ZpH3eXr7FOVd0G/Ba41xT9HpZkeZLlq1evnvd2SJIkaX6mOx1Nuzzt6WVWJPlxkocPe4ySJEmL2UgShEk2At4IvGmyxZOU1TTl061z18Kqj1TVrlW169KlS3sZriRJkgbrGCY5HU2Hp3LnKWYOozntjCRJkvpkyYj6/RNgB+BH7UzgbYEfJNmN5sjA7Trqbgtc3pZvO0k5HeusTLIEuDuTT2mWJEnSAlNV35jhInP7A59oTzPznSSbJ9m6qq4YzgglSZJ6t2zZMlatWsVWW23FUUcdNerh9GQkCcKqOg/YcuJ5kouBXavqN0lOAT6d5N3AfWj2FH+3qm5PckOS3YFzgYOBf2+bOAU4BDgHeBbwlTaA7NnqDx43z61a09KXPb+v7UmSJI2xqU5Bc5cEYZLDaI4y5L73ve9QBidJktRp1apVXHbZZXNe/6r3n97H0cCWr3jqjHWGMsU4yWdoknc7JVmZ5MVT1a2q84ETgJ8CZwAvr6rb28UvAz5Kc+GSXwETr9jHgHslWQH8HXD4QDZEkiRJo+DpZCRJkgZoKEcQVtVzZli+fdfzI4EjJ6m3HNhlkvKbgAPnN0pJkiQtUFOdgkaSJEl9MLKrGEuSJEk9OgU4uL2a8e7Abz3/oCRJUv+M6iIlY+nKD/b3xJT3ftmyvrYnSZI0Cu3paJ4AbJFkJfBmYD2AqvoQcBqwD81pZn4PvHA0I5UkSVqcTBBKkiRppHo4HU0BLx/ScCRJksaOU4wlSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMbZk1ANQf138vgP63ub2r/pi39uUJEmSJEnSwuARhJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYG0qCMMnHk1yV5CcdZe9M8vMkP07yhSSbdyx7fZIVSS5IsldH+SOSnNcue1+StOUbJPlsW35uku2HsV2SJEmSJEnS2m5YRxAeA+zdVXYWsEtVPRj4BfB6gCQ7AwcBD2rX+UCSddt1PggcBuzY3ibafDFwbVU9ADgaeMfAtkSSJEmSJElaRJYMo5Oq+kb3UX1V9aWOp98BntU+3h84vqpuBi5KsgLYLcnFwGZVdQ5Akk8ABwCnt+sc0a5/IvD+JKmqGsgGiXM/vG9f23vU35za1/YkSZIkSZLUm4VyDsIX0ST6ALYBLu1YtrIt26Z93F2+xjpVdRvwW+BeAxyvJEmSJEmStCiMPEGY5I3AbcCnJoomqVbTlE+3zmT9HZZkeZLlq1evnu1wJUmSJEmSpEVlpAnCJIcA+wLP65gOvBLYrqPatsDlbfm2k5SvsU6SJcDdgWsm67OqPlJVu1bVrkuXLu3XpkiSJEmSJElrpZElCJPsDbwO2K+qft+x6BTgoPbKxDvQXIzku1V1BXBDkt3bqxcfDJzcsc4h7eNnAV/x/IOSJEmSJEnSzIZykZIknwGeAGyRZCXwZpqrFm8AnNXk+/hOVb20qs5PcgLwU5qpxy+vqtvbpl5Gc0XkDWnOWThx3sKPAZ9sL2hyDc1VkCVJkiRJkiTNYFhXMX7OJMUfm6b+kcCRk5QvB3aZpPwm4MD5jFGSJEmSJEkaRyO/SIkkSZIkSZKk0TFBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEkaqSR7J7kgyYokh0+y/O5J/jvJj5Kcn+SFoxinJEnSYmWCUJIkSSOTZF3gP4CnAjsDz0myc1e1lwM/raqHAE8A3pVk/aEOVJIkaREzQShJkqRR2g1YUVUXVtUtwPHA/l11Ctg0SYBNgGuA24Y7TEmSpMXLBKEkSZJGaRvg0o7nK9uyTu8H/gy4HDgPeHVV3TFZY0kOS7I8yfLVq1cPYrySJEmLjglCSZIkjVImKauu53sBPwTuAzwUeH+SzSZrrKo+UlW7VtWuS5cu7ec4JUmSFi0ThJIkSRqllcB2Hc+3pTlSsNMLgZOqsQK4CPjTIY1PkiRp0TNBKEmSpFH6HrBjkh3aC48cBJzSVecSYE+AJPcGdgIuHOooJUmSFrElox6AJEmSxldV3ZbkFcCZwLrAx6vq/CQvbZd/CHgbcEyS82imJL+uqn4zskFLkiQtMiYIJUmSNFJVdRpwWlfZhzoeXw48ZdjjkiRJGhdOMZYkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmOcg1IJ1+sf26Wt7T33xaTNXkiRJkiRJGjMeQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgzQShJkiRJkiSNMROEkiRJkiRJ0hgbSoIwyceTXJXkJx1l90xyVpJftvf36Fj2+iQrklyQZK+O8kckOa9d9r4kacs3SPLZtvzcJNsPY7skSZIkSZKktd2wjiA8Bti7q+xw4Oyq2hE4u31Okp2Bg4AHtet8IMm67TofBA4DdmxvE22+GLi2qh4AHA28Y2BbIkmSJEmSJC0iQ0kQVtU3gGu6ivcHjm0fHwsc0FF+fFXdXFUXASuA3ZJsDWxWVedUVQGf6Fpnoq0TgT0nji6UJEmSJEmSNLVRnoPw3lV1BUB7v2Vbvg1waUe9lW3ZNu3j7vI11qmq24DfAvearNMkhyVZnmT56tWr+7QpkiRJkiRJ0tppIV6kZLIj/2qa8unWuWth1Ueqateq2nXp0qVzHKIkSZIkSZK0OIwyQXhlO22Y9v6qtnwlsF1HvW2By9vybScpX2OdJEuAu3PXKc2SJEmSJEmSuowyQXgKcEj7+BDg5I7yg9orE+9AczGS77bTkG9Isnt7fsGDu9aZaOtZwFfa8xRKkiRJkiRJmsaSYXSS5DPAE4AtkqwE3gy8HTghyYuBS4ADAarq/CQnAD8FbgNeXlW3t029jOaKyBsCp7c3gI8Bn0yygubIwYOGsFmSJEmSJEnSWm8oCcKqes4Ui/acov6RwJGTlC8Hdpmk/CbaBKMkSZIkSZKk3i3Ei5RIkiRJkiRJGhIThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSZIkSdIYM0EoSZIkSZIkjTEThJIkSeqLJNsl2X3U45AkSdLsmCCUJEnSvCS5b5L/BX4OfLkte1aSj452ZJIkSeqFCUJJkiTN14eB/wE2BW5ty84CnjyyEUmSJKlnS0Y9AEmSJK31dgOeVlV3JCmAqvptkruPeFySJEnqgUcQSpIkab6uBB7QWZBkZ+CS0QxHkiRJs2GCUJIkSfP1b8CpSV4ILEnyHOCzwDtGOyxJkiT1winGkiRJmpeq+niSa4DDgEuBg4F/qqovjnRgkiRJ6okJQkmSJM1Lkke1ycAvdpXvVlXfHcmgJEmS1DOnGEuSJGm+zpqi/IyhjkKSJElz4hGEkiRJmpMk6wBpHibt4wl/Atw2koFJkiRpVkwQSpIkaa5uA6rjcac7gCOHOxxJkiTNhQlCSZIkzdUONEcNfh3Yo6O8gNVV9YeRjEqSJEmzYoJQY+9Tx+zV1/aed+iZfW1PkqSFqqp+3T6830gHIkmSpHkxQShJkqR5S7If8HhgCzrORVhVB49sUJIkSeqJVzGWJEnSvCR5M/BhmtjyQOBqYC/guhEOS5IkST0yQShJkqT5ehHw5Kr6W+CW9v4vge1HOipJkiT1xAShJEmS5mvzqvpJ+/iWJOtV1XdpphxLkiRpgfMchJIkSZqvXyV5UFWdD/wEeFmSa4FrRzwuSZIk9cAEoSRJkubrH4F7tY8PBz4NbAK8fGQjkiRJUs9MEEqSJGlequq0jsffBR4AkGS9kQ1KkiRJPfMchJIkSeqrJBskeSVw4ajHIkmSpJmZIJQkSdKcJNkpyTeT3JDkB0l2SfJMmsTgC4DXjniIkiRJ6oFTjCVJkjRX7wNWAP8CPBc4GfgDcEhVfXmUA5MkSVLvTBBKkiRprh4B7FdVNyf5BnA9cL+qWjnicUmSJGkWnGIsSZKkuVq/qm4GqKrfAb81OShJkrT28QhCSZIkzdUGSd7a8XzDrudU1ZuGPCZJkiTNkglCSZIkzdWnge06nh/f9byGOxxJkiTNhQlCSZIkzUlVvbAf7STZG3gvsC7w0ap6+yR1ngC8B1gP+E1VPb4ffUuSJMkEoSRJkkYoybrAfwBPBlYC30tySlX9tKPO5sAHgL2r6pIkW45ksJIkSYuUFymRJEnSKO0GrKiqC6vqFpppyvt31XkucFJVXQJQVVcNeYySJEmLmglCSZIkjdI2wKUdz1e2ZZ0eCNwjydeSfD/JwVM1luSwJMuTLF+9evUAhitJkrT4mCCUJEnSKGWSsu6LmywBHgE8DdgL+KckD5yssar6SFXtWlW7Ll26tL8jlSRJWqQ8B6EkSZLmLclOwEOATTrLq+rjM6y6kjWvfLwtcPkkdX5TVb8DfpfkG21fv5jXoCVJkgSYIJQkSdI8JXkD8CbgR8DvOxYVMFOC8HvAjkl2AC4DDqI552Cnk4H3J1kCrA88Cji6D0OXJEkSJgglSZI0f68BdquqH892xaq6LckrgDOBdYGPV9X5SV7aLv9QVf0syRnAj4E7gI9W1U/6N3xJkqTxNvIEYZK/BV5Cs4f5POCFwEbAZ4HtgYuBZ1fVtW391wMvBm4HXlVVZ7bljwCOATYETgNeXVXd56+RJElS//0B+PlcV66q02jit86yD3U9fyfwzrn2IUmSpKmN9CIlSbYBXgXsWlW70Ow1Pgg4HDi7qnYEzm6fk2TndvmDgL2BDyRZt23ug8BhwI7tbe8hbookSdJYSbLOxA34J+Dfk2zdWd4ukyRJ0gK3EIK2JcCG7TllNqI5KfX+wLHt8mOBA9rH+wPHV9XNVXURsALYLcnWwGZVdU571OAnOtaRJElS/90G3NrejgH+muZiIhNlE8slSZK0wI10inFVXZbk34BLaKamfKmqvpTk3lV1RVvniiRbtqtsA3yno4mVbdmt7ePu8rtIchjNkYbc97737efmSJIkjZMdRj0ASZIk9cdIE4RJ7kFzVOAOwHXA55I8f7pVJimracrvWlj1EeAjALvuuqvnKJQkSZqDqvr1qMcgSZKk/ug5QZjkwKr63CTlz6qqE+fY/5OAi6pqddvWScBjgCuTbN0ePbg1cFVbfyWwXcf629JMSV7ZPu4ulyRJ0oAl+SST75y9mSZO+2JV/Wi4o5IkSVKvZnMOwo9NUf6RefR/CbB7ko2SBNgT+BlwCnBIW+cQ4OT28SnAQUk2SLIDzcVIvttOR74hye5tOwd3rCNJkqTB+i3NrJDQJAQD