US Baby Names Presentation Fixed.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# One Hundred Years of US Baby Names\n",
    "\n",
    "## Bootcamp Project\n",
    "### June 30, 2020\n",
    "\n",
    "### Group\n",
    "Dhara Bhansali\n",
    "Sarah Grant\n",
    "Keke Li\n",
    "Matt Debnar\n",
    "\n",
    "### Overview\n",
    "Analysis of baby names in the US from 1910 thru 2014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies\n",
    "#from config import (census_key, gkey)\n",
    "import gmaps\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "import time\n",
    "#from us import states\n",
    "from scipy.stats import linregress\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Id</th>\n",
       "      <th>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>State</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Mary</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Annie</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Anna</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Margaret</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Helen</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Id      Name  Year Gender State Count\n",
       "0  1      Mary  1910      F    AK    14\n",
       "1  2     Annie  1910      F    AK    12\n",
       "2  3      Anna  1910      F    AK    10\n",
       "3  4  Margaret  1910      F    AK     8\n",
       "4  5     Helen  1910      F    AK     7"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#data source: https://www.kaggle.com/kaggle/us-baby-names\n",
    "#import baby name data\n",
    "baby_name_original = pd.read_csv(\n",
    "    \"Data/StateNames.csv\", dtype=\"object\", encoding=\"utf-8\")\n",
    "#display result\n",
    "baby_name_original.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#clean up column formats for Count (float), Year (int), convert year to date in new column date_conv (datetime)\n",
    "baby_name_original[\"Count\"] = baby_name_original.Count.astype(float)\n",
    "baby_name_original[\"Year\"] = baby_name_original[\"Year\"].astype(int)\n",
    "#alternative: change year into datetime if desired as new column date_conv\n",
    "#baby_name_original['date_conv'] = pd.to_datetime(baby_name_original.Year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id        0\n",
       "Name      0\n",
       "Year      0\n",
       "Gender    0\n",
       "State     0\n",
       "Count     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#look for null values\n",
    "baby_name_original.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>State</th>\n",
       "      <th>Count</th>\n",
       "      <th>Decade</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mary</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Annie</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Anna</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Helen</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647422</th>\n",
       "      <td>Seth</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647423</th>\n",
       "      <td>Spencer</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647424</th>\n",
       "      <td>Tyce</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647425</th>\n",
       "      <td>Victor</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647426</th>\n",
       "      <td>Waylon</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5647426 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name  Year Gender State  Count  Decade\n",
       "Id                                                 \n",
       "1            Mary  1910      F    AK   14.0    1910\n",
       "2           Annie  1910      F    AK   12.0    1910\n",
       "3            Anna  1910      F    AK   10.0    1910\n",
       "4        Margaret  1910      F    AK    8.0    1910\n",
       "5           Helen  1910      F    AK    7.0    1910\n",
       "...           ...   ...    ...   ...    ...     ...\n",
       "5647422      Seth  2014      M    WY    5.0    2010\n",
       "5647423   Spencer  2014      M    WY    5.0    2010\n",
       "5647424      Tyce  2014      M    WY    5.0    2010\n",
       "5647425    Victor  2014      M    WY    5.0    2010\n",
       "5647426    Waylon  2014      M    WY    5.0    2010\n",
       "\n",
       "[5647426 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#add a new column for Decade\n",
    "baby_name_new = baby_name_original.copy()\n",
    "baby_name_new.set_index('Id', inplace=True)\n",
    "#baby_name_new[\"Year\"] = baby_name_new[\"Year\"].astype(int)\n",
    "baby_name_new['Decade'] = ((baby_name_new['Year']//10)*10)\n",
    "#baby_name_new = baby_name_new.reset_index(drop=True)\n",
    "baby_name_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define Region by State values\n",
    "Northeast = ('CT', 'ME', 'MA', 'NH', 'RI', 'VT', 'NJ', 'NY', 'PA')\n",
    "Midwest = ('IL', 'IN', 'MI', 'OH', 'WI', 'IA', 'KS', 'MN', 'MO', 'NE', 'ND', 'SD')\n",
    "South = ('DE', 'FL', 'GA', 'MD', 'NC', 'SC', 'VA', 'DC', 'WV', 'AL', 'KY', 'MS', 'TN', 'AR', 'LA', 'AR', 'OK', 'TX')\n",
    "West = ('AZ', 'CO', 'ID', 'MT', 'NV', 'NM', 'UT', 'WY', 'AK', 'CA', 'HI', 'OR', 'WA')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name      30274\n",
       "Year        105\n",
       "Gender        2\n",
       "State        51\n",
       "Count      4944\n",
       "Decade       11\n",
       "Region        4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#add column Region and assign based on region-state values\n",
    "baby_name_new[\"Region\"] = np.where(baby_name_new[\"State\"].isin(Northeast), \"Northeast\", \n",
    "         (np.where(baby_name_new[\"State\"].isin(South), \"South\",\n",
    "            (np.where(baby_name_new[\"State\"].isin(West), \"West\",\n",
    "                (np.where(baby_name_new[\"State\"].isin(Midwest), \"Midwest\", \"Unknown\")))))))\n",
    "\n",
    "#confirm 4 regions across all data\n",
    "baby_name_new.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>State</th>\n",
       "      <th>Count</th>\n",
       "      <th>Decade</th>\n",
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       "      <th>Id</th>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Name, Year, Gender, State, Count, Decade, Region]\n",
       "Index: []"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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   ],
   "source": [
    "#find any Unkown regions to bug fix Region States\n",
    "baby_unknown = baby_name_new.loc[baby_name_new[\"Region\"] == \"Unknown\", :]\n",
    "baby_unknown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#summarize names per year\n",
    "years = list(range(1910, 2011, 10))\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.plot(baby_name_original.groupby(['Year']).agg({'Count':np.sum}))\n",
    "plt.title(\"Names Per Year\")\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Names')\n",
    "plt.xticks(years)\n",
    "plt.grid()\n",
    "\n",
    "plt.savefig(f'Output/Names Per Year.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: the baby boom is real! Count of names jumped at the end of WWII in 1945 and peaked just before 1960"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Between 1910 and 2014, the number of names increased over time.\n",
    "\n",
    "The first sharp incline in baby names occurs in the mid-1940s (from 250,000 to just under 350,000), which correlates to WWII ending in 1945.\n",
    "\n",
    "These births will mark the beginning of the largest generation in the U.S. (until the millennials), the Baby Boomers. \n",
    "\n",
