chapter2.3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>sex</th>\n",
       "      <th>births</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name sex  births\n",
       "0       Mary   F    7065\n",
       "1       Anna   F    2604\n",
       "2       Emma   F    2003\n",
       "3  Elizabeth   F    1939\n",
       "4     Minnie   F    1746"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names1880 = pd.read_csv('yob1880.txt', names=['name', 'sex', 'births'])\n",
    "names1880[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sex\n",
       "F     90993\n",
       "M    110493\n",
       "Name: births, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1880年の性別出生数\n",
    "names1880.groupby('sex').births.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690754</th>\n",
       "      <td>Zaviyon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690755</th>\n",
       "      <td>Zaybrien</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690756</th>\n",
       "      <td>Zayshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690757</th>\n",
       "      <td>Zayyan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690758</th>\n",
       "      <td>Zeal</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690759</th>\n",
       "      <td>Zealan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690760</th>\n",
       "      <td>Zecharia</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690761</th>\n",
       "      <td>Zeferino</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690762</th>\n",
       "      <td>Zekariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690763</th>\n",
       "      <td>Zeki</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690764</th>\n",
       "      <td>Zeriah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690765</th>\n",
       "      <td>Zeshan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690766</th>\n",
       "      <td>Zhyier</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690767</th>\n",
       "      <td>Zildjian</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690768</th>\n",
       "      <td>Zinn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690769</th>\n",
       "      <td>Zishan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690770</th>\n",
       "      <td>Ziven</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690771</th>\n",
       "      <td>Zmari</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690772</th>\n",
       "      <td>Zoren</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690773</th>\n",
       "      <td>Zuhaib</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690774</th>\n",
       "      <td>Zyeire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690775</th>\n",
       "      <td>Zygmunt</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690776</th>\n",
       "      <td>Zykerion</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690777</th>\n",
       "      <td>Zylar</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690778</th>\n",
       "      <td>Zylin</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690779</th>\n",
       "      <td>Zymaire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690780</th>\n",
       "      <td>Zyonne</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690781</th>\n",
       "      <td>Zyquarius</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690782</th>\n",
       "      <td>Zyran</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690783</th>\n",
       "      <td>Zzyzx</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1690784 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name sex  births  year\n",
       "0             Mary   F    7065  1880\n",
       "1             Anna   F    2604  1880\n",
       "2             Emma   F    2003  1880\n",
       "3        Elizabeth   F    1939  1880\n",
       "4           Minnie   F    1746  1880\n",
       "5         Margaret   F    1578  1880\n",
       "6              Ida   F    1472  1880\n",
       "7            Alice   F    1414  1880\n",
       "8           Bertha   F    1320  1880\n",
       "9            Sarah   F    1288  1880\n",
       "10           Annie   F    1258  1880\n",
       "11           Clara   F    1226  1880\n",
       "12            Ella   F    1156  1880\n",
       "13        Florence   F    1063  1880\n",
       "14            Cora   F    1045  1880\n",
       "15          Martha   F    1040  1880\n",
       "16           Laura   F    1012  1880\n",
       "17          Nellie   F     995  1880\n",
       "18           Grace   F     982  1880\n",
       "19          Carrie   F     949  1880\n",
       "20           Maude   F     858  1880\n",
       "21           Mabel   F     808  1880\n",
       "22          Bessie   F     794  1880\n",
       "23          Jennie   F     793  1880\n",
       "24        Gertrude   F     787  1880\n",
       "25           Julia   F     783  1880\n",
       "26          Hattie   F     769  1880\n",
       "27           Edith   F     768  1880\n",
       "28          Mattie   F     704  1880\n",
       "29            Rose   F     700  1880\n",
       "...            ...  ..     ...   ...\n",
       "1690754    Zaviyon   M       5  2010\n",
       "1690755   Zaybrien   M       5  2010\n",
       "1690756   Zayshawn   M       5  2010\n",
       "1690757     Zayyan   M       5  2010\n",
       "1690758       Zeal   M       5  2010\n",
       "1690759     Zealan   M       5  2010\n",
       "1690760   Zecharia   M       5  2010\n",
       "1690761   Zeferino   M       5  2010\n",
       "1690762   Zekariah   M       5  2010\n",
       "1690763       Zeki   M       5  2010\n",
       "1690764     Zeriah   M       5  2010\n",
       "1690765     Zeshan   M       5  2010\n",
       "1690766     Zhyier   M       5  2010\n",
       "1690767   Zildjian   M       5  2010\n",
       "1690768       Zinn   M       5  2010\n",
       "1690769     Zishan   M       5  2010\n",
       "1690770      Ziven   M       5  2010\n",
       "1690771      Zmari   M       5  2010\n",
       "1690772      Zoren   M       5  2010\n",
       "1690773     Zuhaib   M       5  2010\n",
       "1690774     Zyeire   M       5  2010\n",
       "1690775    Zygmunt   M       5  2010\n",
       "1690776   Zykerion   M       5  2010\n",
       "1690777      Zylar   M       5  2010\n",
       "1690778      Zylin   M       5  2010\n",
       "1690779    Zymaire   M       5  2010\n",
       "1690780     Zyonne   M       5  2010\n",
       "1690781  Zyquarius   M       5  2010\n",
       "1690782      Zyran   M       5  2010\n",
       "1690783      Zzyzx   M       5  2010\n",
       "\n",
       "[1690784 rows x 4 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 全txt読み込み\n",
    "years = range(1880,2011)\n",
    "pieces = []\n",
    "# 列は名前、性別、出生数\n",
    "columns = ['name', 'sex', 'births']\n",
    "for year in years:\n",
    "    path = 'yob%d.txt' % year\n",
    "    frame = pd.read_csv(path, names=columns)\n",
    "    \n",
    "    frame['year'] = year\n",
    "    pieces.append(frame)\n",
    "    \n",
    "# 配列piecesを一つのデータフレームにまとめる\n",
    "names = pd.concat(pieces, ignore_index=True)\n",
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 年度別男女出生数\n",
    "total_births = names.pivot_table('births', index='year', columns='sex', aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1896468</td>\n",
       "      <td>2050234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1916888</td>\n",
       "      <td>2069242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1883645</td>\n",
       "      <td>2032310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1827643</td>\n",
       "      <td>1973359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1759010</td>\n",
       "      <td>1898382</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex         F        M\n",
       "year                  \n",
       "2006  1896468  2050234\n",
       "2007  1916888  2069242\n",
       "2008  1883645  2032310\n",
       "2009  1827643  1973359\n",
       "2010  1759010  1898382"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_births.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x14a22cc18>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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ppQGVdOWeleke49AhN7w5MjLdTfXZZ91TEU+fTn/b9IwY4eYSi082xVR8vOvb\nuuEGN+z3fG7Q37zZ/ZtKfAQw1qdhTN62+fBmLipyEV8tT/3JSPG+eCZvnMxtjW/jww/dr8n69XM5\nyFT492vM3zmffcf2pbmtT30MXjqYx1o/BkCPhj34fv33uRUqWw5vof2w9oxcNZJWQ1uxcq+7y3pJ\n5BJ6TerF460f5/Lgy9M9zpdfwi23QEYmaRgwAEqUcP0G0dHnH/uSJa4mMXy466OYOBF27ID4eFfj\n2bcPvv8eLr3UzRWWWXXquOa2sWPT2TC1TFKQXlhNw+QTL8x8Qf89499a7p1yKR6kpKo6ad0kbfW/\nVnr6tBvtsnlzAIJMxf/+p9rbVRy0zw99dOBfA9Pcdnr4dG3xZYszc1VtO7JNLx5w8XlP550RPp9P\ntxzeokOWDNHK71fWzxd/rj6fT79Z/Y1ePOBibT6kuYZ+HKoD/hyQYnRUak6dcqOjVq/OeAynT7u7\n9Rs0UN2wIfPXcPy423fsWFeLmDJFNSzMxVG0qBs9dzQbBqJNm6baooU7BzbkNqmQkBDFPaK2wLxC\nQkIy+2/E5CE9xvXQcWvH6R0T7tDPF39+pjw2Plb/O/u/WuX9KjpryyydPl21XbsABprM2rXubmhV\n1bnb5mqdT+qkOoFegi9BW37ZUr9d/W2S8pZftszSlOHnEnEkQmt/XFuDPwjWuybepX9u/zPJ+k0H\nN+mM8BmZmlJ82DDVzp3PL56hQ93zTebPz9x+Tz7pmp9Sc/x4yuaq85WQoFqnjuqCBZY0jMnzGn/W\nVJvftExnhM/U5kOaq6qbB6jZkGba7dtuZx7Fef/9qh99FMhIk0pIUC1XTnX/fve+zw999IHJD6TY\nbuTKkdp2aNsUM+K+Pe9tfXLakzkS22M/P6bP//J8ts3Cu3u3m+V34cLzP8aMGa7vIHE6j7QsWqT6\n3/+6GkXNmrl3H87Age6GP0saxuRhPp9PS7xRUikepTN+SdCQj0L0xjE3ao0Pa+iYVWPOfOnFxqoG\nBanu3BnggJPp3t110qq66bXrf1Zfv1n9zZn1x2KPafWB1VOdT2nhzoXabEizbI9p37F9GvRukO49\nujf9jTPA51O98UbVV1/N+rHmzVOtVEm1Xz83lUfyv+fQoW6eqFdeUZ0+XTU687Own7fDh10nf1pJ\nw6ZGNyYP2HtsL0W0FGWKlWPEcHij3xtsPbKVCbdPoFSxUme2mzXLdXTWyNxs2Dmub1/44AO4/343\nvfbY28aHnfCVAAAgAElEQVTSeUxnihQqQtvqbRm2YhjXhFxDuxrtAPD54Pnn4dVXoWmVpmw8uJHY\n+FiKFymebTF9uuhTejXpRZXSVdLfOAO+/BL273cxZ9XVV8Pvv8O338KQIa6T+/LL4ckn3UO0Roxw\n93mkN1Q2JwQFwYwZbjh1qlLLJAXphdU0TD4wb9s8rfrf9vrSS66p5+DB1Le77z7VTz/N3dgy4vRp\n1yn7999nyyatm6Rdv+mqVT+oqmXfKavbo87Omfbjj66dY6g3s/tlX1ymSyKTTbeaBdGnorXiexV1\ny+Et2XK8WbNck9L69dlyuBRiY1W/+Ua1bVv3yo2ZitNDGjWNC/aOcGPykhErRvB/I37nk7BRTJrk\nhj4+/XTSbU6dckM8//4bqlYNTJzn8vLLLsYPP0y5Li4h7swUHKpw5ZWutnTkiKs99Z3Sl/Y12vPP\nlv/Mllg++OsDlu1Zxne3fZfpfX0+d5d3aCgUKQKffALvvQfffQdhYdkSXr6Q1h3h1jxlTB6w+fBm\nTu2uS7168OCD7slqTz0FsbGuqSA83N3Z27Rp3kwY4OJu1w7eeQeKJ2tl8p+z6Y8/4MABmDnTJY79\n+6FFcAuW7V4GLbMeh6oyeOlgxt6W3g0HqXvuOTf9xqlTLr6LLnL3oYSGZj22gsBu7jMmDwg/vJmo\nrXWpU8f9mj12DB54AGrWdJMS7tkDbdvCV6nf95cn1Knj2uV/+OHc273zDrzwApQuDV27wqRJ0LJa\nS5bvXZ4tcfy18y+KFy5Oq2qtMr3v2LHw44+upnHggOtzsISRlCUNY/KA9Xs3E6R1KVkSChWCN990\nE80tWACzZ7smn2eegbp1Ax3puT38sEtyPl/q61esgNWr4b773Ps773Rf1JdXuZy/9//N6YTTWY5h\nzOox9G7aG0njtuitW91516xJWr5uneuInjTJdQaXKgWtWkHJklkOqUCxpGFMgKkqW6M3U//isxnh\nnnvc7LF5PUkkd9ttbjruQYNSrlOF//zHTYWR2HzVpYv78o4+WIraQbVZd2Bdls4fGx/LhHUTuPuy\nu1Ndv2iR608JCoKOHV0/xdGjrt/i+uvdZ96sWZZCKPAsaRgTYAdPHARfYRqFBuCBGNmsSBEYM8bV\nlP7+O+m6776DgwfhscfOlhUv7ubQmjABWlT1+jWyYFr4NJpUbkJI+ZAzZapuyu8PP4Ru3WDoUDfM\n9ddf3fDZmjXhr7/cvE3335+l018QLGkYE2CbD2+mTHzdgIzJzwl167oH/9xzj+vIBzdK6rnn3L0O\nRZINv+nRA37+GVpWbcnyPVnr1xizxjVNJdqyxU0V3qWLe8bEzJkucYDrf1m50jVLjRvn+oxM+mz0\nlDEBtvnwZopE16VuAWoWeeABN5S2YUPXf7Fli5vlNbUv5rZtoU8f+G9wC8auzfyIpwU7F7Dn2B5K\nFCnB7K2zGdZ92Jl1r77qag+vvZb6zK+lS7uXyThLGsYEmP9w24JCxDVHrVgBo0a5pDF9eurbVqkC\nZcpA+VPNWbN/DfG+eIoUythX08ETB7nhmxvoWLsjMbExPH/F85QvUR6AVavcXdf/+9/5TRVuUmdJ\nw5gACz+0meiILtSpE+hIspeIe4Roixbpb9uqFWxYVYYaZWuw7sA6mlZpmqFzjFk9hpvr38yYHmNS\nrHvlFejXz2oS2c36NIwJsPADOyhPyAU9tLNVK/fY2G71ujFq1agM7aOqfLX8Kx5q8VCKdfPnuz6M\nRx7J7kiNJQ1jAmxXdCSXVK4e6DACKjFpPN3uaUasHEH0qfQfcbcochGxCbF0COmQYt3rr7t+jOR3\nppuss6RhTACpKgdjd3NpjQs7abRs6aZJqVGmFjfUvYGhy4emu8/QZUN5qPlDKW7i27LFjYq6O/Vb\nNUwWWdIwJoAOnTxEYS1Jw7oXBTqUgKpY0b3Cw+G59s/xyaJPztwdHu+LJ8GXkGT7mNgYvt/wPX2a\n9UlxrOHD4d57rZaRU6wj3JgAioyJpNipatTNWL9vgdaypWuiuueeFtSvWJ+vln/F0dijfLTwI4oW\nLkqfy/vQvUF3Vu9bzYR1E7g29FqCSwcnOUZ8vHsWxa+/BugiLgBW0zAmgHYf3Q1Hq1OrVqAjCbzE\nfg2A/1zxH56c/iSr96/m1/t+Zdrd0zgRd4I+k/vw+7bf6XVpryT3YySaOtXdzNe4cS4HfyFJ7SEb\nmvQhRsOAfcBqv7LXgF3Acu91g9+6fkA4sB7o7FfeAlgNbAI+9isvBoz19lkA1PJb18fbfiNwn195\nKLDQW/cdUOQc8efcU0qMyaKhy4ZqiTv76t7seSJpvvbrr6pXXXX2/ZGTRzJ9jK5dzz521mQNaTyE\nKSM1jRFAl1TKP1TVFt5rBoCINALuABoBNwJfyNleqsHAg6paH6gvIonHfBA4rKr1gI+BAd6xgoD/\nA1oDbYHXRKSct897wEDvWFHeMYzJd7YfjuT0oepUqhToSAKvRQt3M2CC132ReJNeekaOhDfecA9K\n+usvuP32HAzSpJ80VPVP4Egqq1K7x/IWYKyqxqvqNlztoY2IBANlVHWJt90o4Fa/fUZ6yxOBjt5y\nF2CmqkarahQwE7jBW9cRmOQtjwT+kd51GJMXhe+LpHzhahSyhmKCgtwDptavz/g+4eHuWeNxcbB3\nLwwe7KY0NzknK/9UnxCRlSLylV8NoDqw02+bSK+sOq45K9EuryzJPqqaAESLSIW0jiUiFYEjqurz\nO1a1LFyHMQGz48huqlx0YQ+39de1q5t2JKM+/9w9MfDNN+Gjj9xzMkzOOt+k8QVwiao2A/YCA7Mv\npFRrMOezjTF53u5jkdQsZ0kj0TPPwLBhEBOT/rbHjsHo0fCvf+V8XOas8xpyq6oH/N4OBX7yliOB\nmn7ranhlaZX777NbRAoDZVX1sIhEAmHJ9vldVQ+JSDkRKeTVNvyPlar+/fufWQ4LCyPsQno6vMnT\nDsZGcmNlqygnCg2Fzp3dJIPPP3/ubUePhg4dICTk3NuZjJkzZw5z5sxJf8PUeseTv3Cjldb4vQ/2\nW/438K233BhYgRsRVRvYDIi3biHQBldLmIY34gp4DPjCW+6F6xMBCAK2AOX8lst768YBd3rLg4FH\nzxF79g4pMCabnIo7pYVeK6offhQf6FDylGXLVGvUUI2NTXsbn0+1cWPV337LvbguNKQxeirdmoaI\nfIv7xV9RRHbghtteKyLNAB+wDXjE+3ZeJyLjgXVAHPCYd3KAx4GvgRLANPVGXOGG9I4WkXDgkJc4\nUNUjIvImsBRQ4HV1HeIALwFjvfUrvGMYk6/sPbaX4nFVqFWzcKBDyVNatIAGDdwTAGvVgsmToWxZ\n6NULLrvMdXh/9517lro1GuQ+OfudXjCJiBb0azT50187/6LzwGeZfddCe2pcMrNmuWaqNm3ck/0O\nH3ZP1zt50o2UCgtzTwK88spAR1pwiQiqmqL/2KYRMSZAImMiiY+qRo0agY4k77n+eveI2PJ+t2q8\n+y5s2+ZqH4WtchYwljSMyQWqmmI21h1RkcQdrE5wcBo7XeDKJ7u3T8RNEWICy24pMiaH9fu1Hw/+\nmHLSgvC9uymt1e1Xs8lXLGkYk4OW71nO8JXDmbxhMjujdyZZt/VgJJVK2D0aJn+xpGFMDon3xfPP\nn/7Jm9e8x12N7ueTRZ8kWb8rOpJqZeweDZO/WNIwJocMWjyIMsXLMOO9Pqz9yj3GNCb27K3OB05F\nUrui1TRM/mJJw5gcEBsfy+tzX+fWIkNYv05YvzCE9pU689XyrwDXMR7l2039qpY0TP5iScOYHLDu\nwDqCS1bnvf80YNgweOghKL3mOT5e+DHHTx8nOjYafIWoW7NMoEM1JlNsyK0xOWDl3pXEbm/G7bfD\nFVdAzZpw+eWt6DGsKw0GNeCB5g9Q5GR1u0fD5DtW0zAmByzYtoLdy5rz9tvufc2a0LEjNN89mAm3\nT2DW1llwuI4lDZPv2DQixuSAyz68hkJ/vMaqHzqdKZs7Fx59FNatg/h4pWTZ0xyPLk6xYgEM1Jg0\npDWNiNU0jMlmPvURfnQVV9VplqT8mmsgOBhuvhlWrRIuLm8Jw+Q/ljSMyWYRRyIodLocV7eqmKRc\nBH75xc3iGhbmmqyMyW+sI9yYbLZy70rY24yW96dcV6wYvPEGdOsGO3bkemjGZJklDWOy2V9bV+Lb\n3Zw6ddLepk0b9zImv7HmKWOy2Z9bVlC/TDMK2f9dpgCyf9bGZLMNUStpf0mz9Dc0Jh+ypGHytLg4\n9zCe/OLA8QOciD9Gx+ahgQ7FmBxhScPkaU88AU2bwq5dgY4kY1buXUmhA81o3TrF8HZjCgRLGiag\nIiLg3nshKirluhkz3OvBB6FLF/ec6Lzuj/CVyN5m9oQ5U2BZ0jABExPjbnTbvBluvRVOnTq7LioK\nHn4Yhg2D/v3hxhuhe3c4cSJg4WbID39PpX6JqxGraJgCypKGCYiEBLj7brjqKvjrL6hSxdU4jh+H\npUtd7aJ7d7juOrf9gAEQGgq9ekF8fEBDT9Pa/WvZdmwTN9TuHuhQjMkxljRMQLzxhqs1fPYZFCoE\no0a52kWFCi5hVKwI7713dvtChWD4cDh92s3flDidWEzM2eVA+3zxFxRd/U9u6VY00KEYk2NswkKT\n644ehZAQWLkSatU6W+7zudFSxYunve+xY2622IoVITIS1q93zVhffJHzcZ9LTGwM1d8Ppe7MtSyf\nW82ap0y+ZxMWmjxj1Cj3xe+fMMDVJs6VMABKl4Zp01xfyFdfwd69bj6nSZNyLt6MGLVqFCV2X0e/\nJyxhmILNahomx6ly5otUFRo3hsGD3aR92WHJEujaFRYvdv0euU1VqfPhpRwfP5jI+R0oYpPzmALA\nahomIHw+uPxyePdd9372bChSBDp0yL5ztG4NL77oOtZPn86+42bUT5t+4sjBorxwxzWWMEyBZzUN\nk6PmznV9DkWLumG1a9fCTTfBI49k73l8Pnf80FD49NPsPfa5xCXE0fDTy9g/+iMi59xI2bK5d25j\ncpLVNExAfP21SxBz58L06TBvnhtam1Hj1o7jjgl3sPnw5lTXR8ZEcuz0sTMjsKZPh9Gj3TrVnL+T\nfOjyr4jaUYNXe91gCcNcEKymYXLMsWPuQUMbNrj7MKKj3XLbthnbf8WeFXQe05mHmj/E0OVDeajF\nQ9zV5C4aVWpE1Kko3pj7BmNWj6FciXIMvXkonet0Zu1auPZauPNO12G+fbtLWFddlf3XdzT2KLU+\nqE/FGdNY/1tzitpIW1OApFXTsKRhcsyIEfDDD/Djj+feTlWRZEOODp04RKuhrXjvuve449I72H10\nN2/OfZN5O+YRcSSCYoWLcX+z+/nvNf9l+Z7lPPzTw9xY90YG3TSI32cXYf58+Mc/YMEC+Pln98oO\nq/as4c3f3ic4qBxbD21nzi/lmfnoqBxJSsYEkiUNk+s6dIBnnnFf3mmZvXU2Pcb34K4md/Fs+2ep\nWroqc7bNYcBfA2hXvR3vd34/xT4n405yPO44F5e8+ExZTGwMPcf3pHb52gzpNgQRIfpUNB/O/5Qv\n+z7LzJ9L0bRp1q7nVPwpqr/ekpjF/+AirUTJoBg6lv0n3w6tkrUDG5MHWdIwuWrLFmjf3vUpFCuW\n+jY7o3fS5qs2fHLDJ6zdv5YhS4dwMv4kbau35aZ6N/FU26coUijjw5GOxh6lw9cduLXhrXRv0J3b\nJ9zOybiTXH7yacqv+w/ffJO1a+ox+AV+WbyVnQMnEB0tLFsGnTtjfRmmQLKkYXKNzwe33OKG2r71\nVurbxMbHcs3X13Bbo9t44coXAPdL3qc+ShYted7n3ntsL1cMu4KY2BgG3TSISytdynWjrid+4BaW\n/FWKSy45v+NOXvYXt427jSk3rqbbtZXOOz5j8gtLGibXvPWWm9L8t9/SrmW8MOsFNh/ezKQ7JqXo\nz8iqXTG7iEuIo3aQm5+85/ieRK1pz9ZvnqNYMTfH1XffuQ7zjNgQuZtmn15Fj9ID+fbVc7S1GVOA\nWNIwuWLmTOjb192lXa1a6tvEJcRRdWBVlv1zGSHlQ3I8ptX7VtNldBdGttxCzeCSzJ/vhgL/8QdJ\npvyIi4OtW93UJC1builL5q/aS8dRYbQs3Jc/3nmRwoVzPFxj8oTzvk9DRIaJyD4RWe1XFiQiM0Vk\no4j8IiLl/Nb1E5FwEVkvIp39yluIyGoR2SQiH/uVFxORsd4+C0Sklt+6Pt72G0XkPr/yUBFZ6K37\