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US baby names
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "slideshow": { | |
| "slide_type": "notes" | |
| } | |
| }, | |
| "source": [ | |
| "# US Baby Names 1880-2010\n", | |
| "\n", | |
| "United States Social Security Administration(SSA, 미국사회안전부)에서 1880년부터 지금까지의 출생자의 이름 빈도 데이터를 제공하고 있다. \n", | |
| "\n", | |
| "데이터를 제공하는 URL은 http://www.ssa.gov/oact/babynames/limits.html 이다. names.zip 파일을 내려받아 압축을 풀면 다음과 같은 파일 목록을 볼 수 있다.\n", | |
| "\n", | |
| "```\n", | |
| "$ ls\n", | |
| "NationalReadMe.pdf yob1912.txt yob1945.txt yob1978.txt\n", | |
| "yob1880.txt yob1913.txt yob1946.txt yob1979.txt\n", | |
| "yob1881.txt yob1914.txt yob1947.txt yob1980.txt\n", | |
| "yob1882.txt yob1915.txt yob1948.txt yob1981.txt\n", | |
| "yob1883.txt yob1916.txt yob1949.txt yob1982.txt\n", | |
| "yob1884.txt yob1917.txt yob1950.txt yob1983.txt\n", | |
| "yob1885.txt yob1918.txt yob1951.txt yob1984.txt\n", | |
| "yob1886.txt yob1919.txt yob1952.txt yob1985.txt\n", | |
| "yob1887.txt yob1920.txt yob1953.txt yob1986.txt\n", | |
| "yob1888.txt yob1921.txt yob1954.txt yob1987.txt\n", | |
| "yob1889.txt yob1922.txt yob1955.txt yob1988.txt\n", | |
| "yob1890.txt yob1923.txt yob1956.txt yob1989.txt\n", | |
| "yob1891.txt yob1924.txt yob1957.txt yob1990.txt\n", | |
| "yob1892.txt yob1925.txt yob1958.txt yob1991.txt\n", | |
| "yob1893.txt yob1926.txt yob1959.txt yob1992.txt\n", | |
| "yob1894.txt yob1927.txt yob1960.txt yob1993.txt\n", | |
| "yob1895.txt yob1928.txt yob1961.txt yob1994.txt\n", | |
| "yob1896.txt yob1929.txt yob1962.txt yob1995.txt\n", | |
| "yob1897.txt yob1930.txt yob1963.txt yob1996.txt\n", | |
| "yob1898.txt yob1931.txt yob1964.txt yob1997.txt\n", | |
| "yob1899.txt yob1932.txt yob1965.txt yob1998.txt\n", | |
| "yob1900.txt yob1933.txt yob1966.txt yob1999.txt\n", | |
| "yob1901.txt yob1934.txt yob1967.txt yob2000.txt\n", | |
| "yob1902.txt yob1935.txt yob1968.txt yob2001.txt\n", | |
| "yob1903.txt yob1936.txt yob1969.txt yob2002.txt\n", | |
| "yob1904.txt yob1937.txt yob1970.txt yob2003.txt\n", | |
| "yob1905.txt yob1938.txt yob1971.txt yob2004.txt\n", | |
| "yob1906.txt yob1939.txt yob1972.txt yob2005.txt\n", | |
| "yob1907.txt yob1940.txt yob1973.txt yob2006.txt\n", | |
| "yob1908.txt yob1941.txt yob1974.txt yob2007.txt\n", | |
| "yob1909.txt yob1942.txt yob1975.txt yob2008.txt\n", | |
| "yob1910.txt yob1943.txt yob1976.txt yob2009.txt\n", | |
| "yob1911.txt yob1944.txt yob1977.txt yob2010.txt\n", | |
| "\n", | |
| "$ head yob1880.txt\n", | |
| "Mary,F,7065\n", | |
| "Anna,F,2604\n", | |
| "Emma,F,2003\n", | |
| "Elizabeth,F,1939\n", | |
| "Minnie,F,1746\n", | |
| "Margaret,F,1578\n", | |
| "Ida,F,1472\n", | |
| "Alice,F,1414\n", | |
| "Bertha,F,1320\n", | |
| "Sarah,F,1288\n", | |
| "```\n", | |
| "\n", | |
| "이 데이터로 어떤 분석들이 가능할까?\n", | |
| "\n", | |
| "* 특정 이름의 빈도 변화를 그래프로 표시\n", | |
| "* 각 이름의 상대적인 등수 결정\n", | |
| "* 매년 가장 인기있던 이름과 가장 큰 증감률을 보인 이름\n", | |
| "* 이름 유행 분석 등\n", | |
| "\n", | |
| "그럼 지금부터 pandas로 이 데이터분석을 시작해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## 데이터 로드" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "%matplotlib inline\n", | |
| "import pandas as pd" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "names1880 = pd.read_csv('/Users/yong27/study/pydata/pydata-book/ch02/names/yob1880.txt', names=['name', 'sex', 'births'])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>Margaret</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1578</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>Ida</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1472</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>Alice</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1414</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>Bertha</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1320</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>Sarah</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1288</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>Annie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1258</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>Clara</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1226</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>Ella</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1156</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>Florence</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1063</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>Cora</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1045</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>Martha</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1040</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>Laura</td>\n", | |
| " <td>F</td>\n", | |
| " <td>1012</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>Nellie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>995</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>Grace</td>\n", | |
| " <td>F</td>\n", | |
| " <td>982</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>Carrie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>949</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>Maude</td>\n", | |
| " <td>F</td>\n", | |
| " <td>858</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>Mabel</td>\n", | |
| " <td>F</td>\n", | |
| " <td>808</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>Bessie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>794</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>Jennie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>793</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>Gertrude</td>\n", | |
| " <td>F</td>\n", | |
| " <td>787</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>Julia</td>\n", | |
