susanli2016/Baby_names_alberta.ipynb

## Baby_names_alberta.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names = pd.read_excel(\"baby-names.xlsx\", skiprows = 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The data contains newborn baby names in Alberta from 1980 to 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Michael</td>\n",
       "      <td>732</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Christopher</td>\n",
       "      <td>633</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>David</td>\n",
       "      <td>537</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jason</td>\n",
       "      <td>526</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ryan</td>\n",
       "      <td>511</td>\n",
       "      <td>Boy</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Frequency Gender  Year\n",
       "0      Michael        732    Boy  1980\n",
       "1  Christopher        633    Boy  1980\n",
       "2        David        537    Boy  1980\n",
       "3        Jason        526    Boy  1980\n",
       "4         Ryan        511    Boy  1980"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>312827</th>\n",
       "      <td>Aaditri</td>\n",
       "      <td>1</td>\n",
       "      <td>Girl</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312828</th>\n",
       "      <td>Aadila</td>\n",
       "      <td>1</td>\n",
       "      <td>Girl</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312829</th>\n",
       "      <td>Aadhya</td>\n",
       "      <td>1</td>\n",
       "      <td>Girl</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312830</th>\n",
       "      <td>Aadhana</td>\n",
       "      <td>1</td>\n",
       "      <td>Girl</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312831</th>\n",
       "      <td>A'Isha</td>\n",
       "      <td>1</td>\n",
       "      <td>Girl</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Name  Frequency Gender  Year\n",
       "312827  Aaditri          1   Girl  2015\n",
       "312828   Aadila          1   Girl  2015\n",
       "312829   Aadhya          1   Girl  2015\n",
       "312830  Aadhana          1   Girl  2015\n",
       "312831   A'Isha          1   Girl  2015"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The data should be re-indexed by \"gender, name and year\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names_indexed=names.set_index([\"Gender\", \"Name\", \"Year\"]).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Frequency</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <th>Name</th>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Boy</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">True</th>\n",
       "      <th>2014</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>2001</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A'Jay</th>\n",
       "      <th>1986</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A'Lex'ander</th>\n",
       "      <th>2001</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Frequency\n",
       "Gender Name        Year           \n",
       "Boy    True        2014          1\n",
       "                   2015          1\n",
       "       A           2001          1\n",
       "       A'Jay       1986          1\n",
       "       A'Lex'ander 2001          1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names_indexed.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plotname(Gender, Name):\n",
    "    data = names_indexed.loc[Gender, Name]\n",
    "    plt.plot(data.index, data.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's have a look the popularity of my name and my friends' names. C'mon, my name has never been popular for the past 35 years in Alberta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x16c64538e10>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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rW17BhfF9qvluxNuZTCZGtLqK/LIC1uzbwPqsTXy2bRY32q7FZDJ5OjwRERER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\nkyAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16c64538470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,3))\n",
    "names = [\"Susan\", \"Jessica\", \"Elizabeth\", \"Lisa\", \"Karen\"]\n",
    "\n",
    "for name in names:\n",
    "    plotname(\"Girl\", name)\n",
    "plt.legend(names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How about my male friends' names?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x16c677e68d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IY0yceE0rP+mFpeDMgiJdYUS6whoXwK+vc1OQW0bu0VLyskspL6tmxJXdSOro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\nIAiCIAiCIAiCIAiCICzh/wfknSBZUgkV4gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16c677e6908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,3))\n",
    "names = [\"Andrew\", \"John\", \"Peter\", \"Michael\", \"Jacob\"]\n",
    "\n",
    "for name in names:\n",
    "    plotname(\"Boy\", name)\n",
    "plt.legend(names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def topten(Gender, Year):\n",
    "    list=names_indexed.loc[Gender,:,Year].sort_values(by=\"Frequency\", ascending=False).reset_index()\n",
    "    list=list.drop([\"Gender\", \"Year\", \"Frequency\"], axis=1).head(10)\n",
    "    list.columns=[Year]\n",
    "    list.index=list.index+1\n",
    "    \n",
    "    return list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Olivia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Emily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sophia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ava</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chloe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Ella</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Abigail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Avery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Amelia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       2015\n",
       "1    Olivia\n",
       "2      Emma\n",
       "3     Emily\n",
       "4    Sophia\n",
       "5       Ava\n",
       "6     Chloe\n",
       "7      Ella\n",
       "8   Abigail\n",
       "9     Avery\n",
       "10   Amelia"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topten(\"Girl\", 2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now, let's look at the top ten most popular boy's names for the past 10 years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def toptens(Gender, Year0, Year1):\n",
    "    years=[topten(Gender, Year) for Year in range(Year0, Year1+1)]\n",
    "    \n",
    "    return years[0].join(years[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Liam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Joshua</td>\n",
       "      <td>Joshua</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Noah</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jacob</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Mason</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Ethan</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Ethan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Joshua</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Noah</td>\n",
       "      <td>William</td>\n",
       "      <td>Benjamin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Logan</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>Joshua</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Mason</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Lucas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Liam</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Noah</td>\n",