nTkTsPtw8ICYG7rsPvv027YQB8OvWX6lfsX6uJAyAplWackWtK/jyQG9eW3sHQ3yt2J6wkLlz3XpV\nN7Nu6YujuOaxsdz59VNUvOUdmvQaS4fhHbmxem/+GmAJwxjIQE1DRK4CjgGjVLWpV/YecEhVB4jI\ni0CQqr4kIo2Bb4DWQA3gV6CeqqqILAKeUNUlIjIN+ERVfxGRfwGXqepjInIn8A9V7SUiQcBSoAUg\nwDKghapGi8g4YKKqThCRwcBKVf0yjfitppFLBgyAVatIt8O5z+Q+tKzakqfaPpU7gQHborYxYsUI\nGlzcgN1Hd/PF3AnUnr2Q2b8K778PH655geONhnB1yNV0COnA7qiDLA7fQtvqV/LR7c/mWpzG5BVp\n1TRQ1XRfQAiw2u/9BqCKtxwMbPCWXwJe9NtuOtDW22adX3kvYLC3PANo6y0XBvYn38Z7Pxi401s+\nABTyltsBM84Ru5qcd+KEanCw6urVKdcdPH5QfT6fqqqejDup5d8tr5Exkbkc4VkJvgRtNri5Xtxh\nvL75pmr5tlO05gehevjE4YDFZExe4313pvhOPd9pRCqr6j7vG3kvUNkrrw7s9Nsu0iurDvhP6LDL\nK0uyj6omANEiUiGtY4lIReCIqvr8jnWOxhCTG4YPhzZt4LLLkpb71MflQy7nld9eAWDG5hk0C25G\ntTKB+5MVkkJ80Pl95LqXeW3gLgrd8gjf9BxF0EVBAYvJmPwiu/oCsrP9JyNDaeyJBXlIXJxrmho3\nLuW6BTsXUKpYKSasm0CdoDrM2jqLXpf2yv0gk+l0SSeah9Rh+YtteKjV/VwdcnWgQzImXzjfpLFP\nRKqo6j4RCQb2e+WRQE2/7Wp4ZWmV+++zW0QKA2VV9bCIRAJhyfb5XVUPiUg5ESnk1Tb8j5Wq/v37\nn1kOCwsjLLse5GAAN3y1bl1o1y7luonrJnJ3k7u567K7uHrE1ZyIO8GgmwblfpCpGNjlA/rP6c/r\n174e6FCMCbg5c+YwZ86c9DdMrc0q+QsIBdb4vX8Pr+8CeBF411tuDKwAigG1gc2c7WxfCLTB1RKm\nATd45Y8BX+jZfoyx3nIQsAUo57dc3ls3jrP9G4OBR88Re841+hlVVX3gAdUhQ1KWJ/gStMaHNXTt\nvrWqqjpv2zx9adZLuRydMeZ8kEafRro1DRH5FveLv6KI7ABeA94FJojIA8B24A7v23mdiIwH1gFx\nwGPeyQEeB74GSgDTVHWGVz4MGC0i4cAhL3GgqkdE5E3cCCoFXlfVKG+fl4Cx3voV3jFMgEREQK9U\nWpyWRC6hdLHSNK7UGICrQ662ZiBj8jm7uc9kWe3aMGuWa6Ly98KsFyheuDhvdnwzMIEZY86bPYTJ\n5Ii4ONi9G2rVSlquqkxcN5GejXsGJjBjTI6wpGGyZOdOCA5OOcfUir0rKCSFaFoli/ORG2PyFEsa\nJksiIlzzlL9T8ad4fNrjPNb6sWyfjNAYE1iWNEyWJE8aqsq/pv6LGmVr8O92/w5cYMaYHGET/Zks\nSZ40Pl30Kcv3LOevB/6yWoYxBZDVNEyWbN3KmQcbLY5czP/78/8xpdcUShUrFdjAjDE5wpKGyZLE\nmsbx08e59/t7GXTjIELLhwY6LGNMDrH7NEyWVKkCK1bA2yseJ+Z0DKP/MTrQIRljskFa92lYn4Y5\nb8ePuwcvrTkxi5/Df2bVo6sCHZIxJodZ85Q5b9u2QUgIjP97LC9e+SLlS5QPdEjGmBxmScOct61b\nXX/GpsObzswvZYwp2CxpmPMWEeFGTm06tIn6FesHOhxjTC6wpGHOW0QEBIdGcSLuBFVLVw10OMaY\nXGBJw5y3iAgoFhxO/Yr17UY+Yy4QljTMeYuIgLhyG61pypgLiA25NedF1XWERxfdRP0yljSMuVBY\nTcOcl0OHoHBh2HncOsGNuZBY0jDnZeVKaNrURk4Zc6GxpGHOy+LF0LqNsunQJupVrBfocIwxucSS\nhjkvixdDveZ7KFWslN0JbswFxJKGyTRVWLQIytexpiljLjSWNEymRUZCQgJEF9lE/QqWNIy5kFjS\nMJm2eDG0aQPhhzfR4OIGgQ7HGJOLLGmYTEtMGjZyypgLjyUNk2mJSWPjIbsb3JgLjSUNkykJCbB0\nKTRrEcf2qO3UCaoT6JCMMbnIkobJlI0boXJlOCKbqVG2BsWLFA90SMaYXGRJw2RKYtPUsj3LaFmt\nZaDDMcbkMksaJlMSk8bS3UtpVbVVoMMxxuQySxomw2Jj4YcfoHNnL2lUs6RhzIXGkobJsPHjoUkT\nqN8wnpV7V9KiaotAh2SMyWWWNEyGqMInn8DTT8OGgxuoXrY65UqUC3RYxphcZknDZMhff0F0NNx0\nkzVNGXMhs6RhMuSTT+Cpp6BQIVi2exktq9rIKWMuRJY0TLp27oTZs+H++937pXuspmHMhcqShknX\nrFlwww1QpgzEJcSxet9qmgc3D3RYxpgAyFLSEJFtIrJKRFaIyGKvLEhEZorIRhH5RUTK+W3fT0TC\nRWS9iHT2K28hIqtFZJOIfOxXXkxExnr7LBCRWn7r+njbbxSR+7JyHebclixx92YArDuwjpByIZQp\nXiawQRljAiKrNQ0fEKaqzVXV+1rhJeBXVW0A/Ab0AxCRxsAdQCPgRuALERFvn8HAg6paH6gvIl28\n8geBw6paD/gYGOAdKwj4P6A10BZ4zT85mey1ZAm0bu2WrRPcmAtbVpOGpHKMW4CR3vJI4FZvuTsw\nVlXjVXUbEA60EZFgoIyqLvG2G+W3j/+xJgIdveUuwExVjVbVKGAmcEMWr8WkIjYW1q2DZs3ce0sa\nxlzYspo0FJglIktE5CGvrIqq7gNQ1b1AZa+8OrDTb99Ir6w6sMuvfJdXlmQfVU0AokWkwjmOZbLZ\n6tVQrx6ULAk+9TF983Q6hHQIdFjGmAApksX9r1TVPSJSCZgpIhtxicRf8vdZIelvklL//v3PLIeF\nhREWFpZN4RR8/k1TC3YuoGTRkjSt0jSwQRljst2cOXOYM2dOuttlKWmo6h7vvwdEZDLQBtgnIlVU\ndZ/X9LTf2zwSqOm3ew2vLK1y/312i0hhoKyqHhaRSCAs2T6/pxWnf9IwmbNkCbRr55a/W/sdd192\nN2e7oowxBUXyH9Svv/56qtudd/OUiJQUkdLecimgM7AG+BG439usDzDFW/4R6OWNiKoN1AUWe01Y\n0SLSxusYvy/ZPn285dtxHesAvwDXi0g5r1P8eq/MZLPEmka8L54J6ybQq0mvQIdkjAmgrNQ0qgA/\niIh6x/lGVWeKyFJgvIg8AGzHjZhCVdeJyHhgHRAHPKaqiU1XjwNfAyWAaao6wysfBowWkXDgENDL\nO9YREXkTWIpr/nrd6xA32ejYMYiIcJMUzt46m9DyodStUDfQYRljAkjOfm8XTCKiBf0ac8off8Dz\nz8OiRXD/5PtpFtyMZ9o9E+iwjDG5QERQ1RRt0XZHuElTYtPUybiTTNk4hTsvvTPQIRljAsyShklT\nYtL4Y8cfNKnchKplqgY6JGNMgFnSMKmaOhVmzoSrroJNhzbRpFKTQIdkjMkDLGmYJOLi4MUX4dFH\n4ccfoU4dCD8UTr2K9QIdmjEmD8jqzX2mgHn5ZVi2DJYvh0qVXNnmI5vpdEmnwAZmjMkTLGmYMzZs\ngK+/hr//PpswADYf3mxDbY0xgDVPGY+qe/73K69A5cpny+N98WyP2s4lQZcELjhjTJ5hScMArv9i\n5054/PGk5Tujd1K5VGVKFCkRmMCMMXmKNU9d4Hw+mDYNnnwShg2DokWTrg8/bJ3gxpizLGlcoBIS\nYPRoePddKFUKPvgArr8+5XabD2+mbpD1ZxhjHEsaF6Dp0+GFF6B8eRgyBDp0gLQmrrVOcGOMP0sa\nF5DTp+Gpp2D2bBg4EG6+Oe1kkWjz4c1cXevq3AnQGJPnWUd4PnHyJMyYkf52admzBzp2dP9dtgy6\nd08/YYD1aRhjkrKkkU8MHw7durmpyjMiPh6++MI9QKlKFbjkErjuOvjhByhbNmPHSPAlEHEkwobb\nGmPOsKnR8wGfDxo3hurVoUEDlwzSoupGQ/3nP1C1qrvDu1EjCA6GQpn8ibA9ajtXDr+SXc/uSn9j\nY0yBktbU6NankQ/MnAkXXQTffQcNG8Krr7qEoOqedVG4MFSo4JYHDHAjo957z9VMsvJkVusEN8Yk\nZ0kjDxoxAv78EwYNcsni009dB3blytC7N3z0Ebz9NjzxBPzyC1SsCIcPQ2ioK7/ppqwli0SWNIwx\nyVnSyEN8PtecNHEiNGvm7pt4/33Xcf39926b559365Yvh2LFYM0aKFMmZ+IJPxxOvQrWCW6MOcuS\nRi7z+WDePJg8Gdavh02bXKd17dquWalwYVi40DU3vfgiXHON+28JbxaPmjWhb183hfnAgVAkB/+C\nmw9vpn2N9jl3AmNMvmMd4blk7VoYMwa+/RaCguDOO12NoX59N3VHRATs3w+33ALFi5/db9IkuPZa\nl0Ry06ETh7hs8GXM7D2TJpXtAUzGXGjS6gi3pJED4uOhf39Yt84tb9sGR47APfe412WX5Wo4mXY0\n9iidRnWiY+2OvHvdu4EOxxgTAJY0csmpU3DXXe5mvIcfds1HlSq5+yUyO+Q1EE7Fn+Kmb26iXoV6\nDOk2BMmOHnVjTL5jSSMHJCS4u7THjnUjm5o0cU1QF1/sJgMsVixHTptj4n3x9Bzfk+JFivNtj28p\nXFFlU6YAAAsvSURBVKhwoEMyxgSIJY1scOCAG9108qSrNfz5pxvuev/9cOyY67eoWRPefNN1aOcn\nPvXxwJQH2Hd8H1N6TaFY4XyW8Ywx2cqSRhadOAGdOsHll8NVV7laRuPG0Lp1NgQZYFGnonhl9ius\n3LeSmffOpFSxUoEOyRgTYJY0siAhAW67zd0PMWpU9tw4dz5OxJ2gZNGS2XKsiCMRzI6YzZSNU5i3\nfR7XX3I9Q28eStBFQdlyfGNM/mZJIxNOn3b3UfzyC0RHw44dbpK/adMC10/xzepveGrGU/z92N8E\nlw4+r2PExMYwZOkQvlz2JcdOH6NT7U7cVO8mujfoTtniGZzF0BhzQbCkcQ7Hj7v+ic2b3TDZiRPh\n0kuhZ0/XqV22rLvJrmT2/MjPtH3H9tF0SFOurnU1ijLpjknn3D4yJpK/D/xN+KFwIo9Gcir+FDGx\nMUzeMJnr61zPc+2fo2XVljYyyhiTJksaqVCFb76Bl16COnVcH0Xduu7hRPXrp9z+0IlDTFg3gU61\nO53zGROx8bF8uuhTqpSuwi0NbqFciXKAG5105OQRjpw6cua/UaeiKF+iPO1rtKdciXLsiN7B+L/H\nExMbw7Ptn6V8ifLcOfFOQsuF8vq1r9P8y+a8ee2b9Gzck1V7V/HFki8oV6IcIeVCXCf2xilExkTS\ntEpT6lesT82yNbmo6EWUKFKCznU621xSxpgMuaCTRtTJKMoWL8ufO/7krV8/Zte+k1Q+fCv7Fnfg\nRKV5VAobx7FCkbSr0Y521duRoAnsProbVaVb/W60rdGWqZum8ujUR2lZtSWLIxcTUj6EllVbkuBL\nQEToVLsTXet3ZWf0Tu6adBdVy1SlSKEi/B7xO40qNWLvsb3sObqHssXLEnRREOVLlCeoRBBBFwWx\n79g+lu5eSpXSVYg6FUWPhj3wqY+p4VO5rdFtzNo6i1WPruKiohexYOcCeozvwQ11b2B6+HSebvs0\nANujt1O2eFm6N+hO+xrtbbisMSZLLuikUfadslS+qCoHDvqI//PftG1agSOVp7Cj0FyurXMlvZrc\nySVBl7Bg1wIWRy6mRJESVCtTjdj4WCZvnMz+4/spU6wMI24ZQYfQDsT74pm9dTbhh8MpWqgop+JP\n8XP4zyyJXEKRQkV4q+NbPNLyEUSE6FPRrN63muplq1OjbI00h7KeTjjNhoMb/n979x9rdV3Hcfz5\nQlQKGpCWd4nMmDSKSlFAJpQrFak2remaNPuha66tgnIiMt3A1iKdK91atSVsWjFdLsM1J9qClYlB\n8fvGryg0SKDWFakmCb374/MBvxD3es7lwPdzDq/Hdsf3fL7fc/d57Xzv58331+cw5uwxh7dZs2sN\n85bNY9Zls5g8cvLhbef/ej579+9lzpQ5h49izMxa6ZQuGueOepme07u55aOTuOvOAZx1VnO/Y9s/\nttE1pOsNb0Xd86897D+wn/OGnnccPTYzq98pXTS2bw+GD2/8a07NzE51p3TR6PSMZmat1lvRaIMp\n9MzMrBRtXTQkTZO0SdIWSbPr7o+ZWadr26IhaQDwHeBqYCwwXdKYent1Yi1btqzuLrRUJ+XppCzQ\nWXk6KQvUn6dtiwYwEdgaES9ExGvAI8C1NffphKp7Z2m1TsrTSVmgs/J0UhaoP087F41zgb9UXu/I\nbWZmdoK0c9EwM7OTrG1vuZU0CZgXEdPy6zuAiIh7jtquPQOamdWso57TkHQasBm4AngJWAFMj4iN\ntXbMzKyDDay7A/0VEQclfQl4mnSabYELhpnZidW2RxpmZnbytd2FcEkLJO2WtK7SNkHSCkmr87/j\nc/uZkhZJWiepO1/3OPSei3P7Fkn315El9+NYed4v6TlJayUtljSksm6OpK2SNkqaWmmvPU8zWSRd\nKel3uX2lpA+VlCX3o6nPJq8fKWmfpFsrbbXn6cd+dmjdhrz+jFKy5H40s68VPQ5IGiHpl7lv6yXN\nyO3DJT0tabOkJZKGVt5T3zgQEW31A0wBLgLWVdqWAlPz8keApXn5s8CivPwm4M/AyPz6t8CEvPwk\ncHVBeVYAU/Ly54Cv5eX3AKtJpxXPB/7I60eLtedpMsuFQFdeHgvsqLyn9izN5qms/wnwKHBrSXma\n/GxOA9YC782vh5e0n/UjT9HjANAFXJSXh5Cu1Y4B7gFuz+2zgW/m5VrHgbY70oiIZ4Geo5pfAg5V\n4WHAzry8CxicL5q/GdgPvCKpC3hLRKzM2z0MfPyEdrwXveQZndsBfgFcl5evAR6JiAMRsR3YCkws\nJU8zWSJibUTsysvdwCBJp5eSJfermc8GSdcCfwK6K21F5Gkyy1RgbURsyO/tiYgoJUvuUzN5ih4H\nImJXRKzJy/8ENgIjSA8rP5Q3e6jSt1rHgbYrGr24A/iWpBeBe4E5ABGxBHiFVFS2A/dFxMukhwB3\nVN5f2oOB3ZKuycufJO1A8P8PNO7MbSXn6S3LYZKuB1ZFerK/5CzQS558KuR24G6geptiyXl6+2ze\nBSDpqXwKcVZuLzkL9JKnncYBSeeTjqCeB86JiN2QCgvw9rxZreNApxSNBcCXI2Ik8FVgIYCkG0mH\no13AKOC2/KGU7mbgi5JWAoOB/9Tcn+PRZxZJY4H5wC019K0/esszF/h2RPy7tp41r7csA4HJwHTg\nA8AnqtecCnbMPO0yDuT/eDwGzMxHHEffpVTEXUtte8vtUS6NiKsAIuIxSQ/m9suAxyPiv8DfJP0G\nGA88C1S/Xm8Er5/Sql1EbCFNxIik0cDH8qqdHLvfvbXXro8sSBoB/BT4dD7MhoKzQJ95LgWuk3Qv\n6RrAQUmvkvIVmaePLDuAX0VET173JHAx8GMKzQJ95il+HJA0kFQwfhgRi3PzbknnRMTufOppT26v\ndRxo1yMNceQpgK2SLgeQdAXpHB/AJtLDf0gaDEwCNuZDvb2SJkoS8BlgMfU5Io+kt+V/BwB3Ad/P\nq54AbpB0hqR3AhcAKwrL01AWScOAnwOzI+L5Q9sXlgUazBMRH4yIURExCrgf+EZEfLewPI3uZ0uA\n90kalAezy4HuwrLAG+f5Xl7VDuPAQuAPEfFApe0J0gV9SBfzF1fa6xsHTvadAsf7AywC/kq6mPUi\ncBNwCemugdXAcmBc3vZM4EfAemADR97Rcklu3wo8UFieGaQ7KDaRBp/q9nNId0tsJN8xVkqeZrIA\ndwL7gFX5c1sFnF1Klv58NpX3zS1tX+vHfvap/DezDphfUpZ+7GtFjwOkU4EHgTWVv4VpwFtJF/Q3\nkx5iHlZ5T23jgB/uMzOzhrXr6SkzM6uBi4aZmTXMRcPMzBrmomFmZg1z0TAzs4a5aJiZWcNcNMzM\nrGEuGmaFy084mxXBO6NZC0m6W9LMyuuvS5oh6TalLwhbI2luZf3jSl9CtV7S5yvt+yTdJ2k1adoL\nsyK4aJi11kLSnD/k+X9uIE3JPToiJgLjgPGSpuTtb4qICcAEYKak4bl9MLA8IsZFxHMnNYFZHzpl\nlluzIkTEC5L+LulC0lTcq4CJwFWSVpEm2BsMjCbNsvoVSYe+KGdEbl8BHCDNkGtWFBcNs9Z7kDSB\nXhfpyONK0qR/P6hulGdm/jBpav/9kpYCg/LqV8MTw1mBfHrKrPV+RpqldDxpmvElwM15Wm4kvSNP\n4z0U6MkFYwxHXrsQZgXykYZZi0XEa/mooScfLTyTi8LydJmDfcCNwFPAFyR1k6a/Xl79NSe522YN\n8dToZi2Wb5H9PXB9RGyruz9mreTTU2YtJOndpC/AecYFwzqRjzTMzKxhPtIwM7OGuWiYmVnDXDTM\nzKxhLhpmZtYwFw0zM2uYi4aZmTXsf9SYqMbN9xPrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14a281390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_births.plot(title='Total births by sex and year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.077643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.028618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.019188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.017342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.016177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.015540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.012704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.009429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690754</th>\n",
       "      <td>Zaviyon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690755</th>\n",
       "      <td>Zaybrien</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690756</th>\n",
       "      <td>Zayshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690757</th>\n",
       "      <td>Zayyan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690758</th>\n",
       "      <td>Zeal</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690759</th>\n",
       "      <td>Zealan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690760</th>\n",
       "      <td>Zecharia</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690761</th>\n",
       "      <td>Zeferino</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690762</th>\n",
       "      <td>Zekariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690763</th>\n",
       "      <td>Zeki</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690764</th>\n",
       "      <td>Zeriah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690765</th>\n",
       "      <td>Zeshan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690766</th>\n",
       "      <td>Zhyier</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690767</th>\n",
       "      <td>Zildjian</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690768</th>\n",
       "      <td>Zinn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690769</th>\n",
       "      <td>Zishan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690770</th>\n",
       "      <td>Ziven</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690771</th>\n",
       "      <td>Zmari</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690772</th>\n",
       "      <td>Zoren</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690773</th>\n",
       "      <td>Zuhaib</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690774</th>\n",
       "      <td>Zyeire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690775</th>\n",
       "      <td>Zygmunt</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690776</th>\n",
       "      <td>Zykerion</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690777</th>\n",
       "      <td>Zylar</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690778</th>\n",
       "      <td>Zylin</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690779</th>\n",
       "      <td>Zymaire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690780</th>\n",
       "      <td>Zyonne</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690781</th>\n",
       "      <td>Zyquarius</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690782</th>\n",
       "      <td>Zyran</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690783</th>\n",
       "      <td>Zzyzx</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1690784 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name sex  births  year      prop\n",
       "0             Mary   F    7065  1880  0.077643\n",
       "1             Anna   F    2604  1880  0.028618\n",
       "2             Emma   F    2003  1880  0.022013\n",
       "3        Elizabeth   F    1939  1880  0.021309\n",
       "4           Minnie   F    1746  1880  0.019188\n",
       "5         Margaret   F    1578  1880  0.017342\n",
       "6              Ida   F    1472  1880  0.016177\n",
       "7            Alice   F    1414  1880  0.015540\n",
       "8           Bertha   F    1320  1880  0.014507\n",
       "9            Sarah   F    1288  1880  0.014155\n",
       "10           Annie   F    1258  1880  0.013825\n",
       "11           Clara   F    1226  1880  0.013474\n",
       "12            Ella   F    1156  1880  0.012704\n",
       "13        Florence   F    1063  1880  0.011682\n",
       "14            Cora   F    1045  1880  0.011484\n",
       "15          Martha   F    1040  1880  0.011429\n",
       "16           Laura   F    1012  1880  0.011122\n",
       "17          Nellie   F     995  1880  0.010935\n",
       "18           Grace   F     982  1880  0.010792\n",
       "19          Carrie   F     949  1880  0.010429\n",
       "20           Maude   F     858  1880  0.009429\n",
       "21           Mabel   F     808  1880  0.008880\n",
       "22          Bessie   F     794  1880  0.008726\n",
       "23          Jennie   F     793  1880  0.008715\n",
       "24        Gertrude   F     787  1880  0.008649\n",
       "25           Julia   F     783  1880  0.008605\n",
       "26          Hattie   F     769  1880  0.008451\n",
       "27           Edith   F     768  1880  0.008440\n",
       "28          Mattie   F     704  1880  0.007737\n",
       "29            Rose   F     700  1880  0.007693\n",
       "...            ...  ..     ...   ...       ...\n",
       "1690754    Zaviyon   M       5  2010  0.000003\n",
       "1690755   Zaybrien   M       5  2010  0.000003\n",
       "1690756   Zayshawn   M       5  2010  0.000003\n",
       "1690757     Zayyan   M       5  2010  0.000003\n",
       "1690758       Zeal   M       5  2010  0.000003\n",
       "1690759     Zealan   M       5  2010  0.000003\n",
       "1690760   Zecharia   M       5  2010  0.000003\n",
       "1690761   Zeferino   M       5  2010  0.000003\n",
       "1690762   Zekariah   M       5  2010  0.000003\n",
       "1690763       Zeki   M       5  2010  0.000003\n",
       "1690764     Zeriah   M       5  2010  0.000003\n",
       "1690765     Zeshan   M       5  2010  0.000003\n",
       "1690766     Zhyier   M       5  2010  0.000003\n",
       "1690767   Zildjian   M       5  2010  0.000003\n",
       "1690768       Zinn   M       5  2010  0.000003\n",
       "1690769     Zishan   M       5  2010  0.000003\n",
       "1690770      Ziven   M       5  2010  0.000003\n",
       "1690771      Zmari   M       5  2010  0.000003\n",
       "1690772      Zoren   M       5  2010  0.000003\n",
       "1690773     Zuhaib   M       5  2010  0.000003\n",
       "1690774     Zyeire   M       5  2010  0.000003\n",
       "1690775    Zygmunt   M       5  2010  0.000003\n",
       "1690776   Zykerion   M       5  2010  0.000003\n",
       "1690777      Zylar   M       5  2010  0.000003\n",
       "1690778      Zylin   M       5  2010  0.000003\n",
       "1690779    Zymaire   M       5  2010  0.000003\n",
       "1690780     Zyonne   M       5  2010  0.000003\n",
       "1690781  Zyquarius   M       5  2010  0.000003\n",
       "1690782      Zyran   M       5  2010  0.000003\n",
       "1690783      Zzyzx   M       5  2010  0.000003\n",
       "\n",
       "[1690784 rows x 5 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prop追加 ある名前の数/出生数で名前の珍しさの指標とする\n",