| " <td>F</td>\n", | |
| " <td>783</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>Hattie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>769</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>Edith</td>\n", | |
| " <td>F</td>\n", | |
| " <td>768</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>Mattie</td>\n", | |
| " <td>F</td>\n", | |
| " <td>704</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>Rose</td>\n", | |
| " <td>F</td>\n", | |
| " <td>700</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1970</th>\n", | |
| " <td>Philo</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1971</th>\n", | |
| " <td>Phineas</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1972</th>\n", | |
| " <td>Presley</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1973</th>\n", | |
| " <td>Ransom</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1974</th>\n", | |
| " <td>Reece</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1975</th>\n", | |
| " <td>Rene</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1976</th>\n", | |
| " <td>Roswell</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1977</th>\n", | |
| " <td>Rowland</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1978</th>\n", | |
| " <td>Sampson</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1979</th>\n", | |
| " <td>Samual</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1980</th>\n", | |
| " <td>Santos</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>Schuyler</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>Sheppard</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>Spurgeon</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>Starling</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>Sylvanus</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>Theadore</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>Theophile</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>Tilmon</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>Tommy</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>Unknown</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>Vann</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>Wes</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>Winston</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>Wood</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>Woodie</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>Worthy</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>Wright</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>York</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>Zachariah</td>\n", | |
| " <td>M</td>\n", | |
| " <td>5</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>2000 rows × 3 columns</p>\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\n", | |
| "5 Margaret F 1578\n", | |
| "6 Ida F 1472\n", | |
| "7 Alice F 1414\n", | |
| "8 Bertha F 1320\n", | |
| "9 Sarah F 1288\n", | |
| "10 Annie F 1258\n", | |
| "11 Clara F 1226\n", | |
| "12 Ella F 1156\n", | |
| "13 Florence F 1063\n", | |
| "14 Cora F 1045\n", | |
| "15 Martha F 1040\n", | |
| "16 Laura F 1012\n", | |
| "17 Nellie F 995\n", | |
| "18 Grace F 982\n", | |
| "19 Carrie F 949\n", | |
| "20 Maude F 858\n", | |
| "21 Mabel F 808\n", | |
| "22 Bessie F 794\n", | |
| "23 Jennie F 793\n", | |
| "24 Gertrude F 787\n", | |
| "25 Julia F 783\n", | |
| "26 Hattie F 769\n", | |
| "27 Edith F 768\n", | |
| "28 Mattie F 704\n", | |
| "29 Rose F 700\n", | |
| "... ... .. ...\n", | |
| "1970 Philo M 5\n", | |
| "1971 Phineas M 5\n", | |
| "1972 Presley M 5\n", | |
| "1973 Ransom M 5\n", | |
| "1974 Reece M 5\n", | |
| "1975 Rene M 5\n", | |
| "1976 Roswell M 5\n", | |
| "1977 Rowland M 5\n", | |
| "1978 Sampson M 5\n", | |
| "1979 Samual M 5\n", | |
| "1980 Santos M 5\n", | |
| "1981 Schuyler M 5\n", | |
| "1982 Sheppard M 5\n", | |
| "1983 Spurgeon M 5\n", | |
| "1984 Starling M 5\n", | |
| "1985 Sylvanus M 5\n", | |
| "1986 Theadore M 5\n", | |
| "1987 Theophile M 5\n", | |
| "1988 Tilmon M 5\n", | |
| "1989 Tommy M 5\n", | |
| "1990 Unknown M 5\n", | |
| "1991 Vann M 5\n", | |
| "1992 Wes M 5\n", | |
| "1993 Winston M 5\n", | |
| "1994 Wood M 5\n", | |
| "1995 Woodie M 5\n", | |
| "1996 Worthy M 5\n", | |
| "1997 Wright M 5\n", | |
| "1998 York M 5\n", | |
| "1999 Zachariah M 5\n", | |
| "\n", | |
| "[2000 rows x 3 columns]" | |
| ] | |
| }, | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "names1880" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "1880년생 이름들이 잘 로드되었다 (상위 2000개 이름들만 제공함). 성별별로 몇명이나 있는지 계산해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "sex\n", | |
| "F 90993\n", | |
| "M 110493\n", | |
| "Name: births, dtype: int64" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "names1880.groupby('sex').births.sum()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "1880년생뿐 아니라 모든 연도 출생자들을 다 로드해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "years = range(1880, 2011)\n", | |
| "pieces = []\n", | |
| "columns = ['name', 'sex', 'births']\n", | |
| "\n", | |
| "for year in years:\n", | |
| " path = '/Users/yong27/study/pydata/pydata-book/ch02/names/yob{}.txt'.format(year)\n", | |
| " frame = pd.read_csv(path, names=columns)\n", | |
| " frame['year'] = year\n", | |
| " pieces.append(frame)\n", | |
| " \n", | |
| "names = pd.concat(pieces, ignore_index=True)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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": 6, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "names" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "모든 연도의 데이터가 다 로드되어 **names**라는 하나의 Dataframe에 저장되었다. 총 1,690,784개의 레코드가 있다. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "total_births = names.pivot_table('births', index='year', columns='sex', aggfunc=sum)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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>90993</td>\n", | |