    "The sharp incline continues and peaks in the late-fifties and early sixties (circa 1957 - 1962), the period yielding the greatest volume of names to date -- these names signify the end of the Baby Boomers.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#optional names by Decade\n",
    "years = list(range(1910, 2011, 10))\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.plot(baby_name_new.groupby(['Decade']).agg({'Count':np.sum}))\n",
    "plt.title(\"Names Per Decade\")\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Names')\n",
    "plt.xticks(years)\n",
    "plt.grid()\n",
    "\n",
    "plt.savefig(f'Output/Names Per Decade.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: baby boom confirmed in 1950s then slight bounce back until 2000s (note: 2010 is a partial decade, only half thru 2014)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "GenderNameGB = baby_name_new.groupby(['Year', 'Gender'])['Count'].sum()\n",
    "GenderNameGBDF = pd.DataFrame(GenderNameGB)\n",
    "GenderNameGBDF\n",
    "GenderNameGBDF.rename(index={0: \"Year\", 1: \"Gender\", 2: \"Count\"})\n",
    "GenderNameGBDFX = GenderNameGBDF.unstack()\n",
    "GenderNameGBDFX.columns = GenderNameGBDFX.columns.droplevel()\n",
    "GenderNameGBDFX\n",
    "multi_plot = GenderNameGBDFX.plot(kind=\"line\", figsize=(15, 10))\n",
    "multi_plot.set_title(\"Names Per Year Per Gender\")\n",
    "multi_plot.set_xlabel('Year')\n",
    "multi_plot.set_ylabel('Names')\n",
    "multi_plot.legend(ncol=2)\n",
    "years = list(range(1910, 2021, 10))\n",
    "plt.xticks(years)\n",
    "plt.grid()\n",
    "plt.savefig(f'Output/Names Per Gender.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: girls names outpaced boys until 1930; after 1930 the number of boys' names outpaced girls' consistently thru 2014"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The trends for male and female baby names are parallel to one another, but in the latter half of the century, they are not equal. \n",
    "\n",
    "There are significantly more male baby names beginning in the early 1970s -- a trend that remains the same through 2014. \n",
    "\n",
    "One reason for the increase in male baby names is the rising trend in unisex names, many of which are considered “male.” \n",
    "\n",
    "For example, the name “Madison” was historically considered a male name, but after the 1984 movie “Splash” (in which the female protagonist names herself Madison after the New York City street), there was a marked rise in U.S. females named Madison. “Madison” was ranked second for girls in the United States by 2001. This rise from obscurity to prominence in only 18 years represents an unprecedented 550,000 percent increase in usage.\n",
    "\n",
    "The name “Taylor” is another example of this trend of a traditionally male name that has been co-opted as feminine in modern times.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "babyRegion = baby_name_new.groupby(\"Region\")\n",
    "\n",
    "Region = babyRegion.count().index\n",
    "RegionNames = babyRegion['Count'].sum()\n",
    "\n",
    "regionSummary = pd.DataFrame({\"Region\": Region, \"Names\": RegionNames,\n",
    "                             })\n",
    "regionSummary.set_index('Region', inplace=True)\n",
    "\n",
    "multi_plot = regionSummary.plot(kind=\"bar\", figsize=(15, 10))\n",
    "plt.title(f\"Baby Names Per Region\")\n",
    "plt.grid()\n",
    "plt.xlabel(\"Region\")\n",
    "plt.ylabel(\"Baby Names (Hundred Millions)\")\n",
    "plt.savefig(f'Output/Names Per Region.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#names per region over time\n",
    "RegionNameGB = baby_name_new.groupby(['Year', 'Region'])['Count'].sum()\n",
    "RegionNameGBDF = pd.DataFrame(RegionNameGB)\n",
    "RegionNameGBDF\n",
    "RegionNameGBDF.rename(index={0: \"Year\", 1: \"Region\", 2: \"Count\"})\n",
    "RegionNameGBDFX = RegionNameGBDF.unstack()\n",
    "RegionNameGBDFX.columns = RegionNameGBDFX.columns.droplevel()\n",
    "RegionNameGBDFX\n",
    "multi_plot = RegionNameGBDFX.plot(kind=\"line\", figsize=(15, 10))\n",
    "multi_plot.set_title(\"Names Per Year Per Region\")\n",
    "multi_plot.set_xlabel('Year')\n",
    "multi_plot.set_ylabel('Names')\n",
    "multi_plot.legend(ncol=2)\n",
    "years = list(range(1910, 2021, 10))\n",
    "plt.xticks(years)\n",
    "plt.grid()\n",
    "plt.savefig(f'Output/Names Per Year Per Region.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: the South consitently registers the most names.  The Midwest and and Northeast counts peaked just before 1960 then fell off.  The West gained in name counts starting in 1940 then increased again in 1975 to gain second place"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Name</th>\n",
       "      <th>Popularity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>James</th>\n",
       "      <td>James</td>\n",
       "      <td>4957166.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John</th>\n",
       "      <td>John</td>\n",
       "      <td>4845414.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robert</th>\n",
       "      <td>Robert</td>\n",
       "      <td>4725713.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michael</th>\n",
       "      <td>Michael</td>\n",
       "      <td>4312975.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William</th>\n",
       "      <td>William</td>\n",
       "      <td>3839236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mary</th>\n",
       "      <td>Mary</td>\n",
       "      <td>3740495.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>David</th>\n",
       "      <td>David</td>\n",
       "      <td>3562278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard</th>\n",
       "      <td>Richard</td>\n",
       "      <td>2534949.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Joseph</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>2485220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charles</th>\n",
       "      <td>Charles</td>\n",
       "      <td>2252146.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Name  Popularity\n",
       "Name                        \n",
       "James      James   4957166.0\n",
       "John        John   4845414.0\n",
       "Robert    Robert   4725713.0\n",
       "Michael  Michael   4312975.0\n",
       "William  William   3839236.0\n",
       "Mary        Mary   3740495.0\n",
       "David      David   3562278.0\n",
       "Richard  Richard   2534949.0\n",
       "Joseph    Joseph   2485220.0\n",
       "Charles  Charles   2252146.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#group by Name to find popular names\n",
    "BabyNameGB = baby_name_original.groupby(\"Name\")\n",
    "BabyName = BabyNameGB.count().index\n",
    "NameCount = BabyNameGB[\"Count\"].sum()\n",
    "\n",
    "TopNameGB = pd.DataFrame({\"Name\": BabyName, \"Popularity\": NameCount\n",
    "                             })\n",
    "#sort names by popularity\n",
    "TopName = TopNameGB.sort_values(by=['Popularity'], ascending=False)\n",
    "TopName.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: most of the top names are Male. Given more Female names registered than Male suggests more variability in Female names than Male"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The names used by each gender (female has more diverse name selections/options than male)\n",
    "name= baby_name_original.loc[:,['Name','Gender','Count']]\n",
    "name\n",
    "\n",
    "gendername= name.groupby(['Gender']).nunique()['Name']\n",
    "gendername\n",
    "\n",
    "Male= 13139\n",
    "Female=20031\n",
    "\n",
    "labels = [\"Male\", \"Female\"]\n",
    "\n",