    "def add_prop(group):\n",
    "    births = group.births.astype(float)\n",
    "    group['prop'] = births / births.sum()\n",
    "    return group\n",
    "\n",
    "names = names.groupby(['year', 'sex']).apply(add_prop)\n",
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ある年、ある性別のpropの和が1であること\n",
    "np.allclose(names.groupby(['year','sex']).prop.sum(),1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</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 rowspan=\"30\" valign=\"top\">1880</th>\n",
       "      <th rowspan=\"30\" valign=\"top\">F</th>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.077643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.028618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.019188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.017342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.016177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.015540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.012704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.009429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2010</th>\n",
       "      <th rowspan=\"30\" valign=\"top\">M</th>\n",
       "      <th>1677617</th>\n",
       "      <td>Yair</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677616</th>\n",
       "      <td>Talan</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677614</th>\n",
       "      <td>Keyon</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677613</th>\n",
       "      <td>Kael</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677618</th>\n",
       "      <td>Demarion</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677619</th>\n",
       "      <td>Gibson</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677620</th>\n",
       "      <td>Reagan</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677621</th>\n",
       "      <td>Cristofer</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677622</th>\n",
       "      <td>Daylen</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677623</th>\n",
       "      <td>Jordon</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677624</th>\n",
       "      <td>Dashawn</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677625</th>\n",
       "      <td>Masen</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677629</th>\n",
       "      <td>Rowen</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677631</th>\n",
       "      <td>Yousef</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677630</th>\n",
       "      <td>Thaddeus</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677628</th>\n",
       "      <td>Kadin</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677627</th>\n",
       "      <td>Dillan</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677626</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677634</th>\n",
       "      <td>Slade</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677632</th>\n",
       "      <td>Clinton</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677633</th>\n",
       "      <td>Sheldon</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677636</th>\n",
       "      <td>Keshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677637</th>\n",
       "      <td>Menachem</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677635</th>\n",
       "      <td>Joziah</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677638</th>\n",
       "      <td>Bailey</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677639</th>\n",
       "      <td>Camilo</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677640</th>\n",
       "      <td>Destin</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677641</th>\n",
       "      <td>Jaquan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677642</th>\n",
       "      <td>Jaydan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677645</th>\n",
       "      <td>Maxton</td>\n",
       "      <td>M</td>\n",
       "      <td>193</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>261877 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name sex  births  year      prop\n",
       "year sex                                               \n",
       "1880 F   0             Mary   F    7065  1880  0.077643\n",
       "         1             Anna   F    2604  1880  0.028618\n",
       "         2             Emma   F    2003  1880  0.022013\n",
       "         3        Elizabeth   F    1939  1880  0.021309\n",
       "         4           Minnie   F    1746  1880  0.019188\n",
       "         5         Margaret   F    1578  1880  0.017342\n",
       "         6              Ida   F    1472  1880  0.016177\n",
       "         7            Alice   F    1414  1880  0.015540\n",
       "         8           Bertha   F    1320  1880  0.014507\n",
       "         9            Sarah   F    1288  1880  0.014155\n",
       "         10           Annie   F    1258  1880  0.013825\n",
       "         11           Clara   F    1226  1880  0.013474\n",
       "         12            Ella   F    1156  1880  0.012704\n",
       "         13        Florence   F    1063  1880  0.011682\n",
       "         14            Cora   F    1045  1880  0.011484\n",
       "         15          Martha   F    1040  1880  0.011429\n",
       "         16           Laura   F    1012  1880  0.011122\n",
       "         17          Nellie   F     995  1880  0.010935\n",
       "         18           Grace   F     982  1880  0.010792\n",
       "         19          Carrie   F     949  1880  0.010429\n",
       "         20           Maude   F     858  1880  0.009429\n",
       "         21           Mabel   F     808  1880  0.008880\n",
       "         22          Bessie   F     794  1880  0.008726\n",
       "         23          Jennie   F     793  1880  0.008715\n",
       "         24        Gertrude   F     787  1880  0.008649\n",
       "         25           Julia   F     783  1880  0.008605\n",
       "         26          Hattie   F     769  1880  0.008451\n",
       "         27           Edith   F     768  1880  0.008440\n",
       "         28          Mattie   F     704  1880  0.007737\n",
       "         29            Rose   F     700  1880  0.007693\n",
       "...                     ...  ..     ...   ...       ...\n",
       "2010 M   1677617       Yair   M     201  2010  0.000106\n",
       "         1677616      Talan   M     201  2010  0.000106\n",
       "         1677614      Keyon   M     201  2010  0.000106\n",
       "         1677613       Kael   M     201  2010  0.000106\n",
       "         1677618   Demarion   M     200  2010  0.000105\n",
       "         1677619     Gibson   M     200  2010  0.000105\n",
       "         1677620     Reagan   M     200  2010  0.000105\n",
       "         1677621  Cristofer   M     199  2010  0.000105\n",
       "         1677622     Daylen   M     199  2010  0.000105\n",
       "         1677623     Jordon   M     199  2010  0.000105\n",
       "         1677624    Dashawn   M     198  2010  0.000104\n",
       "         1677625      Masen   M     198  2010  0.000104\n",
       "         1677629      Rowen   M     197  2010  0.000104\n",
       "         1677631     Yousef   M     197  2010  0.000104\n",
       "         1677630   Thaddeus   M     197  2010  0.000104\n",
       "         1677628      Kadin   M     197  2010  0.000104\n",
       "         1677627     Dillan   M     197  2010  0.000104\n",
       "         1677626   Clarence   M     197  2010  0.000104\n",
       "         1677634      Slade   M     196  2010  0.000103\n",
       "         1677632    Clinton   M     196  2010  0.000103\n",
       "         1677633    Sheldon   M     196  2010  0.000103\n",
       "         1677636    Keshawn   M     195  2010  0.000103\n",
       "         1677637   Menachem   M     195  2010  0.000103\n",
       "         1677635     Joziah   M     195  2010  0.000103\n",
       "         1677638     Bailey   M     194  2010  0.000102\n",
       "         1677639     Camilo   M     194  2010  0.000102\n",
       "         1677640     Destin   M     194  2010  0.000102\n",
       "         1677641     Jaquan   M     194  2010  0.000102\n",
       "         1677642     Jaydan   M     194  2010  0.000102\n",
       "         1677645     Maxton   M     193  2010  0.000102\n",
       "\n",
       "[261877 rows x 5 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 上位1000を取得する\n",
    "def get_top1000(group):\n",
    "    return group.sort_values(by='births', ascending=False)[:1000]\n",
    "# 年代、性別ごとのグループ\n",
    "grouped = names.groupby(['year', 'sex'])\n",
    "top1000 = grouped.apply(get_top1000)\n",
    "top1000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.1 名付けの傾向分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</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 rowspan=\"30\" valign=\"top\">1880</th>\n",
       "      <th rowspan=\"30\" valign=\"top\">M</th>\n",
       "      <th>942</th>\n",
       "      <td>John</td>\n",
       "      <td>M</td>\n",
       "      <td>9655</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.087381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>William</td>\n",
       "      <td>M</td>\n",
       "      <td>9533</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.086277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944</th>\n",
       "      <td>James</td>\n",
       "      <td>M</td>\n",
       "      <td>5927</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.053641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>Charles</td>\n",
       "      <td>M</td>\n",
       "      <td>5348</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.048401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
       "      <td>George</td>\n",
       "      <td>M</td>\n",
       "      <td>5126</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.046392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>Frank</td>\n",
       "      <td>M</td>\n",
       "      <td>3242</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.029341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>M</td>\n",
       "      <td>2632</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.023821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>M</td>\n",
       "      <td>2534</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>950</th>\n",
       "      <td>Henry</td>\n",
       "      <td>M</td>\n",
       "      <td>2444</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>951</th>\n",
       "      <td>Robert</td>\n",
       "      <td>M</td>\n",
       "      <td>2416</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>952</th>\n",
       "      <td>Edward</td>\n",
       "      <td>M</td>\n",
       "      <td>2364</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>953</th>\n",
       "      <td>Harry</td>\n",
       "      <td>M</td>\n",
       "      <td>2152</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.019476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>954</th>\n",
       "      <td>Walter</td>\n",
       "      <td>M</td>\n",
       "      <td>1755</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.015883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>Arthur</td>\n",
       "      <td>M</td>\n",
       "      <td>1599</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>Fred</td>\n",
       "      <td>M</td>\n",
       "      <td>1569</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>957</th>\n",
       "      <td>Albert</td>\n",
       "      <td>M</td>\n",
       "      <td>1493</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>M</td>\n",
       "      <td>1024</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.009268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>959</th>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>869</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>Louis</td>\n",
       "      <td>M</td>\n",
       "      <td>828</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>961</th>\n",
       "      <td>Joe</td>\n",
       "      <td>M</td>\n",
       "      <td>731</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.006616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>Charlie</td>\n",
       "      <td>M</td>\n",
       "      <td>730</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.006607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>963</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>M</td>\n",
       "      <td>730</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.006607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964</th>\n",
       "      <td>Richard</td>\n",
       "      <td>M</td>\n",
       "      <td>728</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.006589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>Andrew</td>\n",
       "      <td>M</td>\n",
       "      <td>644</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.005828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>Daniel</td>\n",
       "      <td>M</td>\n",
       "      <td>643</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.005819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>967</th>\n",
       "      <td>Ernest</td>\n",
       "      <td>M</td>\n",
       "      <td>615</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.005566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>Will</td>\n",
       "      <td>M</td>\n",
       "      <td>588</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.005322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>969</th>\n",
       "      <td>Jesse</td>\n",
       "      <td>M</td>\n",
       "      <td>569</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.005150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>Oscar</td>\n",
       "      <td>M</td>\n",
       "      <td>544</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.004923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>Lewis</td>\n",
       "      <td>M</td>\n",
       "      <td>517</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.004679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">2010</th>\n",
       "      <th rowspan=\"30\" valign=\"top\">M</th>\n",
       "      <th>1677617</th>\n",
       "      <td>Yair</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677616</th>\n",
       "      <td>Talan</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677614</th>\n",
       "      <td>Keyon</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677613</th>\n",
       "      <td>Kael</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677618</th>\n",
       "      <td>Demarion</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677619</th>\n",
       "      <td>Gibson</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677620</th>\n",
       "      <td>Reagan</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677621</th>\n",
       "      <td>Cristofer</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677622</th>\n",
       "      <td>Daylen</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677623</th>\n",
       "      <td>Jordon</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677624</th>\n",
       "      <td>Dashawn</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677625</th>\n",
       "      <td>Masen</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677629</th>\n",
       "      <td>Rowen</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677631</th>\n",
       "      <td>Yousef</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677630</th>\n",
       "      <td>Thaddeus</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677628</th>\n",
       "      <td>Kadin</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677627</th>\n",
       "      <td>Dillan</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677626</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677634</th>\n",