| " <td>110493</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1881</th>\n", | |
| " <td>91955</td>\n", | |
| " <td>100748</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1882</th>\n", | |
| " <td>107851</td>\n", | |
| " <td>113687</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1883</th>\n", | |
| " <td>112322</td>\n", | |
| " <td>104632</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1884</th>\n", | |
| " <td>129021</td>\n", | |
| " <td>114445</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1885</th>\n", | |
| " <td>133056</td>\n", | |
| " <td>107802</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1886</th>\n", | |
| " <td>144538</td>\n", | |
| " <td>110785</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1887</th>\n", | |
| " <td>145983</td>\n", | |
| " <td>101412</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1888</th>\n", | |
| " <td>178631</td>\n", | |
| " <td>120857</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1889</th>\n", | |
| " <td>178369</td>\n", | |
| " <td>110590</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>190377</td>\n", | |
| " <td>111026</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>185486</td>\n", | |
| " <td>101198</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>212350</td>\n", | |
| " <td>122038</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>212908</td>\n", | |
| " <td>112319</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>222923</td>\n", | |
| " <td>115775</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>233632</td>\n", | |
| " <td>117398</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>237924</td>\n", | |
| " <td>119575</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>234199</td>\n", | |
| " <td>112760</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>258771</td>\n", | |
| " <td>122703</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>233022</td>\n", | |
| " <td>106218</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>299873</td>\n", | |
| " <td>150554</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>239351</td>\n", | |
| " <td>106478</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>264079</td>\n", | |
| " <td>122660</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>261976</td>\n", | |
| " <td>119240</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>275375</td>\n", | |
| " <td>128129</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>291641</td>\n", | |
| " <td>132319</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>295301</td>\n", | |
| " <td>133159</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>318558</td>\n", | |
| " <td>146838</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>334277</td>\n", | |
| " <td>154339</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>347191</td>\n", | |
| " <td>163983</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>1666833</td>\n", | |
| " <td>1789568</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>1692036</td>\n", | |
| " <td>1812642</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>1669486</td>\n", | |
| " <td>1790670</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>1682396</td>\n", | |
| " <td>1802735</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>1719450</td>\n", | |
| " <td>1846162</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>1714053</td>\n", | |
| " <td>1839442</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>1737508</td>\n", | |
| " <td>1865113</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>1779112</td>\n", | |
| " <td>1911858</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>1843057</td>\n", | |
| " <td>1999840</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>1897256</td>\n", | |
| " <td>2052070</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>1874110</td>\n", | |
| " <td>2019018</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>1842818</td>\n", | |
| " <td>1995760</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>1807795</td>\n", | |
| " <td>1959712</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>1784407</td>\n", | |
| " <td>1930363</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>1757240</td>\n", | |
| " <td>1902100</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>1751681</td>\n", | |
| " <td>1892700</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>1739331</td>\n", | |
| " <td>1883571</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>1765390</td>\n", | |
| " <td>1909676</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>1772139</td>\n", | |
| " <td>1918267</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>1813960</td>\n", | |
| " <td>1961702</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>1798284</td>\n", | |
| " <td>1940498</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>1794358</td>\n", | |
| " <td>1938941</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>1824406</td>\n", | |
| " <td>1972439</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>1833005</td>\n", | |
| " <td>1981557</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>1843890</td>\n", | |
| " <td>1993285</td>\n", | |
| " </tr>\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", | |
| "<p>131 rows × 2 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "sex F M\n", | |
| "year \n", | |
| "1880 90993 110493\n", | |
| "1881 91955 100748\n", | |
| "1882 107851 113687\n", | |
| "1883 112322 104632\n", | |
| "1884 129021 114445\n", | |
| "1885 133056 107802\n", | |
| "1886 144538 110785\n", | |
| "1887 145983 101412\n", | |
| "1888 178631 120857\n", | |
| "1889 178369 110590\n", | |
| "1890 190377 111026\n", | |
| "1891 185486 101198\n", | |