       "      <td>William</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Carter</td>\n",
       "      <td>Nathan</td>\n",
       "      <td>Owen</td>\n",
       "      <td>Nathan</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>William</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Oliver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Nathan</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>Matthew</td>\n",
       "      <td>Owen</td>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Jacob</td>\n",
       "      <td>Oliver</td>\n",
       "      <td>Mason</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Noah</td>\n",
       "      <td>Carter</td>\n",
       "      <td>Liam</td>\n",
       "      <td>Noah</td>\n",
       "      <td>William</td>\n",
       "      <td>Owen</td>\n",
       "      <td>William</td>\n",
       "      <td>Carter</td>\n",
       "      <td>Mason</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Logan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Evan</td>\n",
       "      <td>William</td>\n",
       "      <td>Nathan</td>\n",
       "      <td>Owen</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Carter</td>\n",
       "      <td>Logan</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Carter</td>\n",
       "      <td>Carter</td>\n",
       "      <td>Alexander</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       2005     2006       2007       2008       2009       2010       2011  \\\n",
       "1     Ethan    Ethan      Ethan      Ethan      Ethan       Liam       Liam   \n",
       "2    Joshua   Joshua      Jacob      Jacob       Liam      Ethan      Ethan   \n",
       "3     Jacob    Jacob      Logan  Alexander      Jacob      Logan      Mason   \n",
       "4   Matthew    Logan       Noah     Joshua      Logan  Alexander      Lucas   \n",
       "5     Logan  Matthew     Joshua       Liam       Noah      Lucas      Jacob   \n",
       "6      Liam     Noah  Alexander      Logan  Alexander      Jacob  Alexander   \n",
       "7    Carter   Nathan       Owen     Nathan   Benjamin       Noah   Benjamin   \n",
       "8    Nathan     Liam    Matthew    Matthew       Owen   Benjamin       Noah   \n",
       "9      Noah   Carter       Liam       Noah    William       Owen    William   \n",
       "10     Evan  William     Nathan       Owen      Lucas     Carter      Logan   \n",
       "\n",
       "         2012      2013      2014       2015  \n",
       "1        Liam      Liam      Liam       Liam  \n",
       "2       Ethan     Lucas     Ethan       Noah  \n",
       "3       Jacob     Ethan  Benjamin      Ethan  \n",
       "4       Logan      Noah   William   Benjamin  \n",
       "5       Mason     Logan     Logan      Lucas  \n",
       "6    Benjamin  Benjamin      Noah    William  \n",
       "7       Lucas   William     Jacob     Oliver  \n",
       "8   Alexander     Jacob    Oliver      Mason  \n",
       "9      Carter     Mason     Lucas      Logan  \n",
       "10       Noah    Carter    Carter  Alexander  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toptens(\"Boy\", 2005, 2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### And girl's too ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Emma</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Olivia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emily</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Emma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hannah</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emma</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Emily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Madison</td>\n",
       "      <td>Hannah</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Isabella</td>\n",
       "      <td>Isabella</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Sophia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ava</td>\n",
       "      <td>Madison</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>Emily</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Ava</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Grace</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>Hannah</td>\n",
       "      <td>Isabella</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Chloe</td>\n",
       "      <td>Chloe</td>\n",
       "      <td>Lily</td>\n",
       "      <td>Avery</td>\n",
       "      <td>Isabella</td>\n",
       "      <td>Chloe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Olivia</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Madison</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Alexis</td>\n",
       "      <td>Ava</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Ella</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Ella</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>Olivia</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Madison</td>\n",
       "      <td>Ella</td>\n",
       "      <td>Ella</td>\n",
       "      <td>Lily</td>\n",
       "      <td>Isabella</td>\n",
       "      <td>Lily</td>\n",
       "      <td>Ella</td>\n",
       "      <td>Abigail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Chloe</td>\n",
       "      <td>Grace</td>\n",
       "      <td>Sophia</td>\n",
       "      <td>Hannah</td>\n",
       "      <td>Hailey</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Abigail</td>\n",
       "      <td>Chloe</td>\n",
       "      <td>Hannah</td>\n",
       "      <td>Avery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Hailey</td>\n",
       "      <td>Ella</td>\n",
       "      <td>Hailey</td>\n",
       "      <td>Chloe</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>Alexis</td>\n",
       "      <td>Sophie</td>\n",
       "      <td>Chloe</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>Amelia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       2005     2006     2007      2008      2009      2010      2011  \\\n",
       "1      Emma      Ava      Ava       Ava    Olivia      Emma    Olivia   \n",
       "2     Emily     Emma     Emma    Olivia      Emma    Olivia    Sophia   \n",
       "3    Hannah    Emily    Emily      Emma       Ava     Emily      Emma   \n",
       "4   Madison   Hannah    Sarah     Emily  Isabella  Isabella     Emily   \n",
       "5       Ava  Madison   Olivia     Sarah     Emily    Sophia       Ava   \n",
       "6     Grace    Sarah   Hannah  Isabella    Sophia     Chloe     Chloe   \n",
       "7    Olivia  Abigail  Madison    Sophia    Alexis       Ava   Abigail   \n",
       "8     Sarah   Olivia  Abigail   Madison      Ella      Ella      Lily   \n",
       "9     Chloe    Grace   Sophia    Hannah    Hailey   Abigail  Brooklyn   \n",
       "10   Hailey     Ella   Hailey     Chloe     Sarah    Alexis    Sophie   \n",
       "\n",
       "        2012       2013       2014     2015  \n",
       "1       Emma     Olivia     Olivia   Olivia  \n",
       "2     Olivia       Emma       Emma     Emma  \n",
       "3      Emily      Emily      Emily    Emily  \n",
       "4     Sophia     Sophia     Sophia   Sophia  \n",
       "5        Ava        Ava        Ava      Ava  \n",
       "6       Lily      Avery   Isabella    Chloe  \n",
       "7       Ella    Abigail    Abigail     Ella  \n",
       "8   Isabella       Lily       Ella  Abigail  \n",
       "9    Abigail      Chloe     Hannah    Avery  \n",
       "10     Chloe  Charlotte  Charlotte   Amelia  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toptens(\"Girl\", 2005, 2015)"
   ]
  }
 ],
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