       "      <td>Slade</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677632</th>\n",
       "      <td>Clinton</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677633</th>\n",
       "      <td>Sheldon</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677636</th>\n",
       "      <td>Keshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677637</th>\n",
       "      <td>Menachem</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677635</th>\n",
       "      <td>Joziah</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677638</th>\n",
       "      <td>Bailey</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677639</th>\n",
       "      <td>Camilo</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677640</th>\n",
       "      <td>Destin</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677641</th>\n",
       "      <td>Jaquan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677642</th>\n",
       "      <td>Jaydan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677645</th>\n",
       "      <td>Maxton</td>\n",
       "      <td>M</td>\n",
       "      <td>193</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130997 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name sex  births  year      prop\n",
       "year sex                                               \n",
       "1880 M   942           John   M    9655  1880  0.087381\n",
       "         943        William   M    9533  1880  0.086277\n",
       "         944          James   M    5927  1880  0.053641\n",
       "         945        Charles   M    5348  1880  0.048401\n",
       "         946         George   M    5126  1880  0.046392\n",
       "         947          Frank   M    3242  1880  0.029341\n",
       "         948         Joseph   M    2632  1880  0.023821\n",
       "         949         Thomas   M    2534  1880  0.022934\n",
       "         950          Henry   M    2444  1880  0.022119\n",
       "         951         Robert   M    2416  1880  0.021866\n",
       "         952         Edward   M    2364  1880  0.021395\n",
       "         953          Harry   M    2152  1880  0.019476\n",
       "         954         Walter   M    1755  1880  0.015883\n",
       "         955         Arthur   M    1599  1880  0.014472\n",
       "         956           Fred   M    1569  1880  0.014200\n",
       "         957         Albert   M    1493  1880  0.013512\n",
       "         958         Samuel   M    1024  1880  0.009268\n",
       "         959          David   M     869  1880  0.007865\n",
       "         960          Louis   M     828  1880  0.007494\n",
       "         961            Joe   M     731  1880  0.006616\n",
       "         962        Charlie   M     730  1880  0.006607\n",
       "         963       Clarence   M     730  1880  0.006607\n",
       "         964        Richard   M     728  1880  0.006589\n",
       "         965         Andrew   M     644  1880  0.005828\n",
       "         966         Daniel   M     643  1880  0.005819\n",
       "         967         Ernest   M     615  1880  0.005566\n",
       "         968           Will   M     588  1880  0.005322\n",
       "         969          Jesse   M     569  1880  0.005150\n",
       "         970          Oscar   M     544  1880  0.004923\n",
       "         971          Lewis   M     517  1880  0.004679\n",
       "...                     ...  ..     ...   ...       ...\n",
       "2010 M   1677617       Yair   M     201  2010  0.000106\n",
       "         1677616      Talan   M     201  2010  0.000106\n",
       "         1677614      Keyon   M     201  2010  0.000106\n",
       "         1677613       Kael   M     201  2010  0.000106\n",
       "         1677618   Demarion   M     200  2010  0.000105\n",
       "         1677619     Gibson   M     200  2010  0.000105\n",
       "         1677620     Reagan   M     200  2010  0.000105\n",
       "         1677621  Cristofer   M     199  2010  0.000105\n",
       "         1677622     Daylen   M     199  2010  0.000105\n",
       "         1677623     Jordon   M     199  2010  0.000105\n",
       "         1677624    Dashawn   M     198  2010  0.000104\n",
       "         1677625      Masen   M     198  2010  0.000104\n",
       "         1677629      Rowen   M     197  2010  0.000104\n",
       "         1677631     Yousef   M     197  2010  0.000104\n",
       "         1677630   Thaddeus   M     197  2010  0.000104\n",
       "         1677628      Kadin   M     197  2010  0.000104\n",
       "         1677627     Dillan   M     197  2010  0.000104\n",
       "         1677626   Clarence   M     197  2010  0.000104\n",
       "         1677634      Slade   M     196  2010  0.000103\n",
       "         1677632    Clinton   M     196  2010  0.000103\n",
       "         1677633    Sheldon   M     196  2010  0.000103\n",
       "         1677636    Keshawn   M     195  2010  0.000103\n",
       "         1677637   Menachem   M     195  2010  0.000103\n",
       "         1677635     Joziah   M     195  2010  0.000103\n",
       "         1677638     Bailey   M     194  2010  0.000102\n",
       "         1677639     Camilo   M     194  2010  0.000102\n",
       "         1677640     Destin   M     194  2010  0.000102\n",
       "         1677641     Jaquan   M     194  2010  0.000102\n",
       "         1677642     Jaydan   M     194  2010  0.000102\n",
       "         1677645     Maxton   M     193  2010  0.000102\n",
       "\n",
       "[130997 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boys = top1000[top1000.sex == 'M']\n",
    "girls = top1000[top1000.sex == 'F']\n",
    "boys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>name</th>\n",
       "      <th>Aaden</th>\n",
       "      <th>Aaliyah</th>\n",
       "      <th>Aarav</th>\n",
       "      <th>Aaron</th>\n",
       "      <th>Aarush</th>\n",
       "      <th>Ab</th>\n",
       "      <th>Abagail</th>\n",
       "      <th>Abb</th>\n",
       "      <th>Abbey</th>\n",
       "      <th>Abbie</th>\n",
       "      <th>...</th>\n",
       "      <th>Zoa</th>\n",
       "      <th>Zoe</th>\n",
       "      <th>Zoey</th>\n",
       "      <th>Zoie</th>\n",
       "      <th>Zola</th>\n",
       "      <th>Zollie</th>\n",
       "      <th>Zona</th>\n",
       "      <th>Zora</th>\n",
       "      <th>Zula</th>\n",
       "      <th>Zuri</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>1880</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>28</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>35</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>58</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1885</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>48</td>\n",
       "      <td>38</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1886</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "      <td>52</td>\n",
       "      <td>43</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1887</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28</td>\n",
       "      <td>46</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1888</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>30</td>\n",
       "      <td>42</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1889</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>53</td>\n",
       "      <td>55</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1890</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>7</td>\n",
       "      <td>27</td>\n",
       "      <td>60</td>\n",
       "      <td>65</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>52</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>66</td>\n",
       "      <td>53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1893</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>67</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1894</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>66</td>\n",
       "      <td>64</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1895</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>11</td>\n",
       "      <td>38</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1896</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>121</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38</td>\n",
       "      <td>72</td>\n",
       "      <td>65</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1897</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28</td>\n",
       "      <td>67</td>\n",
       "      <td>79</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1898</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28</td>\n",
       "      <td>65</td>\n",
       "      <td>83</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1899</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49</td>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>56</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>112</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48</td>\n",
       "      <td>9</td>\n",
       "      <td>44</td>\n",
       "      <td>99</td>\n",
       "      <td>71</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1901</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31</td>\n",
       "      <td>58</td>\n",
       "      <td>57</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1902</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>58</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1903</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>83</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1904</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>54</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1905</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>24</td>\n",
       "      <td>55</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1906</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1907</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53</td>\n",
       "      <td>11</td>\n",
       "      <td>39</td>\n",
       "      <td>92</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1908</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31</td>\n",
       "      <td>59</td>\n",
       "      <td>53</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39</td>\n",
       "      <td>57</td>\n",
       "      <td>76</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>1981</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14832</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>383</td>\n",
       "      <td>292</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14538</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>372</td>\n",
       "      <td>275</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14627</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>419</td>\n",
       "      <td>223</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13387</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>357</td>\n",
       "      <td>249</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>314</td>\n",
       "      <td>233</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12685</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>369</td>\n",
       "      <td>228</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>327</td>\n",
       "      <td>228</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14393</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>404</td>\n",
       "      <td>226</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>238</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>470</td>\n",
       "      <td>265</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>376</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14545</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>507</td>\n",
       "      <td>311</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>478</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14240</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>451</td>\n",
       "      <td>278</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14494</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>430</td>\n",
       "      <td>260</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>978</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13819</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>503</td>\n",
       "      <td>291</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1194</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1451</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14379</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597</td>\n",
       "      <td>351</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1254</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13277</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>549</td>\n",
       "      <td>351</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1726</td>\n",
       "      <td>219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>831</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11956</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>552</td>\n",
       "      <td>349</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2063</td>\n",
       "      <td>339</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11156</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645</td>\n",
       "      <td>386</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2363</td>\n",
       "      <td>407</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1399</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10539</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>661</td>\n",
       "      <td>398</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2690</td>\n",
       "      <td>478</td>\n",
       "      <td>225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9846</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>211</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710</td>\n",
       "      <td>430</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3238</td>\n",
       "      <td>561</td>\n",
       "      <td>257</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1494</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9548</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>660</td>\n",
       "      <td>432</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3783</td>\n",
       "      <td>691</td>\n",
       "      <td>320</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9529</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244</td>\n",
       "      <td>NaN</td>\n",
       "      <td>687</td>\n",
       "      <td>526</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4642</td>\n",
       "      <td>822</td>\n",
       "      <td>439</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4775</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600</td>\n",
       "      <td>514</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4883</td>\n",
       "      <td>1182</td>\n",
       "      <td>438</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3670</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276</td>\n",
       "      <td>NaN</td>\n",
       "      <td>625</td>\n",
       "      <td>536</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5080</td>\n",
       "      <td>1465</td>\n",
       "      <td>448</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3482</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>258</td>\n",
       "      <td>NaN</td>\n",
       "      <td>504</td>\n",
       "      <td>500</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5359</td>\n",
       "      <td>1621</td>\n",
       "      <td>515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3452</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7796</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>451</td>\n",
       "      <td>445</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4953</td>\n",