| "1892 212350 122038\n", | |
| "1893 212908 112319\n", | |
| "1894 222923 115775\n", | |
| "1895 233632 117398\n", | |
| "1896 237924 119575\n", | |
| "1897 234199 112760\n", | |
| "1898 258771 122703\n", | |
| "1899 233022 106218\n", | |
| "1900 299873 150554\n", | |
| "1901 239351 106478\n", | |
| "1902 264079 122660\n", | |
| "1903 261976 119240\n", | |
| "1904 275375 128129\n", | |
| "1905 291641 132319\n", | |
| "1906 295301 133159\n", | |
| "1907 318558 146838\n", | |
| "1908 334277 154339\n", | |
| "1909 347191 163983\n", | |
| "... ... ...\n", | |
| "1981 1666833 1789568\n", | |
| "1982 1692036 1812642\n", | |
| "1983 1669486 1790670\n", | |
| "1984 1682396 1802735\n", | |
| "1985 1719450 1846162\n", | |
| "1986 1714053 1839442\n", | |
| "1987 1737508 1865113\n", | |
| "1988 1779112 1911858\n", | |
| "1989 1843057 1999840\n", | |
| "1990 1897256 2052070\n", | |
| "1991 1874110 2019018\n", | |
| "1992 1842818 1995760\n", | |
| "1993 1807795 1959712\n", | |
| "1994 1784407 1930363\n", | |
| "1995 1757240 1902100\n", | |
| "1996 1751681 1892700\n", | |
| "1997 1739331 1883571\n", | |
| "1998 1765390 1909676\n", | |
| "1999 1772139 1918267\n", | |
| "2000 1813960 1961702\n", | |
| "2001 1798284 1940498\n", | |
| "2002 1794358 1938941\n", | |
| "2003 1824406 1972439\n", | |
| "2004 1833005 1981557\n", | |
| "2005 1843890 1993285\n", | |
| "2006 1896468 2050234\n", | |
| "2007 1916888 2069242\n", | |
| "2008 1883645 2032310\n", | |
| "2009 1827643 1973359\n", | |
| "2010 1759010 1898382\n", | |
| "\n", | |
| "[131 rows x 2 columns]" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "total_births" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Dataframe.pivot_table 메쏘드는 테이블내 두 컬럼을 결합한다. 이 데이터를 가지고, 매년 남녀 출생수(births)를 차트로 표시해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x108097c18>" | |
| ] | |
| }, | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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ppQGVdOWeleke49AhN7w5MjLdTfXZZ91TEU+fTn/b9IwY4eYSi082xVR8vOvb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\nImJXRKzJy/8ENgIjSA8rP5Q3e6jSt1rHgbYrGr2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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10fd97e48>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "total_births.plot(title='Total births by sex and year')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "매년 남녀 출생수 현황을 한눈에 알 수 있다. 1930년전에는 여자가 많았는데, 그 이후에 남자가 많이지는 점이 이채롭다.\n", | |
| "\n", | |
| "이제, 각 레코드에 \"prop\" 컬럼을 만들고, 해당 이름의 빈도를 추가해보자. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def add_prop(group):\n", | |
| " #births = group.births.astype(float)\n", | |
| " group['prop'] = group.births / group.births.sum()\n", | |
| " return group\n", | |
| "\n", | |
| "names = names.groupby(['year', 'sex']).apply(add_prop)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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": 12, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "names" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "해당 연도, 성별을 그룹으로 하고, 그 그룹에서의 이름 빈도가 추가되었다. 이 빈도가 정확하게 계산되었는지 궁금하다. 한번 확인해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "True" | |
| ] | |
| }, | |
| "execution_count": 13, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "import numpy as np\n", | |
| "np.allclose(names.groupby(['year', 'sex']).prop.sum(), 1)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "오케이. 이제부터 매년, 각 성별별로 특정 이름의 빈도 변화를 살펴보자. 매년, 각 성별별(그룹별)로 데이터수가 다르니, 그룹별 top1000만 쓰기로 하자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def get_top1000(group):\n", | |
| " return group.sort_values(by='births', ascending=False)[:1000]\n", | |
| "\n", | |
| "grouped = names.groupby(['year', 'sex'])\n", | |
| "top1000 = grouped.apply(get_top1000)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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": 15, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "top1000" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "이로서 top1000 변수에 그룹별 1000개의 이름이 정리됐다. \n", | |
| "\n", | |
| "## 이름 유행 분석\n", | |
| "\n", | |
| "이름 유행 분석을 해보자. 먼저 top1000을 boys, girls로 분리해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "boys = top1000[top1000.sex == 'M']\n", | |
| "girls = top1000[top1000.sex == 'F']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "그리고, top1000을 피벗테이블로 펼쳐보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "total_births = top1000.pivot_table('births', index='year', columns='name', aggfunc=sum)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
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| " <td>NaN</td>\n", | |
| " <td>62.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>28.0</td>\n", | |
| " <td>65.0</td>\n", | |
| " <td>83.0</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>71.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>87.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>27.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>49.0</td>\n", | |
| " <td>6.0</td>\n", | |
| " <td>31.0</td>\n", | |
| " <td>56.0</td>\n", | |
| " <td>60.0</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>104.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>112.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>26.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>48.0</td>\n", | |
| " <td>9.0</td>\n", | |
| " <td>44.0</td>\n", | |
| " <td>99.0</td>\n", | |
| " <td>71.0</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>80.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>87.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>26.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>56.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>31.0</td>\n", | |
| " <td>58.0</td>\n", | |