    "# The values of each section of the pie chart\n",
    "sizes = [13139, 20031]\n",
    "\n",
    "# The colors of each section of the pie chart\n",
    "colors = [\"pink\",\"lightskyblue\"]\n",
    "\n",
    "explode = (0,0.1)\n",
    "\n",
    "plt.pie(sizes, labels=labels,explode=explode, colors=colors, shadow=True, startangle=140,autopct=\"%1.1f%%\")\n",
    "plt.title(f\"Female vs Male Unique Baby Names Ratio from 1910 - 2014\")\n",
    "plt.axis(\"equal\")\n",
    "plt.show()\n",
    "# export as png\n",
    "\n",
    "plt.savefig(f'Output/Female vs Male Unique Baby Names Ratio from 1910 - 2014.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Proof! Female names have more variety than Male names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30274"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group the dataset by name\n",
    "names = baby_name_original.groupby(\"Name\")\n",
    "\n",
    "# Different names in the database\n",
    "baby_name_original.Name.nunique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name\n",
       "James       4957166.0\n",
       "John        4845414.0\n",
       "Robert      4725713.0\n",
       "Michael     4312975.0\n",
       "William     3839236.0\n",
       "              ...    \n",
       "Makua             5.0\n",
       "Makinlee          5.0\n",
       "Makenlie          5.0\n",
       "Makenlee          5.0\n",
       "Zyshonne          5.0\n",
       "Name: Count, Length: 30274, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Name with the most occurances\n",
    "most_occurances = names.Count.sum().sort_values(ascending=False)\n",
    "most_occurances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4722"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Least occurances\n",
    "least_occurances = (names.Count.sum()== 5).sum()\n",
    "least_occurances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>James</th>\n",
       "      <td>4938965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John</th>\n",
       "      <td>4829733.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robert</th>\n",
       "      <td>4710600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michael</th>\n",
       "      <td>4295779.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William</th>\n",
       "      <td>3829026.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>David</th>\n",
       "      <td>3554102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard</th>\n",
       "      <td>2529952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Joseph</th>\n",
       "      <td>2479602.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charles</th>\n",
       "      <td>2244617.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas</th>\n",
       "      <td>2216356.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Count\n",
       "Name              \n",
       "James    4938965.0\n",
       "John     4829733.0\n",
       "Robert   4710600.0\n",
       "Michael  4295779.0\n",
       "William  3829026.0\n",
       "David    3554102.0\n",
       "Richard  2529952.0\n",
       "Joseph   2479602.0\n",
       "Charles  2244617.0\n",
       "Thomas   2216356.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top 10 Males Name\n",
    "baby_name_male = baby_name_original[baby_name_original[\"Gender\"] == \"M\"]\n",
    "baby_name_male = baby_name_male[[\"Name\", \"Count\"]]\n",
    "baby_name_male = baby_name_male.groupby(\"Name\")\n",
    "baby_name_male = baby_name_male.sum()\n",
    "baby_name_male = baby_name_male.sort_values(\"Count\", ascending=False)\n",
    "baby_name_male.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mary</th>\n",
       "      <td>3730856.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Patricia</th>\n",
       "      <td>1567779.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elizabeth</th>\n",
       "      <td>1500462.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jennifer</th>\n",
       "      <td>1461813.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Linda</th>\n",
       "      <td>1446300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barbara</th>\n",
       "      <td>1422972.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Margaret</th>\n",
       "      <td>1121985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Susan</th>\n",
       "      <td>1108255.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dorothy</th>\n",
       "      <td>1051603.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jessica</th>\n",
       "      <td>1038060.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Count\n",
       "Name                \n",
       "Mary       3730856.0\n",
       "Patricia   1567779.0\n",
       "Elizabeth  1500462.0\n",
       "Jennifer   1461813.0\n",
       "Linda      1446300.0\n",
       "Barbara    1422972.0\n",
       "Margaret   1121985.0\n",
       "Susan      1108255.0\n",
       "Dorothy    1051603.0\n",
       "Jessica    1038060.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Top 10 Female Names\n",
    "\n",
    "baby_name_female = baby_name_original[baby_name_original[\"Gender\"] == \"F\"]\n",
    "baby_name_female= baby_name_female[[\"Name\", \"Count\"]]\n",
    "baby_name_female = baby_name_female.groupby(\"Name\")\n",
    "baby_name_female = baby_name_female.sum()\n",
    "baby_name_female = baby_name_female.sort_values(\"Count\", ascending=False)\n",
    "baby_name_female.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: counts of top Female names are lower than top Male names, reinforcing lower variety in Male names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For creating tuples\n",
    "males = [(male,'M') for male in list(baby_name_male.head(8).index)]\n",
    "females = [(female,'F') for female in list(baby_name_female.head(8).index)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "most_popular = baby_name_original\n",
    "\n",
    "def plot(ax, name, gender):\n",
    "    data = most_popular.loc[(most_popular.Name==name)&(most_popular.Gender==gender)]\n",
    "    ax.bar(data.Year, data.Count, width = 1, alpha=0.6,\n",
    "           color = 'pink' if gender=='F' else 'lightblue')\n",
    "    ax.set_title(name)\n",
    "    return ax\n",
    "\n",
    "fig, ax = plt.subplots(4,4, figsize=(12,12), sharex=True)\n",
    "ax = ax.flatten()\n",
    "years = list(range(1910, 2021,20))\n",
    "plt.xticks(years)\n",
    "for a, (name, gender) in zip(ax, males+females):\n",
    "    plot(a, name, gender)\n",
    "fig.suptitle('Trends for the most popular names',fontsize='x-large');\n",
    "plt.savefig(\"Output/Popular_Names.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: most Boys names peak around 1960; Joseph and Michael remain popular. Most Girls names also peak in 1950 or 1960, Elizabeth and Jennifer remain popular"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "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>Id</th>\n",
       "      <th>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>State</th>\n",
       "      <th>Count</th>\n",
       "      <th>Name Length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Mary</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Annie</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Anna</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Margaret</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Helen</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647421</th>\n",
       "      <td>5647422</td>\n",
       "      <td>Seth</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647422</th>\n",
       "      <td>5647423</td>\n",
       "      <td>Spencer</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647423</th>\n",