       "      <td>2266</td>\n",
       "      <td>502</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8279</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>404</td>\n",
       "      <td>440</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5145</td>\n",
       "      <td>2839</td>\n",
       "      <td>530</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3941</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>349</td>\n",
       "      <td>468</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4925</td>\n",
       "      <td>3028</td>\n",
       "      <td>526</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>955</td>\n",
       "      <td>4028</td>\n",
       "      <td>219</td>\n",
       "      <td>8511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>317</td>\n",
       "      <td>NaN</td>\n",
       "      <td>344</td>\n",
       "      <td>400</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4764</td>\n",
       "      <td>3438</td>\n",
       "      <td>492</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1265</td>\n",
       "      <td>4352</td>\n",
       "      <td>270</td>\n",
       "      <td>7936</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>307</td>\n",
       "      <td>369</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5120</td>\n",
       "      <td>3981</td>\n",
       "      <td>496</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>448</td>\n",
       "      <td>4628</td>\n",
       "      <td>438</td>\n",
       "      <td>7374</td>\n",
       "      <td>226</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277</td>\n",
       "      <td>NaN</td>\n",
       "      <td>295</td>\n",
       "      <td>324</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6200</td>\n",
       "      <td>5164</td>\n",
       "      <td>504</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 6868 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "name  Aaden  Aaliyah  Aarav  Aaron  Aarush  Ab  Abagail  Abb  Abbey  Abbie  \\\n",
       "year                                                                         \n",
       "1880    NaN      NaN    NaN    102     NaN NaN      NaN  NaN    NaN     71   \n",
       "1881    NaN      NaN    NaN     94     NaN NaN      NaN  NaN    NaN     81   \n",
       "1882    NaN      NaN    NaN     85     NaN NaN      NaN  NaN    NaN     80   \n",
       "1883    NaN      NaN    NaN    105     NaN NaN      NaN  NaN    NaN     79   \n",
       "1884    NaN      NaN    NaN     97     NaN NaN      NaN  NaN    NaN     98   \n",
       "1885    NaN      NaN    NaN     88     NaN   6      NaN  NaN    NaN     88   \n",
       "1886    NaN      NaN    NaN     86     NaN NaN      NaN  NaN    NaN     84   \n",
       "1887    NaN      NaN    NaN     78     NaN NaN      NaN  NaN    NaN    104   \n",
       "1888    NaN      NaN    NaN     90     NaN NaN      NaN  NaN    NaN    137   \n",
       "1889    NaN      NaN    NaN     85     NaN NaN      NaN  NaN    NaN    107   \n",
       "1890    NaN      NaN    NaN     96     NaN NaN      NaN    6    NaN    140   \n",
       "1891    NaN      NaN    NaN     69     NaN NaN      NaN  NaN    NaN    124   \n",
       "1892    NaN      NaN    NaN     95     NaN NaN      NaN  NaN    NaN    119   \n",
       "1893    NaN      NaN    NaN     81     NaN NaN      NaN  NaN    NaN    115   \n",
       "1894    NaN      NaN    NaN     79     NaN NaN      NaN  NaN    NaN    118   \n",
       "1895    NaN      NaN    NaN     94     NaN NaN      NaN  NaN    NaN     92   \n",
       "1896    NaN      NaN    NaN     69     NaN NaN      NaN  NaN    NaN    121   \n",
       "1897    NaN      NaN    NaN     87     NaN NaN      NaN  NaN    NaN     97   \n",
       "1898    NaN      NaN    NaN     89     NaN NaN      NaN  NaN    NaN    120   \n",
       "1899    NaN      NaN    NaN     71     NaN NaN      NaN  NaN    NaN     87   \n",
       "1900    NaN      NaN    NaN    104     NaN NaN      NaN  NaN    NaN    112   \n",
       "1901    NaN      NaN    NaN     80     NaN NaN      NaN  NaN    NaN     87   \n",
       "1902    NaN      NaN    NaN     78     NaN NaN      NaN  NaN    NaN     91   \n",
       "1903    NaN      NaN    NaN     93     NaN NaN      NaN  NaN    NaN     91   \n",
       "1904    NaN      NaN    NaN    117     NaN NaN      NaN  NaN    NaN     80   \n",
       "1905    NaN      NaN    NaN     96     NaN NaN      NaN  NaN    NaN     73   \n",
       "1906    NaN      NaN    NaN     96     NaN NaN      NaN  NaN    NaN     72   \n",
       "1907    NaN      NaN    NaN    130     NaN NaN      NaN  NaN    NaN     79   \n",
       "1908    NaN      NaN    NaN    114     NaN NaN      NaN  NaN    NaN     84   \n",
       "1909    NaN      NaN    NaN    142     NaN NaN      NaN  NaN    NaN     57   \n",
       "...     ...      ...    ...    ...     ...  ..      ...  ...    ...    ...   \n",
       "1981    NaN      NaN    NaN  14832     NaN NaN      NaN  NaN    383    292   \n",
       "1982    NaN      NaN    NaN  14538     NaN NaN      NaN  NaN    372    275   \n",
       "1983    NaN      NaN    NaN  14627     NaN NaN      NaN  NaN    419    223   \n",
       "1984    NaN      NaN    NaN  13387     NaN NaN      NaN  NaN    357    249   \n",
       "1985    NaN      NaN    NaN  13123     NaN NaN      NaN  NaN    314    233   \n",
       "1986    NaN      NaN    NaN  12685     NaN NaN      NaN  NaN    369    228   \n",
       "1987    NaN      NaN    NaN  12676     NaN NaN      NaN  NaN    327    228   \n",
       "1988    NaN      NaN    NaN  14393     NaN NaN      NaN  NaN    404    226   \n",
       "1989    NaN      NaN    NaN  15312     NaN NaN      NaN  NaN    470    265   \n",
       "1990    NaN      NaN    NaN  14545     NaN NaN      NaN  NaN    507    311   \n",
       "1991    NaN      NaN    NaN  14240     NaN NaN      NaN  NaN    451    278   \n",
       "1992    NaN      NaN    NaN  14494     NaN NaN      NaN  NaN    430    260   \n",
       "1993    NaN      NaN    NaN  13819     NaN NaN      NaN  NaN    503    291   \n",
       "1994    NaN     1451    NaN  14379     NaN NaN      NaN  NaN    597    351   \n",
       "1995    NaN     1254    NaN  13277     NaN NaN      NaN  NaN    549    351   \n",
       "1996    NaN      831    NaN  11956     NaN NaN      NaN  NaN    552    349   \n",
       "1997    NaN     1737    NaN  11156     NaN NaN      NaN  NaN    645    386   \n",
       "1998    NaN     1399    NaN  10539     NaN NaN      NaN  NaN    661    398   \n",
       "1999    NaN     1088    NaN   9846     NaN NaN      211  NaN    710    430   \n",
       "2000    NaN     1494    NaN   9548     NaN NaN      222  NaN    660    432   \n",
       "2001    NaN     3351    NaN   9529     NaN NaN      244  NaN    687    526   \n",
       "2002    NaN     4775    NaN   8993     NaN NaN      256  NaN    600    514   \n",
       "2003    NaN     3670    NaN   8851     NaN NaN      276  NaN    625    536   \n",
       "2004    NaN     3482    NaN   8381     NaN NaN      258  NaN    504    500   \n",
       "2005    NaN     3452    NaN   7796     NaN NaN      287  NaN    451    445   \n",
       "2006    NaN     3737    NaN   8279     NaN NaN      297  NaN    404    440   \n",
       "2007    NaN     3941    NaN   8914     NaN NaN      313  NaN    349    468   \n",
       "2008    955     4028    219   8511     NaN NaN      317  NaN    344    400   \n",
       "2009   1265     4352    270   7936     NaN NaN      296  NaN    307    369   \n",
       "2010    448     4628    438   7374     226 NaN      277  NaN    295    324   \n",
       "\n",
       "name  ...   Zoa   Zoe  Zoey  Zoie  Zola  Zollie  Zona  Zora  Zula  Zuri  \n",
       "year  ...                                                                \n",
       "1880  ...     8    23   NaN   NaN     7     NaN     8    28    27   NaN  \n",
       "1881  ...   NaN    22   NaN   NaN    10     NaN     9    21    27   NaN  \n",
       "1882  ...     8    25   NaN   NaN     9     NaN    17    32    21   NaN  \n",
       "1883  ...   NaN    23   NaN   NaN    10     NaN    11    35    25   NaN  \n",
       "1884  ...    13    31   NaN   NaN    14       6     8    58    27   NaN  \n",
       "1885  ...     6    27   NaN   NaN    12       6    14    48    38   NaN  \n",
       "1886  ...    13    25   NaN   NaN     8     NaN    20    52    43   NaN  \n",
       "1887  ...     9    34   NaN   NaN    23     NaN    28    46    33   NaN  \n",
       "1888  ...    11    42   NaN   NaN    23       7    30    42    45   NaN  \n",
       "1889  ...    14    29   NaN   NaN    22     NaN    29    53    55   NaN  \n",
       "1890  ...   NaN    42   NaN   NaN    32       7    27    60    65   NaN  \n",
       "1891  ...   NaN    34   NaN   NaN    29       6    14    52    45   NaN  \n",
       "1892  ...   NaN    34   NaN   NaN    27     NaN    25    66    53   NaN  \n",
       "1893  ...   NaN    23   NaN   NaN    34       6    15    67    70   NaN  \n",
       "1894  ...   NaN    28   NaN   NaN    51     NaN    23    66    64   NaN  \n",
       "1895  ...   NaN    34   NaN   NaN    60      11    38    55    55   NaN  \n",
       "1896  ...   NaN    36   NaN   NaN    47     NaN    38    72    65   NaN  \n",
       "1897  ...   NaN    35   NaN   NaN    51     NaN    28    67    79   NaN  \n",
       "1898  ...   NaN    30   NaN   NaN    62     NaN    28    65    83   NaN  \n",
       "1899  ...   NaN    27   NaN   NaN    49       6    31    56    60   NaN  \n",
       "1900  ...   NaN    26   NaN   NaN    48       9    44    99    71   NaN  \n",
       "1901  ...   NaN    26   NaN   NaN    56     NaN    31    58    57   NaN  \n",
       "1902  ...   NaN    34   NaN   NaN    58     NaN    23    58    66   NaN  \n",
       "1903  ...   NaN    19   NaN   NaN    64     NaN    41    83    74   NaN  \n",
       "1904  ...   NaN    27   NaN   NaN    46     NaN    35    54    74   NaN  \n",
       "1905  ...   NaN    24   NaN   NaN    66       8    24    55    61   NaN  \n",
       "1906  ...   NaN    19   NaN   NaN    59     NaN    37    64    58   NaN  \n",
       "1907  ...   NaN    19   NaN   NaN    53      11    39    92    72   NaN  \n",
       "1908  ...   NaN    23   NaN   NaN    70     NaN    31    59    53   NaN  \n",
       "1909  ...   NaN    22   NaN   NaN    59     NaN    39    57    76   NaN  \n",
       "...   ...   ...   ...   ...   ...   ...     ...   ...   ...   ...   ...  \n",
       "1981  ...   NaN   NaN   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1982  ...   NaN   NaN   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1983  ...   NaN   174   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1984  ...   NaN   200   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1985  ...   NaN   193   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1986  ...   NaN   213   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1987  ...   NaN   248   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1988  ...   NaN   238   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1989  ...   NaN   376   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1990  ...   NaN   478   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1991  ...   NaN   722   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1992  ...   NaN   978   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1993  ...   NaN  1194   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1994  ...   NaN  1332   NaN   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1995  ...   NaN  1726   219   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1996  ...   NaN  2063   339   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1997  ...   NaN  2363   407   NaN   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1998  ...   NaN  2690   478   225   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "1999  ...   NaN  3238   561   257   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2000  ...   NaN  3783   691   320   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2001  ...   NaN  4642   822   439   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2002  ...   NaN  4883  1182   438   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2003  ...   NaN  5080  1465   448   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2004  ...   NaN  5359  1621   515   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2005  ...   NaN  4953  2266   502   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2006  ...   NaN  5145  2839   530   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2007  ...   NaN  4925  3028   526   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2008  ...   NaN  4764  3438   492   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2009  ...   NaN  5120  3981   496   NaN     NaN   NaN   NaN   NaN   NaN  \n",
       "2010  ...   NaN  6200  5164   504   NaN     NaN   NaN   NaN   NaN   258  \n",
       "\n",
       "[131 rows x 6868 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_births = top1000.pivot_table('births', index='year', columns='name', aggfunc=sum)\n",
    "total_births\n",
    "# ある名前の出生数の年代ごとの推移"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x14bec0358>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x14a8bba20>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x14a7bd7f0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x144649f98>], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LkxHT07O3LVvgiSdCnemixh3+9a+Q4/yf/4QRQJFE0ORBkfjkt1Tdj8DJ7p4e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7VN7LK2iV3WNrEr6m2TkLB/oGJXBYNQXu6C6cittLTDQ2JlmZq5wGZV3aaqrcCjwHlRrpPphq4s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\nSerI4lmSJEnq6E97DlrFrztrXwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14a30f940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "subset = total_births[['John', 'Harry', 'Mary', 'Marilyn']]\n",
    "subset.plot(subplots=True, figsize=(12,10), grid=False, title='Number of births per year')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.1.1多様化していく名付け"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x14527e9b0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x144642e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 上位1000の名前が全体に占める割合を計算し、名前が多様化しているかどうかを検証する\n",
    "table = top1000.pivot_table('prop', index='year', columns='sex', aggfunc=sum)\n",
    "table.plot(title='Sum of table1000.prop by year and sex',\n",
    "          yticks=np.linspace(0,1.2,13), xticks=range(1880,2020,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "近年名前の多様性が上がっている。特に女子の方がその傾向が顕著。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</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 rowspan=\"61\" valign=\"top\">2010</th>\n",
       "      <th rowspan=\"61\" valign=\"top\">M</th>\n",
       "      <th>1676644</th>\n",
       "      <td>Jacob</td>\n",
       "      <td>M</td>\n",
       "      <td>21875</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.011523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676645</th>\n",
       "      <td>Ethan</td>\n",
       "      <td>M</td>\n",
       "      <td>17866</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.009411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676646</th>\n",
       "      <td>Michael</td>\n",
       "      <td>M</td>\n",
       "      <td>17133</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.009025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676647</th>\n",
       "      <td>Jayden</td>\n",
       "      <td>M</td>\n",
       "      <td>17030</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676648</th>\n",
       "      <td>William</td>\n",
       "      <td>M</td>\n",
       "      <td>16870</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676649</th>\n",
       "      <td>Alexander</td>\n",
       "      <td>M</td>\n",
       "      <td>16634</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676650</th>\n",
       "      <td>Noah</td>\n",
       "      <td>M</td>\n",