| " <td>57.0</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>78.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>91.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>34.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>58.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>23.0</td>\n", | |
| " <td>58.0</td>\n", | |
| " <td>66.0</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>93.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>91.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>19.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>64.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>41.0</td>\n", | |
| " <td>83.0</td>\n", | |
| " <td>74.0</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>117.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>80.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>27.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>46.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>35.0</td>\n", | |
| " <td>54.0</td>\n", | |
| " <td>74.0</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>96.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>73.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>24.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>66.0</td>\n", | |
| " <td>8.0</td>\n", | |
| " <td>24.0</td>\n", | |
| " <td>55.0</td>\n", | |
| " <td>61.0</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>96.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>72.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>19.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>59.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>37.0</td>\n", | |
| " <td>64.0</td>\n", | |
| " <td>58.0</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>130.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>79.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>19.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>53.0</td>\n", | |
| " <td>11.0</td>\n", | |
| " <td>39.0</td>\n", | |
| " <td>92.0</td>\n", | |
| " <td>72.0</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>114.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>84.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>23.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>70.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>31.0</td>\n", | |
| " <td>59.0</td>\n", | |
| " <td>53.0</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>142.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>57.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>22.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>59.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>39.0</td>\n", | |
| " <td>57.0</td>\n", | |
| " <td>76.0</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>14832.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>383.0</td>\n", | |
| " <td>292.0</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>14538.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>372.0</td>\n", | |
| " <td>275.0</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>14627.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>419.0</td>\n", | |
| " <td>223.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>174.0</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>13387.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>357.0</td>\n", | |
| " <td>249.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>200.0</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>13123.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>314.0</td>\n", | |
| " <td>233.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>193.0</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>12685.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>369.0</td>\n", | |
| " <td>228.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>213.0</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>12676.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>327.0</td>\n", | |
| " <td>228.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>248.0</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>14393.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>404.0</td>\n", | |
| " <td>226.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>238.0</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>15312.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>470.0</td>\n", | |
| " <td>265.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>376.0</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>14545.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>507.0</td>\n", | |
| " <td>311.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>478.0</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>14240.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>451.0</td>\n", | |
| " <td>278.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>722.0</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>14494.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>430.0</td>\n", | |
| " <td>260.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>978.0</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>13819.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>503.0</td>\n", | |
| " <td>291.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>1194.0</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>1451.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>14379.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>597.0</td>\n", | |
| " <td>351.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>1332.0</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>1254.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>13277.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>549.0</td>\n", | |
| " <td>351.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>1726.0</td>\n", | |