7AfcDvwZcE6Sg0c3PEmSJE1nxiMIk9y/fbhOm5TrnM57f+CmuXZeVecmORH4Ac2JrP+PJuG4CXBCkhfTJBEPbOufn+QE4Kdt/ZdX1e1tcy+jOUH2hsDp7U2SJEmD90Bgn6r634mCJI8G3lpVT06yN/AemgvJSZIkaYHpZYrxCu48z9+vupatAo6YzwCq6s3Am7uKb6Y5mnCy+kcCR05SvhzYZT5jkSRJ0pw8Cji3q2w5sFv7+EzWPB2MJEmSFpAZpxhX1TpVtS7wzfZx5+0+7UU/JEmSNL5+CByZ5G4A7f3bgInzDu4AXDOaoUmSJGkmPZ+DsKoeP8iBSJIkaa11CPAXwPVJVgHXA3tw5zml7wn8fyMamyRJkmYwm6sY70AztfehNOcI/KOqum9/hyVJkqS1RVVdDDwmyX2BrYErquqSjuXLRzU2SZIkzaznBCHwaZpzEL4W+P1ghiNJkqS1TZKJWSkr29sfy6rqjlGNS5IkSb2ZTYLwQcBjDfIkSZLU5Taai9pNZt1hDkSSJEmzN5sE4TeAhwHfH9BYJEmStHbaoev51sDhwH+PYCySJEmapdkkCC8GzkxyErCqc0FVvamfg5IWm/cft1df23vF88/sa3uSJM1HVf26q+jXSQ4Bvgd8bARDkiRJ0izMJkG4Mc1e4PWA7QYzHEmSJC0SmwFLRz0ISZIkzaznBGFVvXCQA5EkSdLaKcknWfMchBsBewDHjWZEkiRJmo2eE4RJ7j/Vsqq6sD/DkSRJ0lpoRdfz3wEfqqovj2IwkiRJmp3ZTDFeQbNnOB1lE3uKvTqdJEnSmKqqt4x6DJIkSZq7dXqtWFXrVNW67f06wH2AjwAvGNjoJEmStFZI8sIkX0lyQXvv6WkkSZLWErM5gnANVbUqyWuAXwCf7tuIJEmStFZJ8kbgYOBdwK+B+wHLktynqo4c6eAkSZI0ozknCFs70ZyEWpIkSePrJcATqurXEwVJzgS+AZgglCRJWuBmc5GSb3LXq9M9CHhrvwclSZKktcrGwOqusquBDUcwFkmSJM3SbI4g/GjX898BP6qqX/ZxPJIkSVr7nAF8KsnhwCU0U4yPBM4c6agkSZLUk54ThFV17CAHIkmSpLXWK4D3Az8C1gNuBU4AXjXKQUmSJKk3PV/FOMl6Sd6S5MIkN7X3b0my/iAHKEmSpIUrybrA3wOH0ZyCZmtgo6o6uKquG+XYJEmS1JueE4TAUcCTgJcCD2nvnwi8YwDjkiRJ0lqgqm4HXg7cUlV3VNVVVXXHqMclSZKk3s3mHIQHAg+pqqvb5xck+QHNVJK/7fvIJEmStLY4lmbn8QdGPRBJkiTN3mwShJlluSRJksbDbsArkywDLgVqYkFV7TGyUUmSJPXRle/9Tk/1br/upj/ez7TOvV+9+7zH1Q+zSRB+DvjvJG/hzqvT/WNbLkmSpPH1n+1NkiRJa6HZJAiX0SQE/wO4D3AZ8BngnwcwLkmSJK0lqurYUY9BkiRJczdjgjDJY4H9qup1wJva28SydwAPB3o7xlKSJEmLUpKnAA8FNuksr6o3TbqCJEmSFoxermL8BuAbUyz7KvDG/g1HkiRJa5sk7weOAx4BbNd1kyRJ0gLXyxTjhwJnTLHsy8DH+zYaSZIkrY2eAzy0qi4d9UAkSZI0e70cQbgZsP4Uy9YDNu3fcCRJkrQWuhq4btSDkCRJ0tz0cgThz4GnACdPsuwp7XJJkiSNkST373j6LuBTSf4VuLKzXlVdONSBSZIkadZ6SRAeDXw4ybrAF6vqjiTrAAfQXNH47wY4PkmSJC1MKyYp27freQHrDmEskiRJmocZE4RV9ekkWwHHAhsk+Q2wBXAT8Oaq+syAxyhJkqQFpqp6OVWNJEmS1gK9HEFIVb07yUeBRwP3ojnPzDlVdf0gBydJkqSFK8l5VfXnox6HJEmS5qenBCFAmww8c4BjkSRJ0tpl+1EPQJIkSfPn1BBJkiTNVY16AJIkSZq/no8glCRJkrpslOQb01Woqj2GNRhJkiTNjQlCSZIkzdWtwMdGPQhJkiTNjwlCSZIkzdWtVXXsqAchSZKk+fEchJIkSZqrjHoAkiRJmj8ThJIkSZqrfxn1ACRJkjR/JgglSZI0J1X1r6MegyRJkubPBKEkSZIkSZI0xkaeIEyyeZITk/w8yc+SPDrJPZOcleSX7f09Ouq/PsmKJBck2auj/BFJzmuXvS+J58SRJEmSJEmSZjDyBCHwXuCMqvpT4CHAz4DDgbOrakfg7PY5SXYGDgIeBOwNfCDJum07HwQOA3Zsb3sPcyMkSZLGVZL7TFH+sGGPRZIkSbO3ZJSdJ9kM2AM4FKCqbgFuSbI/8IS22rHA14DXAfsDx1fVzcBFSVYAuyW5GNisqs5p2/0EcABw+pA2RRq5fzqh/znxtz37jL63KUlalL6UZI+qumaiIMluwMnA1qMbliRJknox6iMI7w+sBv4ryf8l+WiSjYF7V9UVAO39lm39bYBLO9Zf2ZZt0z7uLr+LJIclWZ5k+erVq/u7NZIkSePpIzRJwk0AkjwGOAV48UhHJUmSpJ6MOkG4BHg48MGqehjwO9rpxFOY7LyCNU35XQurPlJVu1bVrkuXLp3teCVJktSlqt5Hc7TgaUmeCnwBeH5VnTbakUmSJKkXo04QrgRWVtW57fMTaRKGVybZGqC9v6qj/nYd628LXN6WbztJuSRJkoagqt4GfA/4LHBgVX15xEOSJElSj0aaIKyqVcClSXZqi/YEfkozJeWQtuwQmj3StOUHJdkgyQ40FyP5bjsN+YYku7dXLz64Yx1JkiT1WZJLk1zSeQP+iia+PK6jTJIkSQvcSC9S0nol8Kkk6wMXAi+kCSxPSPJi4BLgQICqOj/JCTRJxNuAl1fV7W07LwOOATakuTiJFyiRJEkanOePegCSJEnqj5EnCKvqh8Cukyzac4r6RwJHTlK+HNilr4OTJEnSpKrq66MegyRJkvpj1OcglCRJ0louyUlJ/qKr7C+SnDiqMUmSJKl3JgglSZI0X48Hvt1Vdg7w/0YwFkmSJM2SCUJJkiTN103Axl1lmwC39rJykr2TXJBkRZLDp6n3yCS3J3nWPMYqSZKkLiYIJUmSNF9nAh9OshlAe/9+4IyZVkyyLvAfwFOBnYHnJNl5inrvaPuSJElSH5kglCRJ0ny9FtgMuCbJVcA1wN2B1/Sw7m7Aiqq6sKpuAY4H9p+k3iuBzwNX9WXEkiRpQVm2bBkHH3wwy5YtG/VQxtLIr2IsSZKktVtVXQs8LcnWwLbApVW1qsfVtwEu7Xi+EnhUZ4Uk2wBPB54IPHK6xpIcBhwGcN/73rfHIUiSpFFbtWoVl1122aiHMbY8glCSJEmzliQdj9dJsg5wJfB94KqOshmbmqSsup6/B3hdVd0+U2NV9ZGq2rWqdl26dGkP3UuSJMkjCCVJkjQXv6WZVgxwG3dN6qUtW3eGdlYC23U83xa4vKvOrsDxbU5yC2CfJLdV1RdnP2xJkiR1M0EoSZKkuXhQx+Md5tHO94Adk+wAXAYcBDy3s0JV/bH9JMcAp5oclCRJ6h8ThJIkSZq1qrq04/Gv59HObUleQXN14nWBj1fV+Ule2i7/0LwHK0mSpGmZIJQkSdKsJfkkd51WfBdVdXAPdU4DTusqmzQxWFWH9jhESZIk9cgEoSRJkuZixagHIEmSpP4wQShJkqRZq6q3jHoMkiRJ6o91Rj0ASZIkrZ2SPCbJO6ZY9vYkuw97TJIkSZo9E4SSJEmaqzcC35hi2dfb5ZIkSVrgTBBKkiRprh4KnDHFsrOARwxvKJIkSZorE4SSJEmaq82A9adYth6w6RDHIkmSpDkyQShJkqS5+jnwlCmWPaVdLkmSpAXOqxhLkiRpro4GPpxkXeCLVXVHknWAA4D/AP5ulIOTJElSb0wQSpIkaU6q6tNJtgKOBTZI8htgC+Am4M1V9ZmRDlCSJEk9MUEoSZKkOauqdyf5KPBo4F7A1cA5VXX9aEcmSZKkXpkglCRJ0ry0ycAzRz0OSZIkzY0XKZEkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmAlCSZIkSZIkaYyZIJQkSZIkSZLGmAlCSZIkSZIkaYwtGfUAJK1dnnrKfn1t7/T9Tulre5IkSZIkaXY8glCSJEmSJEkaYyYIJUmSJEmSpDFmglCSJEmSJEkaYyYIJUmSJEmSpDFmglCSJEmSJEkaYwsiQZhk3ST/l+TU9vk9k5yV5Jft/T066r4+yYokFyTZq6P8EUnOa5e9L0lGsS2SJEmSJEnS2mRBJAiBVwM/63h+OHB2Ve0InN0+J8nOwEHAg4C9gQ8kWbdd54PAYcCO7W3v4QxdkiRJkiRJWnuNPEGYZFvgacBHO4r3B45tHx8LHNBRfnxV3VxVFwErgN2SbA1sVlXnVFUBn+hYR5IkSZIkSdIURp4gBN4DLAPu6Ci7d1VdAdDeb9mWbwNc2lFvZVu2Tfu4u/wukhyWZHmS5atXr+7LBkiSJEmSJElrq5EmCJPsC1xVVd/vdZVJymqa8rsWVn2kqnatql2XLl3aY7eSJEmSJEnS4rRkxP0/FtgvyT7A3YDNkhwHXJlk66q6op0+fFVbfyWwXcf62wKXt+XbTlIuSZIkSZIkaRojPYKwql5fVdtW1fY0Fx/5SlU9HzgFOKStdghwcvv4FOCgJBsk2YHmYiTfbach35Bk9/bqxQd3rCNJkiRJkiRpCqM+gnAqbwdOSPJi4BLgQICqOj/JCcBPgduAl1fV7e06LwOOATYETm9vkiRJkiRJkqaxYBKEVfU14Gvt46uBPaeodyRw5CTly4FdBjdCSZIkSZIkafFZCFcxliRJkiRJkjQiJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMWaCUJIkSZIkSRpjJgglSZIkSZKkMbZk1AOQpG77fOHNfW3vtKe/pa/tSZIkSZK0mHgEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSRJkkYqyd5JLkiyIsnhkyx/XpIft7dvJ3nIKMYpSZK0WJkglCRJ0sgkWRf4D+CpwM7Ac5Ls3FXtIuDxVfVg4G3AR4Y7SkmSpMXNBKEkSZJGaTdgRVVdWFW3AMcD+3dWqKpvV9W17dPvANsOeYySJEmLmglCSZIkjdI2wKUdz1e2ZVN5MXD6QEckSZI0ZpaMegCSJEkaa5mkrCatmPw/mgTh46ZsLDkMOAzgvve9bz/GJ0mS5mnFv185Y51br7v9j/cz1X/AK+/dl3HpTh5BKEmSpFFaCWzX8Xxb4PLuSkkeDHwU2L+qrp6qsar6SFXtWlW7Ll26tO+DlSRJWoxMEEqSJGmUvgfsmGSHJOsDBwGndFZIcl/gJOAFVfWLEYxRkiRpUXOKsSRJkkamqm5L8grgTGBd4ONVdX6Sl7bLPwS8CbgX8IEkALdV1a6jGrMkSb1YtmwZq1atYquttuKoo44a9XCkaZkglCRJ0khV1WnAaV1lH+p4/BLgJcMelyRJ87Fq1Souu+yyUQ9D6olTjCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQx5lWMJY2lp530vr63+T/PeFXf25QkSZIkadBMEEqSJEmSpLGxbNkyVq1axVZbbcVRRx016uFIC4IJQkmSJEmSNDZWrVrFZZddNuphSAuK5yCUJEmSJEmSxpgJQkmSJEmSJGmMjTRBmGS7JF9N8rMk5yd5dVt+zyRnJflle3+PjnVen2RFkguS7NVR/ogk57XL3pcko9gmSZIkSZIkaW0y6iMIbwNeW1V/BuwOvDzJzsDhwNlVtSNwdvucdtlBwIOAvYEPJFm3beuDwGHAju1t72FuiCRJkiRJ0jAtW7aMgw8+mGXLlo16KFrLjTRBWFVXVNUP2sc3AD8DtgH2B45tqx0LHNA+3h84vqpurqqLgBXAbkm2BjarqnOqqoBPdKwjSZIkSZK06ExccGXVqlWjHorWcqM+gvCPkmwPPAw4F7h3VV0BTRIR2LKttg1wacdqK9uybdrH3eWSJEmSJEmSprEgEoRJNgE+D7ymqq6fruokZTVN+WR9HZZkeZLlq1evnv1gJUmSJEmSpEVk5AnCJOvRJAc/VVUntcVXttOGae+vastXAtt1rL4tcHlbvu0k5XdRVR+pql2ratelS5f2b0MkSZIkSZKktdCor2Ic4GPAz6rq3R2LTgEOaR8fApzcUX5Qkg2S7EBzMZLvttOQb0iye9vmwR3rSJIkSZIkSZrCkhH3/1jgBcB5SX7Ylr0BeDtwQpIXA5cABwJU1flJTgB+SnMF5JdX1e3tei8DjgE2BE5vb5IkSZIkSZKmMdIEYVV9i8nPHwiw5xTrHAkcOUn5cmCX/o1OkiRJkiRJWvxGfg5CSZIkSZIkSaMz6inGkiRJkiRJACxbtoxVq1ax1VZbcdRRR416ONLYMEEoSZIkSZIWhFWrVnHZZZeNehjS2HGKsSRJkiRJkjTGPIJQkiRJkiQtCn910oUz1rnmxlsBuOLGW2es/9ln3P8uZe/9wqqexnLdjbf/8X6mdV799K16alMaFI8glCRJkiRJksaYRxBK0gDt+/lj+treqc88tK/tSZIkSZLkEYSSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI0xE4SSJEmSJEnSGDNBKEmSJEmSJI2xJaMegCRJkiRJWtiWLVvGqlWr2GqrrTjqqKPm1MYzPn/OjHVuuPEmAK648aYZ65/0zEfPaRyS7soEoSRJkiRJmtaqVau47LLLRj0MjUA/ksNa+EwQSpIkSZK0FjOBszid/LnfzFjndzfe8cf7mervf+AWcxqHyeHxYIJQkiRJkqS1mAkcSfPlRUokSZIkSZKkMWaCUJIkSZIkSRpjTjGWJEmSJEljY93NtljjXpIJQkmSJEmSBsYLiCw8d9/vb0c9BGnBMUEoSWu5fU/8XN/bPPVZB/a9TUmSpHE03wuI9BLr3XTjjQBcfuONM9afLM7b/8QzZuzjdzf+vu3j9z3VP/lZe89YR9LC4TkIJUmSJEmSpDHmEYSSJEmSJGlBWGfTzde4lzQcJgglSZIkSWPHcwMuTBvv98JRD0EaSyYIJUmSJEkLyjCSd/M9NyDAvp8/ZsY6N914PQCX33j9jPVPfeah8xqPFpaN2qskb+TVkrUWMEEoSZIkSVpQ+pG8k0bt0fu/ftRDkHpmglCSJEmS1DOn5i482XTTNe4labZMEEqSJEmSejbfo/v2+cKbZ6xzy41XA3D5jVfPWP+0p7/lLmVPO+l9M/Zx843XtX1cN2P9/3nGq2Zsb5Q2+Mt9Rz0ESWs5E4SSJEmSJA1INt1kjfu11TqbbsYd7b2kxccEoSSpJ/ufeEZf2zv5WXv3tT1JkhaytWFa7lNP2a+nerf87vcAXPa7y2dc5/T9Tpn3uNZ2G+z3pFEPoS82/Mtnj3oIkgbIBKEkSZIkDdgwLrqxNiQhJUkLkwlCSZIkSVoEFtWVfze7G2nvByWbbbTGvSSNMxOEkiRJkjQP7z9urxnrXHfDbe39ZTPWf8Xzz7xL2T+dMPOpOa6+8db2/rIZ67/t2XM/dUg2C9XeD8r6++8ysLb/2Md+jxl4H5K0tjBBKEmSJGlsOS139tZ7+oajHoKkPjnn2NUz1rnp+tv/eN9L/UcfsnTe49LwmSCUJC0Yz/j8OX1t76RnPrqv7UmShmsYybthTcvdeJMA1d5LkrSwmCCUJEmSNGvzTd6d/rF9Zqxz4S9u4dobit9ff/mM9Z/64tPuUvapY2ae+nvD9be195f1VP95h951+m8vHrvXunNabzY22LRJQjb3kiT1zgShJEmStIgMa8rsorogxiLxoKf5750kaW78BZEkSZKGZG2YMnvuh/ftqd5Nv72pvb98