       "      <td>16281</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676651</th>\n",
       "      <td>Daniel</td>\n",
       "      <td>M</td>\n",
       "      <td>15679</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676652</th>\n",
       "      <td>Aiden</td>\n",
       "      <td>M</td>\n",
       "      <td>15403</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676653</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>M</td>\n",
       "      <td>15364</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676654</th>\n",
       "      <td>Joshua</td>\n",
       "      <td>M</td>\n",
       "      <td>15238</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.008027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676655</th>\n",
       "      <td>Mason</td>\n",
       "      <td>M</td>\n",
       "      <td>14728</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676656</th>\n",
       "      <td>Christopher</td>\n",
       "      <td>M</td>\n",
       "      <td>14135</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676657</th>\n",
       "      <td>Andrew</td>\n",
       "      <td>M</td>\n",
       "      <td>14093</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676658</th>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>14042</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676659</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>M</td>\n",
       "      <td>13954</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676660</th>\n",
       "      <td>Logan</td>\n",
       "      <td>M</td>\n",
       "      <td>13943</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676661</th>\n",
       "      <td>Elijah</td>\n",
       "      <td>M</td>\n",
       "      <td>13735</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676662</th>\n",
       "      <td>James</td>\n",
       "      <td>M</td>\n",
       "      <td>13714</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676663</th>\n",
       "      <td>Joseph</td>\n",
       "      <td>M</td>\n",
       "      <td>13657</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.007194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676664</th>\n",
       "      <td>Gabriel</td>\n",
       "      <td>M</td>\n",
       "      <td>12722</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676665</th>\n",
       "      <td>Benjamin</td>\n",
       "      <td>M</td>\n",
       "      <td>12280</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676666</th>\n",
       "      <td>Ryan</td>\n",
       "      <td>M</td>\n",
       "      <td>11886</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676667</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>M</td>\n",
       "      <td>11776</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676668</th>\n",
       "      <td>Jackson</td>\n",
       "      <td>M</td>\n",
       "      <td>11693</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676669</th>\n",
       "      <td>John</td>\n",
       "      <td>M</td>\n",
       "      <td>11424</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.006018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676670</th>\n",
       "      <td>Nathan</td>\n",
       "      <td>M</td>\n",
       "      <td>11269</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.005936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676671</th>\n",
       "      <td>Jonathan</td>\n",
       "      <td>M</td>\n",
       "      <td>11028</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.005809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676672</th>\n",
       "      <td>Christian</td>\n",
       "      <td>M</td>\n",
       "      <td>10965</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.005776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676673</th>\n",
       "      <td>Liam</td>\n",
       "      <td>M</td>\n",
       "      <td>10852</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.005716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>Yair</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677617</th>\n",
       "      <td>Talan</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677616</th>\n",
       "      <td>Keyon</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677614</th>\n",
       "      <td>Kael</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677613</th>\n",
       "      <td>Demarion</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677618</th>\n",
       "      <td>Gibson</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677619</th>\n",
       "      <td>Reagan</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677620</th>\n",
       "      <td>Cristofer</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677621</th>\n",
       "      <td>Daylen</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677622</th>\n",
       "      <td>Jordon</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677623</th>\n",
       "      <td>Dashawn</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677624</th>\n",
       "      <td>Masen</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677625</th>\n",
       "      <td>Rowen</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677629</th>\n",
       "      <td>Yousef</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677631</th>\n",
       "      <td>Thaddeus</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677630</th>\n",
       "      <td>Kadin</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677628</th>\n",
       "      <td>Dillan</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677627</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677626</th>\n",
       "      <td>Slade</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677634</th>\n",
       "      <td>Clinton</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677632</th>\n",
       "      <td>Sheldon</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677633</th>\n",
       "      <td>Keshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677636</th>\n",
       "      <td>Menachem</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677637</th>\n",
       "      <td>Joziah</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677635</th>\n",
       "      <td>Bailey</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677638</th>\n",
       "      <td>Camilo</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677639</th>\n",
       "      <td>Destin</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677640</th>\n",
       "      <td>Jaquan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677641</th>\n",
       "      <td>Jaydan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677642</th>\n",
       "      <td>Maxton</td>\n",
       "      <td>M</td>\n",
       "      <td>193</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name sex  births  year      prop\n",
       "year sex                                                 \n",
       "2010 M   1676644        Jacob   M   21875  2010  0.011523\n",
       "         1676645        Ethan   M   17866  2010  0.009411\n",
       "         1676646      Michael   M   17133  2010  0.009025\n",
       "         1676647       Jayden   M   17030  2010  0.008971\n",
       "         1676648      William   M   16870  2010  0.008887\n",
       "         1676649    Alexander   M   16634  2010  0.008762\n",
       "         1676650         Noah   M   16281  2010  0.008576\n",
       "         1676651       Daniel   M   15679  2010  0.008259\n",
       "         1676652        Aiden   M   15403  2010  0.008114\n",
       "         1676653      Anthony   M   15364  2010  0.008093\n",
       "         1676654       Joshua   M   15238  2010  0.008027\n",
       "         1676655        Mason   M   14728  2010  0.007758\n",
       "         1676656  Christopher   M   14135  2010  0.007446\n",
       "         1676657       Andrew   M   14093  2010  0.007424\n",
       "         1676658        David   M   14042  2010  0.007397\n",
       "         1676659      Matthew   M   13954  2010  0.007350\n",
       "         1676660        Logan   M   13943  2010  0.007345\n",
       "         1676661       Elijah   M   13735  2010  0.007235\n",
       "         1676662        James   M   13714  2010  0.007224\n",
       "         1676663       Joseph   M   13657  2010  0.007194\n",
       "         1676664      Gabriel   M   12722  2010  0.006701\n",
       "         1676665     Benjamin   M   12280  2010  0.006469\n",
       "         1676666         Ryan   M   11886  2010  0.006261\n",
       "         1676667       Samuel   M   11776  2010  0.006203\n",
       "         1676668      Jackson   M   11693  2010  0.006159\n",
       "         1676669         John   M   11424  2010  0.006018\n",
       "         1676670       Nathan   M   11269  2010  0.005936\n",
       "         1676671     Jonathan   M   11028  2010  0.005809\n",
       "         1676672    Christian   M   10965  2010  0.005776\n",
       "         1676673         Liam   M   10852  2010  0.005716\n",
       "...                       ...  ..     ...   ...       ...\n",
       "         1677617         Yair   M     201  2010  0.000106\n",
       "         1677616        Talan   M     201  2010  0.000106\n",
       "         1677614        Keyon   M     201  2010  0.000106\n",
       "         1677613         Kael   M     201  2010  0.000106\n",
       "         1677618     Demarion   M     200  2010  0.000105\n",
       "         1677619       Gibson   M     200  2010  0.000105\n",
       "         1677620       Reagan   M     200  2010  0.000105\n",
       "         1677621    Cristofer   M     199  2010  0.000105\n",
       "         1677622       Daylen   M     199  2010  0.000105\n",
       "         1677623       Jordon   M     199  2010  0.000105\n",
       "         1677624      Dashawn   M     198  2010  0.000104\n",
       "         1677625        Masen   M     198  2010  0.000104\n",
       "         1677629        Rowen   M     197  2010  0.000104\n",
       "         1677631       Yousef   M     197  2010  0.000104\n",
       "         1677630     Thaddeus   M     197  2010  0.000104\n",
       "         1677628        Kadin   M     197  2010  0.000104\n",
       "         1677627       Dillan   M     197  2010  0.000104\n",
       "         1677626     Clarence   M     197  2010  0.000104\n",
       "         1677634        Slade   M     196  2010  0.000103\n",
       "         1677632      Clinton   M     196  2010  0.000103\n",
       "         1677633      Sheldon   M     196  2010  0.000103\n",
       "         1677636      Keshawn   M     195  2010  0.000103\n",
       "         1677637     Menachem   M     195  2010  0.000103\n",
       "         1677635       Joziah   M     195  2010  0.000103\n",
       "         1677638       Bailey   M     194  2010  0.000102\n",
       "         1677639       Camilo   M     194  2010  0.000102\n",
       "         1677640       Destin   M     194  2010  0.000102\n",
       "         1677641       Jaquan   M     194  2010  0.000102\n",
       "         1677642       Jaydan   M     194  2010  0.000102\n",
       "         1677645       Maxton   M     193  2010  0.000102\n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2010年生まれの男子の50%が何種類の名前で構成されているか\n",
    "df = boys[boys.year == 2010]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  sex         \n",
       "2010  M    1676644    0.011523\n",
       "           1676645    0.020934\n",
       "           1676646    0.029959\n",
       "           1676647    0.038930\n",
       "           1676648    0.047817\n",
       "           1676649    0.056579\n",
       "           1676650    0.065155\n",
       "           1676651    0.073414\n",
       "           1676652    0.081528\n",
       "           1676653    0.089621\n",
       "Name: prop, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prop_cumsum = df.sort_values(by='prop', ascending=False).prop.cumsum()\n",
    "prop_cumsum[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([116])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 50%になるインデックスは？\n",
    "prop_cumsum.searchsorted(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 上位117番目で50%になる。続いて、1900は？\n",
    "df = boys[boys.year == 1900]\n",
    "in1900 = df.sort_values(by='prop', ascending=False).prop.cumsum()\n",
    "in1900.searchsorted(0.5)[0] + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>38</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>38</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>38</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>39</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1885</th>\n",
       "      <td>40</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1886</th>\n",
       "      <td>41</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1887</th>\n",
       "      <td>41</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1888</th>\n",
       "      <td>42</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1889</th>\n",
       "      <td>43</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    F   M\n",
       "year        \n",
       "1880  38  14\n",
       "1881  38  14\n",
       "1882  38  15\n",
       "1883  39  15\n",
       "1884  39  16\n",
       "1885  40  16\n",
       "1886  41  16\n",
       "1887  41  17\n",
       "1888  42  17\n",
       "1889  43  18"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 25番目。年代別の推移を知りたい\n",
    "def get_quantile_count(group, q=0.5):\n",
    "    group = group.sort_values(by='prop', ascending=False)\n",
    "    return group.prop.cumsum().searchsorted(q)[0] + 1\n",
    "diversity = top1000.groupby(['year', 'sex']).apply(get_quantile_count)\n",
    "diversity = diversity.unstack()\n",
    "diversity[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x143ee98d0>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fxtgvnAcfvFRLL0ibft9E5NhIlj66lIbXNAzYdTSgK6VyLSYGXnkF2re3vzdq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\nB8Z0k86Pe39k8+HNAJxNPcv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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1452dab38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diversity.plot(title='Number of popular names in top 50%')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "女子の方が常に多様性に富んでいる。また近年急速に多様性が拡大した。\n",
    "\n",
    "## 2.3.1.2 名前「末尾一文字の変化」\n",
    "\n",
    "男の子の名前の末尾の文字は過去100年で大幅に多様化したらしい"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th colspan=\"10\" halign=\"left\">F</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>1880</th>\n",
       "      <th>1881</th>\n",
       "      <th>1882</th>\n",
       "      <th>1883</th>\n",
       "      <th>1884</th>\n",
       "      <th>1885</th>\n",
       "      <th>1886</th>\n",
       "      <th>1887</th>\n",
       "      <th>1888</th>\n",
       "      <th>1889</th>\n",
       "      <th>...</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_letter</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>a</th>\n",
       "      <td>31446</td>\n",
       "      <td>31581</td>\n",
       "      <td>36536</td>\n",
       "      <td>38330</td>\n",
       "      <td>43680</td>\n",
       "      <td>45408</td>\n",
       "      <td>49100</td>\n",
       "      <td>48942</td>\n",
       "      <td>59442</td>\n",
       "      <td>58631</td>\n",
       "      <td>...</td>\n",
       "      <td>39124</td>\n",
       "      <td>38815</td>\n",
       "      <td>37825</td>\n",
       "      <td>38650</td>\n",
       "      <td>36838</td>\n",
       "      <td>36156</td>\n",
       "      <td>34654</td>\n",
       "      <td>32901</td>\n",
       "      <td>31430</td>\n",
       "      <td>28438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>50950</td>\n",
       "      <td>49284</td>\n",
       "      <td>48065</td>\n",
       "      <td>45914</td>\n",
       "      <td>43144</td>\n",
       "      <td>42600</td>\n",
       "      <td>42123</td>\n",