       "      <td>5647424</td>\n",
       "      <td>Tyce</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647424</th>\n",
       "      <td>5647425</td>\n",
       "      <td>Victor</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647425</th>\n",
       "      <td>5647426</td>\n",
       "      <td>Waylon</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5647426 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Id      Name  Year Gender State  Count  Name Length\n",
       "0              1      Mary  1910      F    AK   14.0            4\n",
       "1              2     Annie  1910      F    AK   12.0            5\n",
       "2              3      Anna  1910      F    AK   10.0            4\n",
       "3              4  Margaret  1910      F    AK    8.0            8\n",
       "4              5     Helen  1910      F    AK    7.0            5\n",
       "...          ...       ...   ...    ...   ...    ...          ...\n",
       "5647421  5647422      Seth  2014      M    WY    5.0            4\n",
       "5647422  5647423   Spencer  2014      M    WY    5.0            7\n",
       "5647423  5647424      Tyce  2014      M    WY    5.0            4\n",
       "5647424  5647425    Victor  2014      M    WY    5.0            6\n",
       "5647425  5647426    Waylon  2014      M    WY    5.0            6\n",
       "\n",
       "[5647426 rows x 7 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_name_original[\"Name Length\"]= baby_name_original[\"Name\"].str.len()\n",
    "baby_name_original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(baby_name_original.groupby(['Year']).agg({'Name Length':np.mean}))\n",
    "years = list(range(1910, 2021,10))\n",
    "plt.xticks(years)\n",
    "plt.xlabel(\"Years\",fontsize=12,style='italic')\n",
    "plt.ylabel(\"Name Length\", fontsize=12,style='italic')\n",
    "plt.title(\"Average Length of Baby Names\",fontsize=12,fontweight='bold',style='normal')\n",
    "plt.savefig(\"Output/NameLength.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: Baby name length increases from 1960 thru 1990"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "both_df = baby_name_original.groupby(['Year','Gender'])['Name Length'].mean()\n",
    "both_df = both_df.unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "both_df.plot(kind = 'line')\n",
    "years = list(range(1910, 2021,10))\n",
    "plt.xticks(years)\n",
    "plt.xlabel(\"Years\",fontsize=12,style='italic')\n",
    "plt.ylabel(\"Name Length\",fontsize=12,style='italic')\n",
    "plt.title(\"Male vs Female Average Name Length\",fontsize=12,fontweight='bold',style='normal')\n",
    "#plt.savefig(\"../Output/Male vs Female Name Length.png\")\n",
    "plt.savefig(\"Output/Male vs Female Name Length.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: Looking at the pattern, average female  names length are longer than males names length with a peak at 1990."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The most popular Name Lengths:\n"
     ]
    },
    {
     "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>Name</th>\n",
       "      <th>Name Length</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17369</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>6</td>\n",
       "      <td>7194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17160</th>\n",
       "      <td>Lee</td>\n",
       "      <td>3</td>\n",
       "      <td>7125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12442</th>\n",
       "      <td>James</td>\n",
       "      <td>5</td>\n",
       "      <td>7037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13761</th>\n",
       "      <td>John</td>\n",
       "      <td>4</td>\n",
       "      <td>6865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23582</th>\n",
       "      <td>Robert</td>\n",
       "      <td>6</td>\n",
       "      <td>6820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13485</th>\n",
       "      <td>Jessie</td>\n",
       "      <td>6</td>\n",
       "      <td>6636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29049</th>\n",
       "      <td>William</td>\n",
       "      <td>7</td>\n",
       "      <td>6522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19955</th>\n",
       "      <td>Michael</td>\n",
       "      <td>7</td>\n",
       "      <td>6396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19273</th>\n",
       "      <td>Mary</td>\n",
       "      <td>4</td>\n",
       "      <td>6371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5174</th>\n",
       "      <td>Charles</td>\n",
       "      <td>7</td>\n",
       "      <td>6268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6800</th>\n",
       "      <td>David</td>\n",
       "      <td>5</td>\n",
       "      <td>6147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13982</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>6</td>\n",
       "      <td>5978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10117</th>\n",
       "      <td>George</td>\n",
       "      <td>6</td>\n",
       "      <td>5925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23450</th>\n",
       "      <td>Richard</td>\n",
       "      <td>7</td>\n",
       "      <td>5894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27463</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>6</td>\n",
       "      <td>5832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27348</th>\n",
       "      <td>Terry</td>\n",
       "      <td>5</td>\n",
       "      <td>5828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6528</th>\n",
       "      <td>Daniel</td>\n",
       "      <td>6</td>\n",
       "      <td>5704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12459</th>\n",
       "      <td>Jamie</td>\n",
       "      <td>5</td>\n",
       "      <td>5690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15345</th>\n",
       "      <td>Kelly</td>\n",
       "      <td>5</td>\n",
       "      <td>5659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13437</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>5</td>\n",
       "      <td>5644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Name Length  Count\n",
       "17369   Leslie            6   7194\n",
       "17160      Lee            3   7125\n",
       "12442    James            5   7037\n",
       "13761     John            4   6865\n",
       "23582   Robert            6   6820\n",
       "13485   Jessie            6   6636\n",
       "29049  William            7   6522\n",
       "19955  Michael            7   6396\n",
       "19273     Mary            4   6371\n",
       "5174   Charles            7   6268\n",
       "6800     David            5   6147\n",
       "13982   Joseph            6   5978\n",
       "10117   George            6   5925\n",
       "23450  Richard            7   5894\n",
       "27463   Thomas            6   5832\n",
       "27348    Terry            5   5828\n",
       "6528    Daniel            6   5704\n",
       "12459    Jamie            5   5690\n",
       "15345    Kelly            5   5659\n",
       "13437    Jerry            5   5644"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Most popular Names Length\n",
    "popular_name_length = baby_name_original.groupby(['Name','Name Length']).size().reset_index(name=\"Count\").sort_values(by=\"Count\",ascending=False).drop_duplicates(\"Name\", keep=\"first\")\n",
    "print(\"The most popular Name Lengths:\")\n",
    "popular_name_length.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>State</th>\n",
       "      <th>Count</th>\n",
       "      <th>Name Length</th>\n",