xnUe9Tenzmksm20MkPZ+MDZpp/5u4tRfSdIYM0EoSRorf3XShX1v87PPuH/f25S0OM03eXfx+w6Ysc5t193Y3l8+Y/3tX/XFOY9lGA584voD72PvJw1+6q8kDcqmmy5d416aKxOEkiRJUh9c+cGZjwi8/bfX/vF+pvr3ftmyOY3jXhutA9zR3g/OPTbOGveSpOF7+r5vHPUQtEgsqgRhkr2B9wLrAh+tqrePeEiSpDH13i+s6mt7r376Vn1tT1pIZorhkqRdvg/we+DQqvrB0Ae6lnjtYzYaSj8vevwGQ+lHkiQN3qJJECZZF/gP4MnASuB7SU6pqp+OdmSSJA3GyZ/7TV/b2//ALfrantSLHmO4pwI7trdHAR9s79c6SzfacI17SZKkhWDRJAiB3YAVVXUhQJLjgf0BE4SSJM3DOceu7mt7jz7krufIWfHvV/a1jwe88t59bU8D1UsMtz/wiaoq4DtJNk+ydVVdMfzhzs/r99h11EOQJEm6izRx1tovybOAvavqJe3zFwCPqqpXdNU7DDisfboTcMEsu9oC6O8hG6PpY1j9LJY+htXPYuljWP24LQuvj2H147YsvD6G1c9i6WNY/cylj/tV1dDOdN5LDJfkVODtVfWt9vnZwOuqavkk7c0n1hv3936h9rNY+hhWP27LwutjWP0slj6G1Y/bsvD6GFY/474tk8Z6i+kIwsnOjnyX7GdVfQT4yJw7SZZX1UB3/Q6jj2H1s1j6GFY/i6WPYfXjtiy8PobVj9uy8PoYVj+LpY9h9TOsbZmnXmK4nuI8mF+s53u/MPtZLH0Mqx+3ZeH1Max+Fksfw+rHbVl4fQyrH7dlcoO9tNlwrQS263i+LXD5iMYiSZKk3vQSwxnnSZIkDdBiShB+D9gxyQ5J1gcOAk4Z8ZgkSZI0vV5iuFOAg9PYHfjt2nj+QUmSpIVq0UwxrqrbkrwCOBNYF/h4VZ0/gK7mPD15gfUxrH4WSx/D6mex9DGsftyWhdfHsPpxWxZeH8PqZ7H0Max+hrUtczZVDJfkpe3yDwGnAfsAK4DfAy8c0HB87xdmP4ulj2H147YsvD6G1c9i6WNY/bgtC6+PYfXjtkxi0VykRJIkSZIkSdLsLaYpxpIkSZIkSZJmyQShJEmSJEmSNMZMEPYoyd5JLkiyIsnhA+rj40muSvKTQbTf9rFdkq8m+VmS85O8egB93C3Jd5P8qO3jLf3uo6u/dZP8X5JTB9T+xUnOS/LDJMsH0Ufbz+ZJTkzy8/b9eXSf29+p3YaJ2/VJXtPPPtp+/rZ933+S5DNJ7tbvPtp+Xt32cX6/tmOy72CSeyY5K8kv2/t7DKifA9ttuSPJvC9TP0Uf72w/Xz9O8oUkmw+on7e1ffwwyZeS3KfffXQs+/sklWSLfveR5Igkl3V8Z/aZTx9T9dOWv7L9jTk/yVH97iPJZzu24+IkPxxAHw9N8p2Jv5VJdptPH9P085Ak57R/l/87yWbz7GPS38V+fven6aPf3/up+un7d38xirHebPoYWqyXAcd5bR8Dj/Uy4Div7WPRxHoZQJzXtjvwWG+KPvr6936afvr6936KPvoa503VT8eytSbWm2o70sc4b6p+Yqw3XR+LItabpo/+fe+rytsMN5oTZv8KuD+wPvAjYOcB9LMH8HDgJwPclq2Bh7ePNwV+0e9tAQJs0j5eDzgX2H2A2/R3wKeBUwfU/sXAFoMaf0c/xwIvaR+vD2w+wL7WBVYB9+tzu9sAFwEbts9PAA4dwPh3AX4CbERzsaUvAzv2od27fAeBo4DD28eHA+8YUD9/BuwEfA3YdUB9PAVY0j5+xwC3ZbOOx68CPtTvPtry7WguavDr+X5Hp9iOI4C/78dndoZ+/l/7Gd6gfb7lIF6vjuXvAt40gO34EvDU9vE+wNcG9Hp9D3h8+/hFwNvm2cekv4v9/O5P00e/v/dT9dP37/5iu2GsN9s+hhbrMeA4r+3j4vn+jvTQx9DivLaPtTbWY0BxXtv2wGO9Kfro69/7afrp69/7Kfroa5w3VT9t+VoV603RR1/jvOler47lxnpr9rEoYr1p+ujb994jCHuzG7Ciqi6sqluA44H9+91JVX0DuKbf7Xb1cUVV/aB9fAPwM5of+n72UVV1Y/t0vfY2kKvhJNkWeBrw0UG0PyztXpE9gI8BVNUtVXXdALvcE/hVVf16AG0vATZMsoQmsLt8AH38GfCdqvp9Vd0GfB14+nwbneI7uD9NUE97f8Ag+qmqn1XVBfNte4Y+vtS+XgDfAbYdUD/XdzzdmHl+/6f523g0sGy+7c/QR19N0c/LgLdX1c1tnasG0AcASQI8G/jMAPooYGIP793pw3d/in52Ar7RPj4LeOY8+5jqd7Fv3/2p+hjA936qfvr+3V+EjPVm18dQYj3jvHlZm2O9gcR5MJxYbxhx3jT99PXv/TDivKn6aa1Vsd4w4rxp+gGM9aboY1HEesOI80wQ9mYb4NKO5yvpc6A1Ckm2Bx5Gs9e3322v2x7WfBVwVlX1vY/We2h+NO4YUPvQ/CH8UpLvJzlsQH3cH1gN/FeaaTQfTbLxgPoCOIh5/mhMpqouA/4NuAS4AvhtVX2p3/3Q7FXeI8m9kmxEswdruwH0A3DvqroCmj/KwJYD6mfYXgScPqjGkxyZ5FLgecCbBtD+fsBlVfWjfrfd5RXt4fofn++Uo2k8EPiLJOcm+XqSRw6oH4C/AK6sql8OoO3XAO9s3/d/A14/gD6g+f7v1z4+kD5+97t+Fwfy3R/kb2+P/Qz0u78WM9abfdvDiPXew+DjPBh8rDfsOA/W7lhvmHEeGOvN2qDjvLaPxRLrDTPOA2O9aS2WWG9QcZ4Jwt5kkrKBHBE3LEk2AT4PvKZrL1BfVNXtVfVQmuz1bkl26XcfSfYFrqqq7/e77S6PraqHA08FXp5kjwH0sYTm0OoPVtXDgN/RHObcd0nWp/mD+7kBtH0Pmj0xOwD3ATZO8vx+91NVP6M5fPos4AyaqWC3TbuS/ijJG2ler08Nqo+qemNVbdf28Yp+tt3+s/BGBhSQdvgg8CfAQ2n+CXrXgPpZAtwD2B34B+CEdu/vIDyHAfzD2HoZ8Lft+/63tEfKDMCLaP4Wf59mesUt/Wh00L+Lw+pjun6G8d1fixnrzdKgY70hxnkw+FhvaHEerP2xnnHe/A367/0g4zxYdLHeMOM8MNab0mKJ9QYZ55kg7M1K1sxab8tgpk0ORZL1aD5Qn6qqkwbZVzt94mvA3gNo/rHAfkkuppkK9MQkx/W7k6q6vL2/CvgCzTSkflsJrOzY+34iTSA5CE8FflBVVw6g7ScBF1XV6qq6FTgJeMwA+qGqPlZVD6+qPWgOSx/EXjKAK5NsDdDez3tawCglOQTYF3heVQ3jn99PM89pAZP4E5p/TH7Ufv+3BX6QZKt+dlJVV7b/AN8B/CeD+e5D8/0/qZ2y912aI2XmdSLuybRTwZ4BfLbfbbcOofnOQ/NP6UBer6r6eVU9paoeQRMA/2q+bU7xu9jX7/6wfnun6mcE3/21jbHeHA0w1htKnAdDifWGGefBIoj1hhjngbHefAwizoPFFesNJc4DY73pLJZYb9BxngnC3nwP2DHJDu0euYOAU0Y8pjlp91Z8DPhZVb17QH0sTXvlnCQb0gQSP+93P1X1+qratqq2p3lPvlJVfd2DmWTjJJtOPKY5AWjfrzxYVauAS5Ps1BbtCfy03/20BrlX6RJg9yQbtZ+1PWnOjdB3SbZs7+9L80M4qG06hebHkPb+5AH1M3BJ9gZeB+xXVb8fYD87djzdjz5//6vqvKrasqq2b7//K2lO2Luqn/1MBAytpzOA737ri8AT2z4fSHPy+t8MoJ8nAT+vqpUDaBuaZMrj28dPZED/zHV899cB/hH40Dzbm+p3sW/f/WH89k7Xz7C++2s5Y73Z9THwWG8YcR4MJ9YbcpwHiyDWG2KcB8Z6s+1joHEeLLpY74sMJ84DY72p2lsUsd5Q4rya51VnxuVGc+6LX9Bkr984oD4+Q3No8600fwRfPIA+HkczZebHwA/b2z597uPBwP+1ffyEeV5Bqcc+n8AArm5Hc86YH7W38wf13rd9PRRY3r5uXwTuMYA+NgKuBu4+wO14C02g8BPgk7RX7BpAP9+kCa5/BOzZpzbv8h0E7gWcTfMDeDZwzwH18/T28c3AlcCZA+hjBc05tia++/246txk/Xy+ff9/DPw3zclz+9pH1/KLmf+V7Sbbjk8C57XbcQqw9YBer/WB49rX7AfAEwfxegHHAC+d7zZMsx2PA77ffifPBR4xoH5eTfN7/Avg7UDm2cekv4v9/O5P00e/v/dT9dP37/5ivGGsN5s+hhrrMaA4r217KLEeQ4jz2n4WRazHAOK8tt2Bx3pT9NHXv/fT9NPXv/dT9NHXOG+qfrqWX8xaEOtN0Udf47zpXi+M9abqY1HEetP00bfvfdqOJEmSJEmSJI0hpxhLkiRJkiRJY8wEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSRJkiRJkjTGTBBKkiRJkiRJY8wEoSSNkSRfS/KSUY9DkiRJ/WesJ2muTBBKWpCSVJIHdJUdkeS4IfR9TJJbktyY5JokZyX503m0t327PUumqXNEklvbPq9L8u0kj55rn5IkSQuZsZ6xnqSFxQShpLE2TSB3VFVtAmwLXAUcM4ThfLbtcynwLeCkJJlNA9MFppIkSePGWE+SemOCUNJaKckWSU5t98Bek+SbSdZpl90nyeeTrE5yUZJXdax3RJITkxyX5Hrg0On6qarfA58GdmnXf2+SS5Ncn+T7Sf6io+3dkixvl12Z5N3tom+099e1e42n3VtcVbcCxwJbAffqniqS5NAk3+p4XklenuSXwC/bsv2T/LAdy6+S7N3Rxf2S/G+SG5J8KckWHW19LsmqJL9N8o0kD+pYtk+Sn7brXZbk7zuW7dv2N7FH/MEdy17X1r8hyQVJ9pxu+yVJkoz1jPUkDZcJQklrq9cCK2n2wN4beANQbeD438CPgG2APYHXJNmrY939gROBzYFPTddJkk2A5wH/1xZ9D3gocE+aYPJzSe7WLnsv8N6q2gz4E+CEtnyP9n7zqtqkqs6Zoc8NaILZlVX1m+nqdjgAeBSwc5LdgE8A/0CzjXsAF3fUfS7wQmBLYH3g7zuWnQ7s2C77AWu+Ph8D/qaqNqUJor/SjvfhwMeBvwHuBXwYOCXJBkl2Al4BPLJdb6+usUiSJE3GWG9NB2CsJ2mATBBKWlvdCmwN3K+qbq2qb1ZVAY8EllbVW6vqlqq6EPhP4KCOdc+pqi9W1R1V9Ycp2v/7JNcBK4BNaPc+V9VxVXV1Vd1WVe8CNgB26hjTA5JsUVU3VtV3ZrlNz277vBR4BE0g2Kt/rapr2u15MfDxqjqr3cbLqurnHXX/q6p+0dY9gSYIpt2+j1fVDVV1M3AE8JAkd+/Yvp2TbFZV11bVD9ryvwY+XFXnVtXtVXUscDOwO3A7zWu0c5L1quriqvrVbF4USZI0loz11mSsJ2mgTBBKWqhuB9brKluPJnABeCdNQPelJBcmObwtvx9wn3b6w3VtEPYGmj3PEy7tof9/q6rNq2qrqtpvItBJ8tokP2unZVwH3B2YmLbxYuCBwM+TfC/JvrPaYjih7XPLqnpiVX1/Fut2btN2wHSB2aqOx7+nCYpJsm6St7fTVK7nzr2/E9v3TGAf4NdJvt4xfeZ+wGu7XvPtgPtU1QrgNTQB6FVJjk9yn1lslyRJWpyM9Yz1JC0gJgglLVSXANt3le0A/Bqg3fP52qq6P/CXwN+15zu5FLioDb4mbptW1T4d7dRcBtSeg+Z1wLOBe1TV5sBvgbRj+mVVPYdmysY7gBOTbDzX/jr8Dtio4/lWk9Tp7ONSmmkvs/Vcmik5T6IJhrdvyye273tVtT/N9n2RO6fVXAoc2fWab1RVn2nX+3RVPY4muCya10aSJI03Y707GetJGjkThJIWqs8C/5hk2yTrJHkSTXB4IvzxRMkPSBLgepq90LcD3wWub0+WvGG7p3SXJI/sw5g2BW4DVgNLkrwJ2GxiYZLnJ1laVXcA17XFt7f17wDuP8d+fwg8I8lGSR5As/d6Oh8DXphkz/a12ybJn/bQz6Y000WupglS/2ViQZL1kzwvyd2rObH2xGsOzbSelyZ5VBobJ3lakk2T7JTkie25dm4C/tCxniRJGl/Genf6IcZ6kkbMBKGkheqtwLeBbwHXAkcBz6uqn7TLdwS+DNwInAN8oKq+VlW30wSXDwUuAn4DfJRmL+l8nUlzYudf0Ozdvok1p3vsDZyf5Eaak1gfVFU3VXN1vCOB/22nZew+y36PBm4BrqS54t20J9uuqu/SnJj6aJq93l+n2aM7k0/QbNdlwE+B7vPqvAC4uJ2S8lLg+W1/y2nOTfN+mvdqBXdeMXAD4O0078Mqmj3Sb+hhLJIkaXEz1ruTsZ6kkUtznldJkiRJkiRJ48gjCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmMmCCVJkiRJkqQxZoJQkiRJkiRJGmP/P4ao4xXUzkVLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18, 6))\n",
    "sns.countplot(x='user_past_purchases', data=full_data, ax=ax[0])\n",
    "ax[0].set_xlabel('User Past Purchases', fontsize=12)\n",
    "ax[0].set_ylabel('Count', fontsize=12)\n",
    "ax[0].set_title('Count Plot of User Past Purchases', fontsize=16)\n",
    "\n",
    "sns.barplot(x='user_past_purchases', y=full_data['link_click'].astype('float'), data=full_data, ax=ax[1])\n",
    "ax[1].set_xlabel('User Past Purchases', fontsize=12)\n",
    "ax[1].set_ylabel('Click Through Rate', fontsize=12)\n",
    "ax[1].set_title('Click Through Rate vs. User Past Purchases', fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4dfa5de",
   "metadata": {},
   "source": [
    "#### Base on the above analysis, company can choose to make modification on the following areas:\n",
    "\n",
    "#### 1. send short emails with personalized contents\n",
    "\n",
    "#### 2. send them during the first half (Monday - Wednesday) and late of the night (10PM -12AM)\n",
    "\n",
    "#### 3. the company can also conduct A/B testing to test if the situation is true as the above analysis: send the old version emails to all users in control group, then send the modified version in test group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f75fc0e6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}