       "      <td>39945</td>\n",
       "      <td>38862</td>\n",
       "      <td>38859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>27113</td>\n",
       "      <td>27238</td>\n",
       "      <td>27697</td>\n",
       "      <td>26778</td>\n",
       "      <td>26078</td>\n",
       "      <td>26635</td>\n",
       "      <td>26864</td>\n",
       "      <td>25318</td>\n",
       "      <td>24048</td>\n",
       "      <td>23125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>609</td>\n",
       "      <td>607</td>\n",
       "      <td>734</td>\n",
       "      <td>810</td>\n",
       "      <td>916</td>\n",
       "      <td>862</td>\n",
       "      <td>1007</td>\n",
       "      <td>1027</td>\n",
       "      <td>1298</td>\n",
       "      <td>1374</td>\n",
       "      <td>...</td>\n",
       "      <td>60838</td>\n",
       "      <td>55829</td>\n",
       "      <td>53391</td>\n",
       "      <td>51754</td>\n",
       "      <td>50670</td>\n",
       "      <td>51410</td>\n",
       "      <td>50595</td>\n",
       "      <td>47910</td>\n",
       "      <td>46172</td>\n",
       "      <td>44398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>33378</td>\n",
       "      <td>34080</td>\n",
       "      <td>40399</td>\n",
       "      <td>41914</td>\n",
       "      <td>48089</td>\n",
       "      <td>49616</td>\n",
       "      <td>53884</td>\n",
       "      <td>54353</td>\n",
       "      <td>66750</td>\n",
       "      <td>66663</td>\n",
       "      <td>...</td>\n",
       "      <td>145395</td>\n",
       "      <td>144651</td>\n",
       "      <td>144769</td>\n",
       "      <td>142098</td>\n",
       "      <td>141123</td>\n",
       "      <td>142999</td>\n",
       "      <td>143698</td>\n",
       "      <td>140966</td>\n",
       "      <td>135496</td>\n",
       "      <td>129012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1758</td>\n",
       "      <td>1817</td>\n",
       "      <td>1819</td>\n",
       "      <td>1904</td>\n",
       "      <td>1985</td>\n",
       "      <td>1968</td>\n",
       "      <td>2090</td>\n",
       "      <td>2195</td>\n",
       "      <td>2212</td>\n",
       "      <td>2255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>24</td>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>25</td>\n",
       "      <td>44</td>\n",
       "      <td>28</td>\n",
       "      <td>...</td>\n",
       "      <td>2151</td>\n",
       "      <td>2084</td>\n",
       "      <td>2009</td>\n",
       "      <td>1837</td>\n",
       "      <td>1882</td>\n",
       "      <td>1929</td>\n",
       "      <td>2040</td>\n",
       "      <td>2059</td>\n",
       "      <td>2396</td>\n",
       "      <td>2666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>4863</td>\n",
       "      <td>4784</td>\n",
       "      <td>5567</td>\n",
       "      <td>5701</td>\n",
       "      <td>6602</td>\n",
       "      <td>6624</td>\n",
       "      <td>7146</td>\n",
       "      <td>7141</td>\n",
       "      <td>8630</td>\n",
       "      <td>8826</td>\n",
       "      <td>...</td>\n",
       "      <td>85959</td>\n",
       "      <td>88085</td>\n",
       "      <td>88226</td>\n",
       "      <td>89620</td>\n",
       "      <td>92497</td>\n",
       "      <td>98477</td>\n",
       "      <td>99414</td>\n",
       "      <td>100250</td>\n",
       "      <td>99979</td>\n",
       "      <td>98090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>61</td>\n",
       "      <td>78</td>\n",
       "      <td>81</td>\n",
       "      <td>76</td>\n",
       "      <td>84</td>\n",
       "      <td>92</td>\n",
       "      <td>85</td>\n",
       "      <td>105</td>\n",
       "      <td>141</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>20980</td>\n",
       "      <td>23610</td>\n",
       "      <td>26011</td>\n",
       "      <td>28500</td>\n",
       "      <td>31317</td>\n",
       "      <td>33558</td>\n",
       "      <td>35231</td>\n",
       "      <td>38151</td>\n",
       "      <td>40912</td>\n",
       "      <td>42956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1069</td>\n",
       "      <td>1088</td>\n",
       "      <td>1203</td>\n",
       "      <td>1094</td>\n",
       "      <td>1291</td>\n",
       "      <td>1241</td>\n",
       "      <td>1254</td>\n",
       "      <td>1381</td>\n",
       "      <td>1416</td>\n",
       "      <td>1459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>k</th>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>18</td>\n",
       "      <td>27</td>\n",
       "      <td>19</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>42477</td>\n",
       "      <td>42043</td>\n",
       "      <td>42296</td>\n",
       "      <td>41400</td>\n",
       "      <td>42151</td>\n",
       "      <td>42537</td>\n",
       "      <td>42136</td>\n",
       "      <td>39563</td>\n",
       "      <td>37507</td>\n",
       "      <td>35198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>l</th>\n",
       "      <td>2541</td>\n",
       "      <td>2911</td>\n",
       "      <td>3527</td>\n",
       "      <td>3848</td>\n",
       "      <td>4808</td>\n",
       "      <td>5144</td>\n",
       "      <td>5721</td>\n",
       "      <td>6175</td>\n",
       "      <td>7900</td>\n",
       "      <td>8395</td>\n",
       "      <td>...</td>\n",
       "      <td>153648</td>\n",
       "      <td>153493</td>\n",
       "      <td>153862</td>\n",
       "      <td>152800</td>\n",
       "      <td>155312</td>\n",
       "      <td>156234</td>\n",
       "      <td>155203</td>\n",
       "      <td>150791</td>\n",
       "      <td>143751</td>\n",
       "      <td>133583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m</th>\n",
       "      <td>58</td>\n",
       "      <td>57</td>\n",
       "      <td>81</td>\n",
       "      <td>86</td>\n",
       "      <td>79</td>\n",
       "      <td>75</td>\n",
       "      <td>103</td>\n",
       "      <td>90</td>\n",
       "      <td>123</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>41967</td>\n",
       "      <td>42663</td>\n",
       "      <td>42790</td>\n",
       "      <td>43054</td>\n",
       "      <td>41600</td>\n",
       "      <td>42503</td>\n",
       "      <td>43860</td>\n",
       "      <td>44316</td>\n",
       "      <td>46278</td>\n",
       "      <td>46808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <td>3008</td>\n",
       "      <td>2959</td>\n",
       "      <td>3576</td>\n",
       "      <td>3837</td>\n",
       "      <td>4507</td>\n",
       "      <td>4735</td>\n",
       "      <td>5242</td>\n",
       "      <td>5512</td>\n",
       "      <td>6833</td>\n",
       "      <td>7103</td>\n",
       "      <td>...</td>\n",
       "      <td>616099</td>\n",
       "      <td>630322</td>\n",
       "      <td>663419</td>\n",
       "      <td>676011</td>\n",
       "      <td>686326</td>\n",
       "      <td>720998</td>\n",
       "      <td>741355</td>\n",
       "      <td>733869</td>\n",
       "      <td>715388</td>\n",
       "      <td>688677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>o</th>\n",
       "      <td>30</td>\n",
       "      <td>49</td>\n",
       "      <td>35</td>\n",
       "      <td>47</td>\n",
       "      <td>74</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>97</td>\n",
       "      <td>134</td>\n",
       "      <td>142</td>\n",
       "      <td>...</td>\n",
       "      <td>82146</td>\n",
       "      <td>83180</td>\n",
       "      <td>85423</td>\n",
       "      <td>88822</td>\n",
       "      <td>92001</td>\n",
       "      <td>96350</td>\n",
       "      <td>96895</td>\n",
       "      <td>91485</td>\n",
       "      <td>86423</td>\n",
       "      <td>81025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3419</td>\n",
       "      <td>3157</td>\n",
       "      <td>2982</td>\n",
       "      <td>2841</td>\n",
       "      <td>2768</td>\n",
       "      <td>2721</td>\n",
       "      <td>2739</td>\n",
       "      <td>2637</td>\n",
       "      <td>2595</td>\n",
       "      <td>2409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>q</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>602</td>\n",
       "      <td>618</td>\n",
       "      <td>585</td>\n",
       "      <td>523</td>\n",
       "      <td>446</td>\n",
       "      <td>430</td>\n",
       "      <td>431</td>\n",
       "      <td>339</td>\n",
       "      <td>377</td>\n",
       "      <td>342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r</th>\n",
       "      <td>481</td>\n",
       "      <td>417</td>\n",
       "      <td>590</td>\n",
       "      <td>640</td>\n",
       "      <td>718</td>\n",
       "      <td>799</td>\n",
       "      <td>917</td>\n",
       "      <td>910</td>\n",
       "      <td>1207</td>\n",
       "      <td>1214</td>\n",
       "      <td>...</td>\n",
       "      <td>165377</td>\n",
       "      <td>164821</td>\n",
       "      <td>169878</td>\n",
       "      <td>169452</td>\n",
       "      <td>172069</td>\n",
       "      <td>176490</td>\n",
       "      <td>177207</td>\n",
       "      <td>174632</td>\n",
       "      <td>173200</td>\n",
       "      <td>166064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s</th>\n",
       "      <td>1391</td>\n",
       "      <td>1316</td>\n",
       "      <td>1637</td>\n",
       "      <td>1794</td>\n",
       "      <td>2039</td>\n",
       "      <td>2127</td>\n",
       "      <td>2524</td>\n",
       "      <td>2803</td>\n",
       "      <td>3582</td>\n",
       "      <td>3569</td>\n",
       "      <td>...</td>\n",
       "      <td>143791</td>\n",
       "      <td>139595</td>\n",
       "      <td>138632</td>\n",
       "      <td>139642</td>\n",
       "      <td>139913</td>\n",
       "      <td>143232</td>\n",
       "      <td>142155</td>\n",
       "      <td>137056</td>\n",
       "      <td>129861</td>\n",
       "      <td>123670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t</th>\n",
       "      <td>2152</td>\n",
       "      <td>2165</td>\n",
       "      <td>2399</td>\n",
       "      <td>2554</td>\n",
       "      <td>2825</td>\n",
       "      <td>2889</td>\n",
       "      <td>3017</td>\n",
       "      <td>3140</td>\n",
       "      <td>3816</td>\n",
       "      <td>3784</td>\n",
       "      <td>...</td>\n",
       "      <td>47688</td>\n",
       "      <td>44991</td>\n",
       "      <td>43765</td>\n",
       "      <td>43870</td>\n",
       "      <td>43369</td>\n",
       "      <td>43553</td>\n",
       "      <td>43437</td>\n",
       "      <td>43846</td>\n",
       "      <td>43674</td>\n",
       "      <td>43398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <td>380</td>\n",
       "      <td>427</td>\n",
       "      <td>410</td>\n",
       "      <td>444</td>\n",
       "      <td>490</td>\n",
       "      <td>495</td>\n",
       "      <td>511</td>\n",
       "      <td>476</td>\n",
       "      <td>541</td>\n",
       "      <td>469</td>\n",
       "      <td>...</td>\n",
       "      <td>1833</td>\n",
       "      <td>1819</td>\n",
       "      <td>2052</td>\n",
       "      <td>2138</td>\n",
       "      <td>2129</td>\n",
       "      <td>2201</td>\n",
       "      <td>2311</td>\n",
       "      <td>2405</td>\n",
       "      <td>2417</td>\n",
       "      <td>2318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>v</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1209</td>\n",
       "      <td>1332</td>\n",
       "      <td>1652</td>\n",
       "      <td>1823</td>\n",
       "      <td>1794</td>\n",
       "      <td>2010</td>\n",
       "      <td>2295</td>\n",
       "      <td>2418</td>\n",
       "      <td>2589</td>\n",
       "      <td>2723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>w</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>52265</td>\n",
       "      <td>50103</td>\n",
       "      <td>49079</td>\n",
       "      <td>47556</td>\n",
       "      <td>45464</td>\n",
       "      <td>43217</td>\n",
       "      <td>40251</td>\n",
       "      <td>36937</td>\n",
       "      <td>33181</td>\n",
       "      <td>30656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10691</td>\n",
       "      <td>11009</td>\n",
       "      <td>11718</td>\n",
       "      <td>12399</td>\n",
       "      <td>13025</td>\n",
       "      <td>13992</td>\n",
       "      <td>14306</td>\n",
       "      <td>14834</td>\n",
       "      <td>16640</td>\n",
       "      <td>16352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>10469</td>\n",
       "      <td>10404</td>\n",
       "      <td>12145</td>\n",
       "      <td>12063</td>\n",
       "      <td>13917</td>\n",
       "      <td>13927</td>\n",
       "      <td>14936</td>\n",
       "      <td>14980</td>\n",
       "      <td>17931</td>\n",
       "      <td>17601</td>\n",
       "      <td>...</td>\n",
       "      <td>139109</td>\n",
       "      <td>134557</td>\n",
       "      <td>130569</td>\n",
       "      <td>128367</td>\n",
       "      <td>125190</td>\n",
       "      <td>123707</td>\n",
       "      <td>123397</td>\n",
       "      <td>122633</td>\n",
       "      <td>112922</td>\n",
       "      <td>110425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>z</th>\n",
       "      <td>106</td>\n",
       "      <td>95</td>\n",
       "      <td>106</td>\n",
       "      <td>141</td>\n",
       "      <td>148</td>\n",
       "      <td>150</td>\n",
       "      <td>202</td>\n",
       "      <td>188</td>\n",
       "      <td>238</td>\n",
       "      <td>277</td>\n",
       "      <td>...</td>\n",
       "      <td>2840</td>\n",
       "      <td>2737</td>\n",
       "      <td>2722</td>\n",
       "      <td>2710</td>\n",
       "      <td>2903</td>\n",
       "      <td>3086</td>\n",
       "      <td>3301</td>\n",
       "      <td>3473</td>\n",
       "      <td>3633</td>\n",
       "      <td>3476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26 rows × 262 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sex              F                                                          \\\n",
       "year          1880   1881   1882   1883   1884   1885   1886   1887   1888   \n",
       "last_letter                                                                  \n",
       "a            31446  31581  36536  38330  43680  45408  49100  48942  59442   \n",
       "b              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "c              NaN    NaN      5      5    NaN    NaN    NaN    NaN    NaN   \n",
       "d              609    607    734    810    916    862   1007   1027   1298   \n",
       "e            33378  34080  40399  41914  48089  49616  53884  54353  66750   \n",
       "f              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "g                7      5     12      8     24     11     18     25     44   \n",
       "h             4863   4784   5567   5701   6602   6624   7146   7141   8630   \n",
       "i               61     78     81     76     84     92     85    105    141   \n",
       "j              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "k               13     15     11     17     21     18     27     19     21   \n",
       "l             2541   2911   3527   3848   4808   5144   5721   6175   7900   \n",
       "m               58     57     81     86     79     75    103     90    123   \n",
       "n             3008   2959   3576   3837   4507   4735   5242   5512   6833   \n",
       "o               30     49     35     47     74     84     93     97    134   \n",
       "p              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "q              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "r              481    417    590    640    718    799    917    910   1207   \n",
       "s             1391   1316   1637   1794   2039   2127   2524   2803   3582   \n",