       "      <th>Decade</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mary</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>14.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Annie</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Anna</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Helen</td>\n",
       "      <td>1910</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647422</th>\n",
       "      <td>Seth</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647423</th>\n",
       "      <td>Spencer</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647424</th>\n",
       "      <td>Tyce</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647425</th>\n",
       "      <td>Victor</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5647426</th>\n",
       "      <td>Waylon</td>\n",
       "      <td>2014</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5647426 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name  Year Gender State  Count  Name Length  Decade\n",
       "Id                                                              \n",
       "1            Mary  1910      F    AK   14.0            4    1910\n",
       "2           Annie  1910      F    AK   12.0            5    1910\n",
       "3            Anna  1910      F    AK   10.0            4    1910\n",
       "4        Margaret  1910      F    AK    8.0            8    1910\n",
       "5           Helen  1910      F    AK    7.0            5    1910\n",
       "...           ...   ...    ...   ...    ...          ...     ...\n",
       "5647422      Seth  2014      M    WY    5.0            4    2010\n",
       "5647423   Spencer  2014      M    WY    5.0            7    2010\n",
       "5647424      Tyce  2014      M    WY    5.0            4    2010\n",
       "5647425    Victor  2014      M    WY    5.0            6    2010\n",
       "5647426    Waylon  2014      M    WY    5.0            6    2010\n",
       "\n",
       "[5647426 rows x 7 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_name_new = baby_name_original.copy()\n",
    "baby_name_new.set_index('Id', inplace=True)\n",
    "#baby_name_new[\"Year\"] = baby_name_new[\"Year\"].astype(int)\n",
    "baby_name_new['Decade'] = ((baby_name_new['Year']//10)*10)\n",
    "#baby_name_new = baby_name_new.reset_index(drop=True)\n",
    "baby_name_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group the dataset by decade\n",
    "decade = baby_name_new.groupby(\"Decade\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Average per decade is:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Decade\n",
       "1910    5.771876\n",
       "1920    5.815646\n",
       "1930    5.780017\n",
       "1940    5.788889\n",
       "1950    5.754392\n",
       "1960    5.748616\n",
       "1970    5.865854\n",
       "1980    5.963152\n",
       "1990    6.014065\n",
       "2000    5.954859\n",
       "2010    5.938594\n",
       "Name: Name Length, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Average per Decade \n",
    "average_decade = decade['Name Length'].mean()\n",
    "print(\"The Average per decade is:\")\n",
    "average_decade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Standard Deviation of decade on Name length is:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Decade\n",
       "1910    1.471722\n",
       "1920    1.470501\n",
       "1930    1.462167\n",
       "1940    1.465226\n",
       "1950    1.452642\n",
       "1960    1.439538\n",
       "1970    1.419871\n",
       "1980    1.420725\n",
       "1990    1.397427\n",
       "2000    1.364146\n",
       "2010    1.368459\n",
       "Name: Name Length, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Standard deviation of decade\n",
    "std_decade= decade['Name Length'].std()\n",
    "print(\"The Standard Deviation of decade on Name length is:\")\n",
    "std_decade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The average name length is:5.875933389831049\n"
     ]
    }
   ],
   "source": [
    "# The average Name Length for 100 years\n",
    "gender_name_length = baby_name_original[\"Name Length\"]\n",
    "average_name = np.average(gender_name_length)\n",
    "print(\" The average name length is:\" + str(average_name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum average value is 6.031970\n",
      "Year with maximum length is 1992\n"
     ]
    },
    {
     "data": {
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       "    }\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8496</th>\n",
       "      <td>Jessica</td>\n",
       "      <td>1990</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>112.0</td>\n",
       "      <td>7</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8497</th>\n",
       "      <td>Ashley</td>\n",
       "      <td>1990</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>96.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8498</th>\n",
       "      <td>Amanda</td>\n",
       "      <td>1990</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>92.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8499</th>\n",
       "      <td>Brittany</td>\n",
       "      <td>1990</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>75.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8500</th>\n",
       "      <td>Samantha</td>\n",
       "      <td>1990</td>\n",
       "      <td>F</td>\n",
       "      <td>AK</td>\n",
       "      <td>72.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5643677</th>\n",
       "      <td>Kaleb</td>\n",
       "      <td>1990</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5643678</th>\n",
       "      <td>Kasey</td>\n",
       "      <td>1990</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5643679</th>\n",
       "      <td>Keith</td>\n",
       "      <td>1990</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5643680</th>\n",
       "      <td>Mathew</td>\n",
       "      <td>1990</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5643681</th>\n",
       "      <td>Trent</td>\n",
       "      <td>1990</td>\n",
       "      <td>M</td>\n",
       "      <td>WY</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69141 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name  Year Gender State  Count  Name Length  Decade\n",
       "Id                                                              \n",
       "8496      Jessica  1990      F    AK  112.0            7    1990\n",
       "8497       Ashley  1990      F    AK   96.0            6    1990\n",
       "8498       Amanda  1990      F    AK   92.0            6    1990\n",
       "8499     Brittany  1990      F    AK   75.0            8    1990\n",
       "8500     Samantha  1990      F    AK   72.0            8    1990\n",
       "...           ...   ...    ...   ...    ...          ...     ...\n",
       "5643677     Kaleb  1990      M    WY    5.0            5    1990\n",
       "5643678     Kasey  1990      M    WY    5.0            5    1990\n",
       "5643679     Keith  1990      M    WY    5.0            5    1990\n",
       "5643680    Mathew  1990      M    WY    5.0            6    1990\n",
       "5643681     Trent  1990      M    WY    5.0            5    1990\n",
       "\n",
       "[69141 rows x 7 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_series = baby_name_new.groupby(['Year'])['Name Length'].mean()\n",
    "max_index = mean_series.argmax()\n",
    "print(\"Maximum average value is %f\"%mean_series.iloc[max_index])\n",
    "\n",
    "# Year with maximum average length\n",
    "print(\"Year with maximum length is %d\"%mean_series.index[max_index])\n",
    "\n",
    "#Top ten values in 1990\n",