       "t             2152   2165   2399   2554   2825   2889   3017   3140   3816   \n",
       "u              380    427    410    444    490    495    511    476    541   \n",
       "v              NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "w              NaN      5    NaN    NaN    NaN    NaN      5    NaN    NaN   \n",
       "x              NaN    NaN    NaN      7    NaN    NaN    NaN    NaN    NaN   \n",
       "y            10469  10404  12145  12063  13917  13927  14936  14980  17931   \n",
       "z              106     95    106    141    148    150    202    188    238   \n",
       "\n",
       "sex                  ...         M                                          \\\n",
       "year          1889   ...      2001    2002    2003    2004    2005    2006   \n",
       "last_letter          ...                                                     \n",
       "a            58631   ...     39124   38815   37825   38650   36838   36156   \n",
       "b              NaN   ...     50950   49284   48065   45914   43144   42600   \n",
       "c              NaN   ...     27113   27238   27697   26778   26078   26635   \n",
       "d             1374   ...     60838   55829   53391   51754   50670   51410   \n",
       "e            66663   ...    145395  144651  144769  142098  141123  142999   \n",
       "f              NaN   ...      1758    1817    1819    1904    1985    1968   \n",
       "g               28   ...      2151    2084    2009    1837    1882    1929   \n",
       "h             8826   ...     85959   88085   88226   89620   92497   98477   \n",
       "i              134   ...     20980   23610   26011   28500   31317   33558   \n",
       "j              NaN   ...      1069    1088    1203    1094    1291    1241   \n",
       "k               22   ...     42477   42043   42296   41400   42151   42537   \n",
       "l             8395   ...    153648  153493  153862  152800  155312  156234   \n",
       "m              137   ...     41967   42663   42790   43054   41600   42503   \n",
       "n             7103   ...    616099  630322  663419  676011  686326  720998   \n",
       "o              142   ...     82146   83180   85423   88822   92001   96350   \n",
       "p              NaN   ...      3419    3157    2982    2841    2768    2721   \n",
       "q              NaN   ...       602     618     585     523     446     430   \n",
       "r             1214   ...    165377  164821  169878  169452  172069  176490   \n",
       "s             3569   ...    143791  139595  138632  139642  139913  143232   \n",
       "t             3784   ...     47688   44991   43765   43870   43369   43553   \n",
       "u              469   ...      1833    1819    2052    2138    2129    2201   \n",
       "v              NaN   ...      1209    1332    1652    1823    1794    2010   \n",
       "w              NaN   ...     52265   50103   49079   47556   45464   43217   \n",
       "x              NaN   ...     10691   11009   11718   12399   13025   13992   \n",
       "y            17601   ...    139109  134557  130569  128367  125190  123707   \n",
       "z              277   ...      2840    2737    2722    2710    2903    3086   \n",
       "\n",
       "sex                                          \n",
       "year           2007    2008    2009    2010  \n",
       "last_letter                                  \n",
       "a             34654   32901   31430   28438  \n",
       "b             42123   39945   38862   38859  \n",
       "c             26864   25318   24048   23125  \n",
       "d             50595   47910   46172   44398  \n",
       "e            143698  140966  135496  129012  \n",
       "f              2090    2195    2212    2255  \n",
       "g              2040    2059    2396    2666  \n",
       "h             99414  100250   99979   98090  \n",
       "i             35231   38151   40912   42956  \n",
       "j              1254    1381    1416    1459  \n",
       "k             42136   39563   37507   35198  \n",
       "l            155203  150791  143751  133583  \n",
       "m             43860   44316   46278   46808  \n",
       "n            741355  733869  715388  688677  \n",
       "o             96895   91485   86423   81025  \n",
       "p              2739    2637    2595    2409  \n",
       "q               431     339     377     342  \n",
       "r            177207  174632  173200  166064  \n",
       "s            142155  137056  129861  123670  \n",
       "t             43437   43846   43674   43398  \n",
       "u              2311    2405    2417    2318  \n",
       "v              2295    2418    2589    2723  \n",
       "w             40251   36937   33181   30656  \n",
       "x             14306   14834   16640   16352  \n",
       "y            123397  122633  112922  110425  \n",
       "z              3301    3473    3633    3476  \n",
       "\n",
       "[26 rows x 262 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_last_letter = lambda x: x[-1]\n",
    "last_letters = names.name.map(get_last_letter)\n",
    "last_letters.name = 'last_letter'\n",
    "\n",
    "table = names.pivot_table('births', index=last_letters, columns=['sex','year'],aggfunc=sum)\n",
    "table\n",
    "# 名前の最後に登場する文字の年代・男女別の推移"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th colspan=\"3\" halign=\"left\">F</th>\n",
       "      <th colspan=\"3\" halign=\"left\">M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_letter</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>a</th>\n",
       "      <td>108376</td>\n",
       "      <td>691247</td>\n",
       "      <td>670605</td>\n",
       "      <td>977</td>\n",
       "      <td>5204</td>\n",
       "      <td>28438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>694</td>\n",
       "      <td>450</td>\n",
       "      <td>411</td>\n",
       "      <td>3912</td>\n",
       "      <td>38859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>5</td>\n",
       "      <td>49</td>\n",
       "      <td>946</td>\n",
       "      <td>482</td>\n",
       "      <td>15476</td>\n",
       "      <td>23125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>6750</td>\n",
       "      <td>3729</td>\n",
       "      <td>2607</td>\n",
       "      <td>22111</td>\n",
       "      <td>262112</td>\n",
       "      <td>44398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>133569</td>\n",
       "      <td>435013</td>\n",
       "      <td>313833</td>\n",
       "      <td>28655</td>\n",
       "      <td>178823</td>\n",
       "      <td>129012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex               F                      M                \n",
       "year           1910    1960    2010   1910    1960    2010\n",
       "last_letter                                               \n",
       "a            108376  691247  670605    977    5204   28438\n",
       "b               NaN     694     450    411    3912   38859\n",
       "c                 5      49     946    482   15476   23125\n",
       "d              6750    3729    2607  22111  262112   44398\n",
       "e            133569  435013  313833  28655  178823  129012"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ある列を抽出\n",
    "subtable = table.reindex(columns= [1910, 1960, 2010], level='year')\n",
    "subtable.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 比率が知りたいので正規化する\n",
    "letter_prop = subtable / subtable.sum().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1438ffba8>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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T5jbgnQARcQLw68zsjIjxETGxWD8BeAOwanAvRSqXZ5pJkobLgCNWmbkjIi4H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\nZmZWiBtWZmZmZoX8D4bIutC+iqKVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x143698518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, axes = plt.subplots(2, 1, figsize=(10,8))\n",
    "letter_prop['M'].plot(kind='bar', rot=0, ax=axes[0], title='Male')\n",
    "letter_prop['F'].plot(kind='bar', rot=0, ax=axes[1], title='Female',legend=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>last_letter</th>\n",
       "      <th>d</th>\n",
       "      <th>n</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>0.083055</td>\n",
       "      <td>0.153213</td>\n",
       "      <td>0.075760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>0.083247</td>\n",
       "      <td>0.153214</td>\n",
       "      <td>0.077451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>0.085340</td>\n",
       "      <td>0.149560</td>\n",
       "      <td>0.077537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>0.084066</td>\n",
       "      <td>0.151646</td>\n",
       "      <td>0.079144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>0.086120</td>\n",
       "      <td>0.149915</td>\n",
       "      <td>0.080405</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "last_letter         d         n         y\n",
       "year                                     \n",
       "1880         0.083055  0.153213  0.075760\n",
       "1881         0.083247  0.153214  0.077451\n",
       "1882         0.085340  0.149560  0.077537\n",
       "1883         0.084066  0.151646  0.079144\n",
       "1884         0.086120  0.149915  0.080405"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# nで終わる名前が圧倒的に増えてる。つぎは男子のd,n,yの文字の年代別推移を見てみる\n",
    "letter_prop = table / table.sum().astype(float)\n",
    "dny_ts = letter_prop.ix[['d','n','y'],'M'].T\n",
    "dny_ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x143b19710>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TbptCSnoKMzfM5MJaF9Kqdiufv4mBKiktiefmP8dHKz6iZ7Oe3HbRbZxX/TzO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14402ae10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dny_ts.plot(style={'d':'-.','n':'-', 'y':':'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.3.1.3 男の子の名前として定着した女の子の名前"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Leslie', 'Lesley', 'Leslee', 'Lesli', 'Lesly'], dtype=object)"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_names = top1000.name.unique()\n",
    "mask = np.array(['lesl' in x.lower() for x in all_names])\n",
    "lesley_like = all_names[mask]\n",
    "lesley_like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name\n",
       "Leslee      1082\n",
       "Lesley     35022\n",
       "Lesli        929\n",
       "Leslie    370429\n",
       "Lesly      10067\n",
       "Name: births, dtype: int64"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered = top1000[top1000.name.isin(lesley_like)]\n",
    "filtered.groupby('name').births.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "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>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</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 rowspan=\"2\" valign=\"top\">1880</th>\n",
       "      <th>F</th>\n",
       "      <th>654</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.000088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <th>1108</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>M</td>\n",
       "      <td>79</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.000715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1881</th>\n",
       "      <th>F</th>\n",
       "      <th>2523</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>F</td>\n",
       "      <td>11</td>\n",
       "      <td>1881</td>\n",
       "      <td>0.000120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <th>3072</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>M</td>\n",
       "      <td>92</td>\n",
       "      <td>1881</td>\n",
       "      <td>0.000913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <th>F</th>\n",
       "      <th>4593</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>1882</td>\n",
       "      <td>0.000083</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name sex  births  year      prop\n",
       "year sex                                         \n",
       "1880 F   654   Leslie   F       8  1880  0.000088\n",
       "     M   1108  Leslie   M      79  1880  0.000715\n",
       "1881 F   2523  Leslie   F      11  1881  0.000120\n",
       "     M   3072  Leslie   M      92  1881  0.000913\n",
       "1882 F   4593  Leslie   F       9  1882  0.000083"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "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>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</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>2008</th>\n",
       "      <th>F</th>\n",
       "      <th>1587788</th>\n",
       "      <td>Lesly</td>\n",
       "      <td>F</td>\n",
       "      <td>699</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.000371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2009</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">F</th>\n",
       "      <th>1622503</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>F</td>\n",
       "      <td>1975</td>\n",
       "      <td>2009</td>\n",
       "      <td>0.001081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1622845</th>\n",
       "      <td>Lesly</td>\n",
       "      <td>F</td>\n",
       "      <td>598</td>\n",
       "      <td>2009</td>\n",
       "      <td>0.000327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2010</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">F</th>\n",
       "      <th>1657142</th>\n",
       "      <td>Leslie</td>\n",
       "      <td>F</td>\n",
       "      <td>1558</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1657525</th>\n",
       "      <td>Lesly</td>\n",
       "      <td>F</td>\n",
       "      <td>502</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000285</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name sex  births  year      prop\n",
       "year sex                                            \n",
       "2008 F   1587788   Lesly   F     699  2008  0.000371\n",
       "2009 F   1622503  Leslie   F    1975  2009  0.001081\n",
       "         1622845   Lesly   F     598  2009  0.000327\n",
       "2010 F   1657142  Leslie   F    1558  2010  0.000886\n",
       "         1657525   Lesly   F     502  2010  0.000285"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>0.091954</td>\n",
       "      <td>0.908046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>0.106796</td>\n",
       "      <td>0.893204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>0.065693</td>\n",
       "      <td>0.934307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>0.053030</td>\n",
       "      <td>0.946970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>0.107143</td>\n",
       "      <td>0.892857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex          F         M\n",
       "year                    \n",
       "1880  0.091954  0.908046\n",
       "1881  0.106796  0.893204\n",
       "1882  0.065693  0.934307\n",
       "1883  0.053030  0.946970\n",
       "1884  0.107143  0.892857"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table = filtered.pivot_table('births', index='year', columns='sex', aggfunc='sum')\n",
    "table = table.div(table.sum(1), axis=0)\n",
    "table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex   F   M\n",
       "year       \n",
       "2006  1 NaN\n",
       "2007  1 NaN\n",
       "2008  1 NaN\n",
       "2009  1 NaN\n",
       "2010  1 NaN"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1436d6080>"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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INm7cSDKZjBo3bkwxMTFSh2vSPvjgA4qMjKTU1FQaPHiwWV1sl5JJJ3Eioj179lCnTp0K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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1440b5710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table.plot(style={'M':'k-','F':'k--'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**レスリー的な名前の比率が男女で入れ替わったね"
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