    "baby_name_new[baby_name_new['Year'] == 1990]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Longest Name Length for year 1990 :\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Name Length</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>470123</th>\n",
       "      <td>Mariadelcarmen</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>644729</th>\n",
       "      <td>Michaelanthony</td>\n",
       "      <td>14</td>\n",
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       "    <tr>\n",
       "      <th>644768</th>\n",
       "      <td>Antoniodejesus</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470124</th>\n",
       "      <td>Mariaguadalupe</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5024084</th>\n",
       "      <td>Michaelangelo</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472164</th>\n",
       "      <td>Maryelizabeth</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3822039</th>\n",
       "      <td>Michaelangelo</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472149</th>\n",
       "      <td>Mariacristina</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1701829</th>\n",
       "      <td>Michaelangelo</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>644235</th>\n",
       "      <td>Michaelangelo</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Name  Name Length\n",
       "Id                                  \n",
       "470123   Mariadelcarmen           14\n",
       "644729   Michaelanthony           14\n",
       "644768   Antoniodejesus           14\n",
       "470124   Mariaguadalupe           14\n",
       "5024084   Michaelangelo           13\n",
       "472164    Maryelizabeth           13\n",
       "3822039   Michaelangelo           13\n",
       "472149    Mariacristina           13\n",
       "1701829   Michaelangelo           13\n",
       "644235    Michaelangelo           13"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The Longest Name Length for year 1990 :\")\n",
    "baby_name_new[baby_name_new['Year'] == 1990].sort_values('Name Length',ascending = False).head(10)[['Name','Name Length']]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#The progression of numbers of unique names in each year\n",
    "\n",
    "\n",
    "year= baby_name_original.loc[:,['Name','Year','Gender']]\n",
    "year\n",
    "\n",
    "# getting female list of unique name by each year\n",
    "\n",
    "genderf= year.loc[year['Gender'] == 'F']\n",
    "genderf\n",
    "\n",
    "genderfemale= genderf.groupby(['Year','Gender']).nunique()['Name']\n",
    "\n",
    "\n",
    "genderfemale= pd.DataFrame(genderfemale)\n",
    "genderfemale\n",
    "\n",
    "#getting male list of unique name by each year\n",
    "\n",
    "genderm= year.loc[year['Gender'] == 'M']\n",
    "genderm\n",
    "\n",
    "gendermale= genderm.groupby(['Year','Gender']).nunique()['Name']\n",
    "\n",
    "gendermale= pd.DataFrame(gendermale)\n",
    "gendermale\n",
    "\n",
    "\n",
    "final=pd.merge(genderfemale, gendermale, how='outer', on=['Year','Gender','Name'])\n",
    "final\n",
    "\n",
    "final.rename(index={0: \"Year\", 1: \"Gender\", 2: \"Name\"})\n",
    "df = final.unstack()\n",
    "df.columns =df.columns.droplevel()\n",
    "df\n",
    "\n",
    "multi_plot = df.plot(kind=\"line\", figsize=(15, 10))\n",
    "multi_plot.set_title(\"The Unique Counts of Names Progession Over The Century per Gender\")\n",
    "multi_plot.set_xlabel(\"Year\")\n",
    "\n",
    "multi_plot.set_ylabel(\"Unique Counts of Names\")\n",
    "multi_plot.legend(ncol=2)\n",
    "\n",
    "\n",
    "years = list(range(1910, 2021, 10))\n",
    "\n",
    "#plt.set_xticks(years)\n",
    "plt.grid()\n",
    "\n",
    "\n",
    "plt.savefig(f'Output/The Unique Counts of Names Progession Over The Century per Gender.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uIcdxnCbHDYHjOE6T44bAcZyGo9Fim11JZ66NGwLHcRqKPn36MH/+/E4bgxa1XyE3K60RMTPmz59Pnz59KtrPg8WO4zQUgwcPZu7cucybN69T+/eInzSzFryyWnLVC3369GHw4MEV7ZPn4vV9gHuA3vE4N5rZWak8hwPnAy/HpEvM7Ld5yeQ4TuPTs2dPNt5441qL0a3Is0WwBNjVzN6V1BO4T9JtZvZgKt8fzOyYHOVwHMdxSpCbIYiL0L8b//aMH4/wOI7j1Bm5Bosl9ZA0A3gDmGxm/87IdqCkmZJulLRhkXKOljRV0tTO+gUdx3GcbHI1BGa2wsxGAYOB7SRtk8pyCzDUzEYCdwJXFylngpmNMbMxG2ywQZ4iO47jNB1d0n3UzN4GpgB7p9Lnm9mS+Pc3wEe7Qh7HcRxnFbkZAkkbSFon/u4L7A78J5VnYOLv/sCsvORxHMdxssmz19BA4GpJPQgG549m9jdJ5wJTzWwS8G1J+wPLgbeAw3OUx3Ecx8nAp6F2HMdpAkpNQ92ha0hSfylM3i1pc0n7x3EBjuM4TjegnBjBPUAfSYOAfwBfBa7KUyjHcRyn6yjHEMjM3gM+B1xsZgcAw/MVy3Ecx+kqyjIEkrYHvgz8Pab5ZHWO4zjdhHIMwfHAacDNZvaEpE2Au/IVy3Ecx+kqOqzZm9ndwN2S+sf/zwHfzlswx3Ecp2sop9fQ9pKeJA72kvQRSZfmLpnjOI7TJZTjGvolsBcwH8DMHgU+kadQjuM4TtdR1hQTZvZSKmlFDrI4juM4NaCc3j8vSdoBMEm9CPEBnxPIcRynm1COIfgGcCEwCJgL3AF8K0+hHMepPVufdTuLlrRt/Pfv3YMnztm7yB5Oo1JOr6E3CWMIHMdpItJGoFia0/h0aAgkbQwcCwxN5jez/fMTy3Ecx+kqynEN/QW4grCaWGu+4jiO4zhdTTmGYLGZXZS7JI7jOE5NKMcQXCjpLEKQuLCsJGb2SG5SOY5Tc/r37pEZLHa6H+UYghHAIcCurHINWfxfFEl9CFNY947HudHMzkrl6Q1cQ1ireD5wkJnNqUB+x3FywnsHNQ/lGIIDgE3MbGmFZS8BdjWzd+NCNvdJus3MHkzkORL4r5ltJulg4DzgoAqP4ziO46wG5YwsfhRYp9KCLfBu/NszftLrYn4GuDr+vhHYTZIqPZbjOI7TecppEXwY+I+kh2kbI+iw+2hcuH4asBnwKzP7dyrLIOClWN5ySe8A6wFvpso5GjgaYMiQIWWI7DiO45RLOYbgrI6zZGNmK4BRktYBbpa0jZk9nsiSVftPtxowswnABAiL13dWHsdxHKc95a5HsFqY2duSpgB7A0lDMBfYEJgr6QPA2sBbq3s8x3Ecp3zKWY/gY5IelvSupKWSVkhaUMZ+G8SWAJL6ArsD/0llmwQcFn9/HvinmXmN33EcpwspxzV0CXAw8CdgDHAoMKyM/QYCV8c4QQvwRzP7m6RzgalmNokwYvlaSc8QWgIHd+Ic6ovWFTB7Mrw2EwaMhGF7QIv3vXYcp34paxF6M3tGUo/o879S0r/K2GcmMDoj/czE78XAFyqQt75pXQHXHgAvT4Wl70GvfjBoDBxysxsDx3HqlnK6j74X1yGYIemnkk4A+ucsV2Mye3I0AosAC98vTw3pjuM4dUo5huCQmO8YYBEhuHtgnkI1LK/NDC2BJEvfg9ceq408juM4ZVBOr6EX4s/FwDn5itPgDBgZ3EFLF61K69UPBoyonUyO4zgdUNQQSLqLjD79ETOz3fIRqYEZtkeICaRjBMP2qLVkjuM4RSnVIjg5I+1jwHeAN/IRp8Fp6RECw7MnB3fQgBHea8hx6g3v2deOoobAzKYVfkv6JHAGYSbRb5jZbV0gW2PS0gO22Dt8HMepL7xnXyYlYwSS9iIYgMXAD83sri6RynEcJw/a9Oyjbc++Jq68lYoRPAxsAJwPPBDTti1s94VpHMdpOEr17HNDkMki4F3C1A8H0naCuA4XpnEcx6k7vGdfJqViBDt3oRyO4zj54z37MilrignHcZxugffsy8QNgeM4zYX37GtH0SkmJO0Yv3t3nTiO4zhOV1NqrqGL4vcDXSGI4ziOUxtKuYaWSboSGCTpovRGM/t2fmI5juM4XUUpQ7AvYVWxXQkL0DuO4zjdkFLdR98EbpA0y8werbRgSRsC1wADgFZggpldmMqzM/BX4PmY9GczO7fSYzmO4zidp5xeQ/Ml3QzsSBhIdh9wnJnN7WC/5cBJZvaIpDWBaZImm9mTqXz3mtm+FUvuOI7jVIVyFqa5krDI/P8DBgG3xLSSmNmrhWkozGwhMCvu7ziO49QR5RiCD5nZlWa2PH6uIsxBVDaShhLWL/53xubtJT0q6TZJWxfZ/2hJUyVNnTdvXiWHdhzHcTqgHNfQPElfASbG/+OB+eUeQNIawE3A8Wa2ILX5EWAjM3tX0j7AX4Bh6TLMbAIwAWDMmDHFFstxasDWZ93OoiUr2qT1792DJ87xwTqO0yiU0yI4Avgi8BrwKmESuiPKKVxST4IRuM7M/pzebmYLzOzd+PtWoKek9cuU3akD0kagWJrjOPVLOWsWvwjsX2nBkgRcAcwys58XyTMAeN3MTNJ2BMNUdmvDcRzHWX3ynGtoR+AQ4DFJM2Lad4EhAGZ2OaF18U1Jy4H3gYPNzF0/juM4XUhuhsDM7qPtGgZZeS4BLslLBsdxVgNf27dp8NlHndWif+8emcFip8HxtX2big4NgaTjCOMGFgK/JXQDPdXM7shZNqcB8N5B3RRf27epKKvXUOz2uSdh/MBXgZ/kKpXjOLWl1Nq+TrejHENQ8PPvA1wZ5x0q6ft3HKfBKaztm8TX9u22lGMIpkm6g2AI/i/OG9Sar1iO49SUwtq+vfoDCt++tm+3pZxg8ZHAKOA5M3tP0noE95DjON0VX9u3qSjHEEw2s90Kf8xsvqQ/AruV2MdxnEbH1/ZtGooaAkl9gH7A+pI+yKq4wFqEmUgdx3GcbkCpFsHXgeMJSn8aqwzBAuBXOcvlOI7jdBGlVii7ELhQ0rFmdnEXyuQ4juN0IeVMOnexpB2Aocn8ZnZNjnI5juM4XUQ5I4uvBTYFZgCFuQSMsB6x4ziO0+CU02toDDDcZwWtb3yBGKfR8Ge2fijHEDwODCAsSuPUKb5AjNNVVEuB+zNbP5RjCNYHnpT0ELCkkGhmFS9W4zhO4+MKvPtRjiE4O28hHMdxnNpRTq+huztTsKQNCQHlAYS5iSbELqnJPAIuJMxj9B5wuJk90pnjOY7jOJ2jw0nnJC2UtCB+FktaIWlBGWUvB04ys62AjwHfkjQ8ledTwLD4ORq4rEL5nUjWYjC+QIxTz/gzWz+U0yJYM/lf0meB7crY71VigNnMFkqaBQwCnkxk+wxwTeyR9KCkdSQNjPs6FeA9LZyuolqr0vkzWz9UvFSlmf1F0qmV7CNpKGFls3+nNg0CXkr8nxvT2hgCSUcTWgwMGTKkMoEdx6kqrsC7H+UMKPtc4m8LYVxB2WMKJK0B3AQcH1c6a7M5Y5d2ZZvZBGACwJgxY3w8g+M4ThUpp0WwX+L3cmAOwaXTIZJ6EozAdWb254wsc4ENE/8HA6+UU7bjVAMf1OQ45cUIOrUITewRdAUwy8x+XiTbJOAYSTcA44B3PD7gdCXeJ95xynMNDQYuBnYkuG3uA44zs7kd7LojcAjwmKQZMe27wBAAM7scuJXQdfQZQvdRX/nMcRyniynHNXQlcD3whfj/KzGt5OKlZnYfHSxyH3sLfasMGRzHcZycKGfx+g3M7EozWx4/VwEb5CyX4ziO00WU0yJ4U9JXgInx/3hgfn4iOdUk92Bo64q4wPlMGDCy4RY4r1afeMdpZMoxBEcAlwC/IMQI/hXTnAYg12Bo6wq49gB4eSosfQ969YNBY+CQmxvGGHjvIMcpr9fQi4DPNOq0Z/bkaAQWhf9LF4X/syfDFq5gHadRKBojkPRTSd/ISD9B0nn5iuU0BK/NDC2BJEvfg9ceq408juN0ilLB4n2Jo3lTXAh8Oh9xnIZiwMjgDkrSqx8MGFEbeRzH6RSlXENmZq0Zia1xsJjTAOQaDB22R4gJpGMEw0r2LHbwEc1OfVHKELwnaZiZzU4mShoGvJ+vWE61yFWxtPQIgeHZk4M7aMCIhus1VCt8RLNTT5QyBGcCt0n6ATAtpo0BTgOOz1swp0Fo6RECwx4cdpyGpaghMLPb4toDpwDHxuTHgQPNzKOBjuM43YSS3UfN7HHgsC6SxXEcx6kBFS9M49QpDT7Ct9nwEc1OPeGGoDvQDUb4Nht59w7yXklOJZQz6ZxT77QZ4WttR/g6TYn3SnIqoUNDIGlzSf+Q9Hj8P1LS6fmL5pSNj/B1GpHWFfDU7XD3T8N3qxuqWlGOa+g3hJ5DvwYws5mSrgd+kKdgTgUURvgW5vwBH+Hr1DfuzqwrynEN9TOzh1JpyzvaSdLvJL1RaElkbN9Z0juSZsTPmeUI7GRQGOHbqz+g8F0Y4eu1LqfaVOOZcndmXVHuegSbEqagRtLngXLWFb6KMH31NSXy3Gtm+5ZRllOKYiN8wWtdTUpuvZKqVZMv5c70wYldTjmG4FuEyee2lPQy8DxhucqSmNk9koaulnRO+WSN8H3q9oafJtp7v3SO3K5PtaYed3dmXVHOegTPAbtL6g+0mNnCKh5/e0mPAq8AJ5vZE1mZJB0NHA0wZMiQKh6+m9MNal25936p1fiLRh33Ua1nqoEmLGyGykiHhiDtuy9MPGpm567msR8BNjKzdyXtA/wFGJaV0cwmEKfEHjNmjK3mcZuHGta6GuLlqVXAspEDpdV6phpowsJm6IpbjmsoccfpQ1inYNbqHtjMFiR+3yrpUknrm9mbq1u2E6lhrashXp5OuDmqYuAaeWW3aj5TOU9Y2BCVkTqhHNfQz5L/JV0ATFrdA0saALxuZiZpO0IPpvmrW66ToIFqXTWhE26Oqhi4RnbZNdAz1RCVkTqhM1NM9AM26SiTpInAzsD6kuYCZwE9AczscuDzwDclLSesb3Cwmbnbp9o0+DTRuc7JUyvXWaMHShv8mXLaU06M4DFi11GgB7AB0GF8wMzGd7D9EkL3UscpSq7N+Fq5zhooUOo0xwSB5bQIkv38lxPcOR0OKGs03J9YXRri5amVm6OB3CtO/hME1gPlGIJ0d9G1kksWm9lbVZWoRrg/sbo0zMtToZujagbO3Su50xCVkTqhHEPwCLAh8F9AwDrAi3GbUUa8wHE6TZ31t28YA+f4vaqAcgzB7cAkM7sVQNKngN3N7KRcJXOcRu5v7zQtjehmLscQjDWzbxT+xLWMv5+jTI4TKNHffuvr27vu6v1lc5qDRnQzlzvp3OnA7wmuoK/QDfv7uz+xDinR337RkuHtstf7y+Y0KHXmnsyDcgzBeMIYgJvj/3tiWrfCa5J1SMn+9q70S9IEyqtLaBL3ZDkji98CjusCWZwmJsuvumZv8dgmxfrb314bQRuBJlFeXUIjTwdSAUUNgaRfmtnxkm5h1YCylZjZ/rlKVuc0YkConsly6yxcYt7fvjPUSHl1y3eiE9OBFHMz1/P1KdUiuDZ+X9AVgtScCpvSjRgQakiK9LfPO6ZTzy9th9RoLqO834mK70k13GOdmA6kmDxDT/17u7R60RlFDYGZTYvfd3edODXCm9INR7GXrVoKvKhSK6Jc6spwNPpcRkWoyNBU651ukulAyplraEfgbGCjmF+AmVn3GUjWJH7ALqVGwco8a6UttBZVLnXVQmwS5VWSar3TTTIdSDm9hq4ATgCm0V27ajTytMD1SCdqY43QfXfnlhnFlUs90STKqyTVfKebYDqQcgzBO2Z2W+6S1JJONKUrVVx15TrIm07UxhrhOmytOcWVC+3HNdSUGiivujLmdegeq6vrk6IcQ3CXpPOBPwNLColm9khuUnU1nWhKV83n3B3pBi2srJf22Q9s4uMaSpC3Ma9Ikdahe6yeKzvlGIJx8XtMIs2AXasvTo3wpnR1qWFtrFq1rsyXtnVvuPbfmcqlf+/JdVvb6y5UpEj9na4I5bUomKTfEdYyeMPMtsnYLuBCYB/gPeDwcloZY8aMsalTpwNsI1cAAB8gSURBVFZb3KJUy6WT1XUMYM5PPt1p2eqW7twLa2UQ3JVLl+OjpVcLSdPMbEzWtlIDyk5MJRnwJnCfmT1fxnGvIqxAdk2R7Z8ChsXPOOAyVrU+6oamculUi87UxhrlJS/me28U+RuVRqpcNOCzUMo1tGZG2lDge5LONrMbShVsZvdIGloiy2eAa+I6xQ9KWkfSQDN7tQOZG5J6DhTlQiXBykZ6ybNodPmrRZ4KsFG6eDfos1BqQNk5WemS1gXuBEoagjIYBLyU+D83prUzBJKOBo4GGDJkyGoetjbUc6AoSU16NzXKS16MRpe/GuStABulA0KpZ2HYHnXbUignWNwGM3tLybUqO09WGZkBCzObAEyAECOowrGdItRimoCTev+FY1XhS55387uS8htFSeVJ3sawDruDZlLsWXj1UXjw0rptKVRsCCTtSli2cnWZS1gCs8Bg4JUqlFtVirp0GtAPWA9kGZXpy4bAGhW85HnXPistv1GUVJ7kbQzrsDtoJsWehdbldd1qLBUsfoz2NfR1Ccr60CocexJwjKQbCEHid+oxPpDdjbAx/YD1ypTWUZW95Hk3vyut3TaKksqTEsawKu7GRukOWuxZaOlR163GUi2CfVP/DZhvZouyMqeRNBHYGVhf0lzC4jY9AczscuBWQtfRZwjdR79akeRdRVbNvzPNYG9BFKWVlspe8ryb35XWbhtFSeVJCWO4aEn7tSM65W7MebR0rgZr9uS6bjWWCha/sDoFm1nJVcxib6Fvrc4xcqdYzX+jHSpTFA3UgqhZ76ZKXvK8m9+dcfU0wXw0JekGxrBq8bGsZ6HOW40VxwiaimI1/w3HVaYoGmgR9rqaJqAYeTe/6/ylrVua3RiWos4NpRuCUhRzEbR8oDJF4Yuwr6Qqhibv5nedv7ROg1LHhtINQSmKuQgGfgQ+cXL5isIXYV9FtWIleTe/6/ilbTSabjBlA+KGoBSlFEsliqKkgqqzRdjzDGrnHSvxmnxd0iiDKWtlsOphino3BKWolmJpFAWVt6LuihG4XpN3OskTZ9Vm5G89zGfmhqAjqqVYarQIe0Xkrah9BG7NqUntsxG6TjdQz748cENQY+qq2Zy3ovYRuJ2mWgq8y2ufjaJgm3y+qJZaC+DUEQVFnaSairoQK+nVH1D49m6ZZVEP7oNO0UbBWv2u81yqEtQEeIug1tRTsznv/vONEivpxrTQys4tM9hac3jChjKldVQY2Z0XjeIO7Aar6q0ObghqSb01m7tCUXswt3a0ruCanj9mdMsz9GEpi+nF9NbNOHTZafkds1HcgTUcRFirIHUSNwS1pB79kq6ouy+zJzO65Vn6awkA/VnC6JZn2Lv3TGC/fI7ZKKO0a9VarZPKoBuCWtIozWan5qzZW4xdNq2NS6dv756VFfLazJVGoEB/LeXSXXpVUdIUjeQOrEUlqE4qg24IakmjNJud2tK6gsc2uTy71lgJtXrevJVZnDqpDHqvoVrivWiccqhWzxt/3uqPvHvqlYm3CGpJIzWbndpRrVqjP2/1R53EUNwQ1Joizea8R4BWWn49zIfStFTTpeNumvqiToxzrq4hSXtLekrSM5JOzdh+uKR5kmbEz1F5ytNI5D2AqNLy31+yjF1bHuHYHn9m15ZHaKG1MQY0dQfcpdO9KRjnT54SvmvQQsutRSCpB/ArYA/CQvUPS5pkZk+msv7BzI7JS45GJe+BPxWVX4v+51WmoVs0dVJrdLovebqGtgOeMbPnAOIi9Z8B0obASZO34q20/NmTGd3yTLv+5zu3zCC3/udVpmGnaCjgLh0nR/I0BIOAlxL/5wLjMvIdKOkTwNPACWb2UjqDpKOBowGGDBmSg6h1Rt6Kt9LyX5tJH5a2SerDUoZrtZa1dpyq0NCtvTohT0OgjDRL/b8FmGhmSyR9A7ga2LXdTmYTgAkAY8aMSZfR/SiieEf1fLE25Q8YyWJ605/FK5MW04vnPrBxdeTpArp8jp1IowTlG1mZhvhV23u7aEnH+zmryNMQzAU2TPwfDLySzGBm8xN/fwOcl6M8jcOAkfTo3baXSI/e/fj2gQfWpvxhe9B/k3Fturj1HzSGSw9pF/+vT2oY46hUSdVKqdWT66wio9QN4lf1QJ6G4GFgmKSNgZeBg4EvJTNIGmhmr8a/+wOzcpSncci7b3Gl5Td6sLIWc+xA5UqqE0qtWjX5WrWYsqjIKHWD+FU9kJshMLPlko4B/g/oAfzOzJ6QdC4w1cwmAd+WtD+wHHgLODwveRqKvBVvZ8pv5GBlLebYgcqVVCeUWlVq8o1cq/b4VVXIdUCZmd0K3JpKOzPx+zSgAZ62GpC34m1kxV4ptZpjp1IlVSul1si16m4Qv6oHfK4hp/tTqwFZUUklKamkKs1PcOmkB/pVTN6dEyqkonMqxK8S97b/Jh/j0rMaJH5VJ/gUEw1GI/fuqBm1inFUGmSvNH+1XDp5d06ohNYVXNf7J4xkdptz+mbL6dn5Gz1+VSe4IWgw6ql3R0NRC1dYpUqq0vzVCoLXycRnAMyezPa9n4elq85pp75zeOzAEs6LZnJz5oQbggajnnp3OGVQqZKqJH+1guD1VKuuk/n5yyH31nkXrmfedIZgxFm3Zq701BCulUbu3eFUn+44K2kDLdaU65iP1hU8cM4nMl1kj52zT5UOsormMgStK7is9QeM7plSpEsaRJE2cu8Op/rUk0unWjTKOeVdKZs9mZHMbveuj102DXBDsHo0uiKts94dTo2pJ5dOtWiUc8pbl3RxV+LmMgSNPviknnp3OPVBvbh0qkkjnFPeumTASBbTi/6s8jUtphdP2kbVKT9Fc0UZ48VNkufFrTq+QInj1AedGPNREcP2YHrrZiyy3qwwsch6M711M6a0jqpO+Smaq0UwbA9mMoyR1jYA83DPj9ZasvJolGaz43R38p6IsaUH32w5nbHLpjFcL/CkbbSyY0seyKyxZnUeM2aMTZ06tfMFrOyS5YrUcZzVoMF0iaRpZjYmc1vTGQLHcZwmpJQhaK4YgeM4jtMONwSO4zhNjhsCx3GcJscNgeM4TpPjhsBxHKfJcUPgOI7T5LghcBzHaXIabhyBpHlANSb0WB9409M93dM7TK8nWTy982xkZhtkbjGzpvwAUz3d0z294/R6ksXT8/m4a8hxHKfJcUPgOI7T5DSzIZjg6Z7u6WWl15Msnp4DDRcsdhzHcapLM7cIHMdxHNwQOI7jND1uCBzHcZqcbm8IJK1dYtvYIuntVoOXtIWkHYvkb5cuaUNJp8Tfa0jqX4asfSS1G/Ah6UOS+nS0f2qfcRllf6HCMlaeQwX7tLt2GXl6Shot6VOVlB33/XCR9Mx7WQsk/ahK5axVYtuQKpTf7lpK+liFZRRdO1FS5gK+knJZJFzSmUU+F0g6o8g+36ug/M68D5n7SDpZ0oaVlJUn3T5YLGkqsIeZ/TeVvidwhZltmErvAbwO/AS43cwel7QvcAvwFmF03rupfR4xs20lrQ98ARgPDAKeBzYH4mrzLAQWmdnwIrJOiMf8cyr9h8C6ZvZNSRub2fOJbZ9L54/pLwIbA3tGefYCXgOuLnatzOznGefwNPBhYIuYbRZwkZldk3HMQ4FfACekNh0OTDazH0fD/ACwIpZ5D/B5M3u7mFxxnwOBLwFbmdmgmD4cODjKuhi4A9gyIeedZnZ7zNvbzJbE3xfHc3otdag14vfZGWJsDhwKDAcMeBL4mZnNTMi5HvAJ4EdmtlXGeZwIvGNmV6TSjwXWJDwfSfm/ZmYfiXn+YWa7xd/rAncBu6QO8c34/X4qfRCwDHgJeDDKD+F6PUPolXKTmb0jaTrwEPC/yXsi6XMZ1wTgdOAnZvbH1Dl9BLgdOBa4x8zekDQSOBX4eMZ79yywNvBKqvw1gRYz2yiV/8vAG4R7WLhm29H+nvYDzgRagf5mtjzu/2HgZ8ABZla0kpZ6H8YAl5rZycXyZ+wzDlgAvJrK9v+AtQj3YyLwJzN7U9KlwKlmtqDUMapNMyxe/2vgLkl7mNk8AElfAn4IfDoj/xUEhbAecJGkF4DtgReB3wOPSDrUzB6MZa0JrCvpdoKyuBnYBLgc2AHY2cyei3k3AaZLOt3MfpBx7J3M7OiM9E8BvePvm4BtE9tOB9KG4xPAusAcwku9I8EonEJ4sdL0AraKxjF5Dt8lKPUTgUcIxmxb4HxJZBiDsbGsZO1cwE4EBflj4KvA02b2WUkDgYeBhyR938yuTZxDX2B/gvLfNsr9WWCOpFMJL9lyYCPga8ClBEU6IR5zNDBJ0ifivXogcd2mAucAZ6XkL9yTpPwGDAY+CBwJXBDL/yjwgKRTzezieC6PxLI3lnQa4dlL8jVgZ9pzNzANuA6YHssfCwyXtKWZ/YdwPwtMIyiSacBAgvIUsE6U98JU+SewaoqCghEDeCye18eBH0t6ADgP2JD292S/RHn7ESpGAD2AX0r6m5m9ByBpZ2AS8DbBgP+vpL8B/wP8CDgi5htFuL9fjOdwNe0rKjcTrnuahwjX+k1gZjz/EYT39DPxPI+Lx/pVPM/pko6L+U4Efkow7G2I7/QBUbbk+/BUMSNQYp9TgfuA/xKMcZqhhMrMGZIeBd4h6Jgzzez6rGPlQt5Dl+vhAxxCeOgHAscD/wGGFsn7OPBi/N0HeBcYADwS0z5BqEWdSXCtvU9QQB9nVQvrOeApoE9G+c8THvrPZXzmFpFpOjCr8Du9LfV/LvAvwguyZuGYHVyf9wnKKH0OD2ZdJ8LD+2CRsgrXTsBX4nX/LzAypv8dODx1bsMJL8BCQu1pGaEGdwWwB0HZPB/P6wngDGBY4nreRjC4aVlmA7eVc92KnMtQ4DJgCXBWxvangUfj7+8C18TfS+Ln+dRnKfBcRjk3Fq5bKv05Qk2dwvOX2PZIBedxAkEZ/Z2gKNfIyNOLoEAnEmrVt6TuyUJgQZFr+T3gXkIF6sB4jOeIzz9BCb8PDCMoyTMJLZ77CC2GF0rIPhP4ckb6RcA8QmuhkNYS0x+O1/ts4IOJ7cfF52ouMDimvRePkfy0Et77Z2j7PjxH9nv7uXi/s96hCwjP7VvAFIIh/DShhZ88nx6EVvv0eK3+APwD+HzyOB3d685+mqFFgJldK2kx4SK/SKghT5GU5RfblBg7MbPFkp42s9ckFcq6R9IYQg30XuB84CSCwrhe0h8Sx12cUf5ahJu+X8a2HpK2M7OHUul9Cc1gWNWsR9IthNrnpETepcAowou9n6S/FvaRdFHGMSG8OFtknMNaZjYnI/8twDBJM1PpAj4s6SjCNfk34UG+HBgS3W47Emt4kj5AMLJ/JSiTX5mZxZqRCMriP2a2It6reYTa+YeBDQiK3oBNzWxKhpwLCbUyaHvdJtH+uiU5KcozjuA++KSZnZOR7z3CdQbYDfhN/P0kQRmManNxpMeA3TPKGUVQuml6AR+XdBLwoehagnBtCrGk5HmdWeR8AP6P0KIdD/wjtnR/ZGYzAMxsqaQnCdd8F4IBPpl4T1JltflvZj+U9D6hhSJgV+APheffzP4r6Skzmy2plfDe7Gdmz0S5T4jxkG8R3FiTgMnAMcBWwEGE1lKS3YG3zaw1kXYeQcmuCWxi0YUraZ24bRywN7APcFtsHTxP+3fxyJjWDzgt8T6sDewbzzHNDELFsc07ZLEFIakXwbW0A6GV8htJb5vZcEkjCK2Cg4D5wGkEw/HDKEfhHI1U679adHtDEF8+I9y8fgSXz11AT8IFTgYsRWgtLIlKTsCm8fcwSY+a2Ucs+E6/JOkwgjthMcGNMR74C6HZ/pKkw8ws3dR9i1Dz/2qGrNsBf5R0FeGlgvDwDAPeiIp/k4QCW5dgVH6WceqjCS/0+cDakg4itHaWxO1J10jhWPemzuFNSZub2dOpsvcF/kb7F+hQguvno8DeZvZCPK+vE2pqA4Djzazgx51JcB/skkjDzD4iaUtCM/tOSW8QXu6vE2pLBwLnSNqM4A5J+4ULDI7HvxgYnDCEexCe/XsJxqrwYm9MaMXcRHAbHBmN0LGShpjZi6ny3yS41A4guJ1uj+kiPF9pzgf+HhX7IzHto4SW6v9k5P9NPOc14u+kW++3GfkXZaT1Jyi29czs+7Fi0JfQSt5c0lsEBTQ+5u1HcLkclbwnxYjPZOH92oBQi/45MFLSawQXDsDQ+NxOAzYjuGtvB26I+15LaDk+ABxFcGP2iumS1N/MFsVj9idUBtLX4CTC890LeKVQeSNcv6WEltBy4I7olroUGFh4ThOcCZwpaVOCgi68D/MJ8ZD0+5C8HpuQeIck/S/BTfQ6oRK4dvzMB5ZF49tKaIntSbg3lxG8BtuZWTq2kAvNECzO6qEggpL4rpntk+GrvA24JpX/WEKgcp9U+eMJTdd9E2kjCS/udgSf5zTCyzKW8AIeama/T5Xz8XjsdwlKYZu46Ym4f1Yw9UPAG2Z2d4nz70moBY0H9jSz9WP6dDMbXWK/EQRl1Upwc7XZTKhx9U/t00poucyjba2xJ7DMzEam8h9CqNXdQgpJ+xXSYwtsPCEAN9fMdojpHyYosZ8RjPGVqWK2ItyDb2fIvw1BcY0kuEwmEgzTS/H/ikT+TQgtmRNoey+/R1B8Swg15zuiXD8B3jSzCzLO61MEv3Hh/j5OcI39OJ03ynm8tQ+snpj4eyJB8a7EQtB/TYIr5EhCa2A+oRb9EkH5/g34J6EGfiMw0cymKsTSJmfInVT4HycE+SFUrAC+T6iwtALPElxAENxnyfRCIHsqIeYzntCCeB8Yb2Z3xJbjm8CQmP4DgnEoKOwhhFb73rS9T9cDXwZ+b4lgvaRnzGyz9DnFbYsJbr2Vl4/QYrjczG5K5BsRr9cSMxucUc7xBFfXDFsVkB5B0CNbEtxG/ya4Wx8k3I/bCEH5xxPlLInn++NCOV1BtzcESVIK/zXCw7Yp4ab8ATjZEr0TUvmfJ/hrL0mlrwFMMLPvpo51AKFpfQWwNeEFeoKg5M8ws1tT+ccQ/ND7xf8bAFgMcCfyrUxX7K0U028yswMlfYbg//xVTP83wWAAnGkx+Jfct8T1KtbN7wnCC5N+eFpi2jap9H8SjN/9qfJfBZZa+x4hRwDfM7NNU+ktwHFm9otU+mEEhTQ/S9iMVlly394EZXQ+QWG2U4KRDQnKLXkvLzCzRzPKLOZyKsizfyp/Omhd4JPxe0oqfWfCdb6H9vQlBNG/TKiEXEi4LjMJLrgFrLpvmxBiFisNSZQlSykU7tGfaKvYlxKC4HsQ3K6FStY1sZzDU+lXESpgKwOnCr2gZgDPmNmuMa3QE28swaf/NqElsTOhJTqc4IMvGIKCcX6YoNd2SZRf9Fkvcu13JVQg3gV+B1xvZo9KOp3gehpI0BcTC641SRcQ3D5bEq71v4D7CYZ6bYLB/xehxfM4IXawfUb+fQit+XT6A2b2VtY5VINubwgkbc6qLoYrFT7hxb6X0Pwv+CqfI9QysvLvUSR9oZmlFR8KvSS2MLNhqfRnCIHfdjGC6Ma6ieArbSG8PCuAi1nVKlHcthxYbmYD477TzWy0pPuBg83spZg+g+C/7g9caau6ICaNyEKyX34BZmZF+7OXg6R9CAppHzObHdNOI7g9jNBSSaZ/CfiUmc1NlTOJUKu9M+s4GQq2lEJuIbzk4wlB4UnA78zs5QrOq1j5exFqsj+krevp0PidtbCSmdn3U+WflJEv6epZI5X/fEJQcQKhhVLwkZ9N9v3NMjQ7FORh1XXuR6iRDyQYkqRif4GgxE8ws4XxeGsRascCdkil/4Kg0B+LnyvMbLmkFaxybYlg0N6L57vIzNZS6A13A+E92Af4cKElHisDlxMMwf/RtgvtmYQaeWbLOWkIC0TjdA/BNXUwwf9/fTz+0phWSJ8I3GBmT6diAdvHz9uESuMO8bMNwUX8AOEZyco/KivdinQ9X126fYyA4PNvF5wi+JkPpr2vslj+YunFBnoNJTuoVNiWxQCCC2I7i2MFos/x1ljW2FT6DEknxBpy4UXvVTACkfvMbD4wX9LOkgr9k/slfgOQVvjRQJDORxED0YFBaSEE6D5LUCpjCTWfbTPSP2GpcR+R7cn27f8oHj+tmIsp5NMI8YBtgXMKTXNJkxJ+5STbxe90EL9Y+b8gvMTbEIxawfX0JO3pT6g19lX2wS369guunq8SFPENah8cPolQcTgd+F6iuGL3K8vQ3E+4D+sRlFehC+YbBMX4PynF/hLhGVuYEHiBQvdfMtLXJNz36wnxueGEVl6PDFlQjMvFvwcRWt83KQwE6xnzFLomLya0VL4EJMc19CDEV7K6TmdiZm9JWmZm5wHnSRpNqDicHWVNp58Vj9OXtrGAV4DHLIxHepvQKeAdQpxtO4Jbr13+YuWUK3+lNEOL4ACCwt+BEMy7AfitmW0ct/enra/yHoJy3zSZn/CytiuH4O/7p5n9hgSSXgemmNlBqfSJwG5m9qFUeqGP+jAzezO17THCi5z2sReaxe+xqga1BqFmlfXiP5t2t3QlknYiBNH+BXzRYq+SYukZ+/cgDMy5jba+/SkEhTSRtgq5hVUKOZn/MVbVPpMvwBrx/6mpcv5KUIS/Kad8M3siIXPS9XSumV0c05M+/OcJtdXkQMWVNX/gl7R19RyRcXlKtRRK9SZKG5ojCa2jFYR+8YVjPgRsbimFIelpgh5Jt3yfjoVvnkp/DOhtZpsr9Bp7qJSLUtLjwKjYavgPcLSFnnuPAj3MbBtJvyLEpfaP7qQZluixVY4bNOO4uxK6Kf+c8N7vRrhHEwn3ee9U+jqE52chbWMBhxB0xo6EbtH3E1oCuxJaWOn85xHcj23Si1SMqka3bxGY2c3AzQmFfwKhi+NlwM0WAnzXAdfF5uAXCDWPLZP5CRH9KwgvYTJ9CXC8wkjHZE+fHrSvQRLT9pA0JZW/F/B62ghEREbrwsx6SHo86ZqSdB3BAKUN09eLyJM7iZaCCAPjdiP0girU0N4tkr4wXRTQ18wOSyjYKYRA5dPx/8oaeFTId0UZkvmPKyjklJw9CC7ANuUQlHG79GLlSzqX4J75NKtcTxcBf47P2ImsUuzbJl/yVM3/tXjdFgIjbNWI9p8VyX8D2T3ISvYmirIX5LmFUFudkDymJEsbgciThG6ZaRaQPYXNGsSabVTuGVnaMBG4W9KbhNbXvTG9L0H5Q3hujiaMg4D2eq3oQbSqV2GSgYn9jiZc16MJCn08YaDgQ4V0M1sUvQq9CV2aX2ZVXGMoIRh/giV6AEnav0j+IUXSc6XbtwiySCr8QnCqM/lThuP7tO3p8wSh29hS2iv8Awg9WlbmN7N/Fqu5SHoEoNi2ZLqkDxFq10to20WxN/BZM3u9o/OtZ6LSSirYNr79dA2c9gq5rFhAiZp8OeWPJARibyP4jguup0wfftyWNhCFIO8SQjwo+aIq/r8omb+cWmOq5v8GoTJzWUEehZ5fWcfsS4hJ9U2Vd2y8Do/StkfVWvH3glT6JwiGv1AxKLRki8ajFOY/GgjcYau6kP6cUKt+gaA8tyUMXFsXuNrMdkzsv64VCbSqfYcII8QFfk/oHPJWIu9dBJfWTVnlRdfe1mTEAsysXVC6VH5CUL6scqpBUxqCrkTSLqQUfom8yYBZklI15D5m1q7Pemzabl3OcRsFSVcTrmUbBRu3ZRmITIXcwTEyDQ2hh1m5Cr+VbNdTsgWUTO9DqMWeRspAFJGxqEEpsU/FhiaplCUNIgxmKgwcKyj2voSKzRYkelSZ2T/ifrtmpVeDIgZic8J4gUdK7pwjkgYTXEE7EFpX65nZOpXmr7Sc1ZLZDYHTKJRQsH0JbogfU55CLhY8zTQ0JdIrKr+D8ypLIXcyf8WGo4SsuSn2RkbSt8mOBdxPCBa3lpl/CKGiUVY5VZPfDYHT6FRZIVdSk69K99q8qdRwOJUTXVX/Au63MkYDF8tfaTnVwg2B4zhOk9PtF6ZxHMdxSuOGwHEcp8lxQ+A4KSR9T9ITkmZKmiFpnKTjJfUrY9+y8jlOPeExAsdJIGl7wmjSnc1sicKyg70IAbwxRQb8JfefU04+x6knvEXgOG0ZSJhCeglAVOifJ8xHf1ccVISkyyRNjS2Hc2LatzPy7SnpAUmPSPqTpDVi+k8kPRlbHe2mq3acrsRbBI6TICrq+wgzbt5JWGnr7nRNvzBaNU5L8Q/g22Y2M5kvtib+TJhJdZHCIiW9gUsIfcO3NDOTtI4lFop3nK7GWwSOkyAOtvooYW6ZecAfJB2ekfWLceqP6YQBVlnTA38spt+vMB34YYR5/RcQZsr8raTPEaZYcJya0e0nnXOcSjGzFYTJ6abESckOS26XtDFhLYqxFtbjvYrs6cgFTDaz8e02hGVJdyPMYHkMYd4cx6kJ3iJwnASStpCUnFJ5FGFis4WsGmG8FmEE8jsKy2Um171O5nsQ2FFhbWUk9ZO0eXQ/rW1hlbrj4zEcp2Z4i8Bx2rIGcLGkdQhTMjxDcBONJyyg86qZ7SJpOmGG2ecI88AUmJDKdzgwMU5mB2HRmIXAXyX1IbQaTuiKE3OcYniw2HEcp8lx15DjOE6T44bAcRynyXFD4DiO0+S4IXAcx2ly3BA4juM0OW4IHMdxmhw3BI7jOE2OGwLHcZwm5/8D8YXd7wTZyusAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The progression of numbers of unique names by state in gender\n",
    "\n",
    "region= baby_name_original.loc[:,['Name','Year','Gender','State']]\n",
    "region\n",
    "\n",
    "\n",
    "\n",
    "f= region.loc[region['Gender'] == 'F']\n",
    "f\n",
    "\n",
    "m= region.loc[region['Gender'] == 'M']\n",
    "m\n",
    "\n",
    "\n",
    "fgender= f.groupby(['State']).sum()\n",
    "fgender = pd.DataFrame(fgender)\n",
    "fgender\n",
    "\n",
    "mgender=m.groupby(['State']).sum()\n",
    "mgender= pd.DataFrame(mgender)\n",
    "mgender\n",
    "\n",
    "data=pd.merge(fgender, mgender, how='left', on=['State'], suffixes=('_F', '_M'))\n",
    "data\n",
    "\n",
    "f= data['Year_F']\n",
    "m =data['Year_M']\n",
    "\n",
    "\n",
    "x = data.index\n",
    "y1 = f\n",
    "y2= m\n",
    "fig = plt.figure()\n",
    "\n",
    "ax1 = fig.add_subplot(111)\n",
    "\n",
    "ax1.scatter(x, y1, s=25, marker=\"s\", label='Female')\n",
    "ax1.scatter(x, y2, s=25, marker=\"o\", label='Male')\n",
    "\n",
    "\n",
    "plt.title(\"Unique Names in Each State\")\n",
    "plt.xlabel(\"States\")\n",
    "plt.ylabel(\"Unique Counts of Names\")\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.legend(loc='upper right');\n",
    "plt.show()\n",
    "plt.savefig(f'Output/The Counts of Unique Name In Different States per Gender.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation: states CA and NY have the highest number of unique names across all states"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overall, there is an increase in “new” baby names overall, and particularly from 1970 onward.\n",
    "\n",
    "One reason for this is U.S. population growth in general (Baby Boomers… now millennials). There are more names, therefore, more opportunities for newness.\n",
    "\n",
    "Another explanation for more “new” names is cultural: the data suggest that modern parents are less likely than their predecessors to name their child after a family (“junior”). These new parents value individualism more than tradition.\n",
    "\n",
    "There is a correlation between the volume of new names and increased immigration during peacetime. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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"
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 },
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}