| " <td>219.0</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>831.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>11956.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>552.0</td>\n", | |
| " <td>349.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2063.0</td>\n", | |
| " <td>339.0</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>1737.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>11156.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>645.0</td>\n", | |
| " <td>386.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2363.0</td>\n", | |
| " <td>407.0</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>1399.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>10539.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>661.0</td>\n", | |
| " <td>398.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2690.0</td>\n", | |
| " <td>478.0</td>\n", | |
| " <td>225.0</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>1088.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>9846.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>211.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>710.0</td>\n", | |
| " <td>430.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>3238.0</td>\n", | |
| " <td>561.0</td>\n", | |
| " <td>257.0</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>1494.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>9548.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>222.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>660.0</td>\n", | |
| " <td>432.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>3783.0</td>\n", | |
| " <td>691.0</td>\n", | |
| " <td>320.0</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>3351.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>9529.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>244.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>687.0</td>\n", | |
| " <td>526.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>4642.0</td>\n", | |
| " <td>822.0</td>\n", | |
| " <td>439.0</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>4775.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>8993.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>256.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>600.0</td>\n", | |
| " <td>514.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>4883.0</td>\n", | |
| " <td>1182.0</td>\n", | |
| " <td>438.0</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>3670.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>8851.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>276.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>625.0</td>\n", | |
| " <td>536.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5080.0</td>\n", | |
| " <td>1465.0</td>\n", | |
| " <td>448.0</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>3482.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>8381.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>258.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>504.0</td>\n", | |
| " <td>500.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5359.0</td>\n", | |
| " <td>1621.0</td>\n", | |
| " <td>515.0</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>3452.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>7796.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>287.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>451.0</td>\n", | |
| " <td>445.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>4953.0</td>\n", | |
| " <td>2266.0</td>\n", | |
| " <td>502.0</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>3737.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>8279.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>297.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>404.0</td>\n", | |
| " <td>440.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5145.0</td>\n", | |
| " <td>2839.0</td>\n", | |
| " <td>530.0</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>3941.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>8914.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>313.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>349.0</td>\n", | |
| " <td>468.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>4925.0</td>\n", | |
| " <td>3028.0</td>\n", | |
| " <td>526.0</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>955.0</td>\n", | |
| " <td>4028.0</td>\n", | |
| " <td>219.0</td>\n", | |
| " <td>8511.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>317.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>344.0</td>\n", | |
| " <td>400.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>4764.0</td>\n", | |
| " <td>3438.0</td>\n", | |
| " <td>492.0</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>1265.0</td>\n", | |
| " <td>4352.0</td>\n", | |
| " <td>270.0</td>\n", | |
| " <td>7936.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>296.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>307.0</td>\n", | |
| " <td>369.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5120.0</td>\n", | |
| " <td>3981.0</td>\n", | |
| " <td>496.0</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>448.0</td>\n", | |
| " <td>4628.0</td>\n", | |
| " <td>438.0</td>\n", | |
| " <td>7374.0</td>\n", | |
| " <td>226.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>277.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>295.0</td>\n", | |
| " <td>324.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>6200.0</td>\n", | |
| " <td>5164.0</td>\n", | |
| " <td>504.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>258.0</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 \\\n", | |
| "year \n", | |
| "1880 NaN NaN NaN 102.0 NaN NaN NaN NaN NaN \n", | |
| "1881 NaN NaN NaN 94.0 NaN NaN NaN NaN NaN \n", | |
| "1882 NaN NaN NaN 85.0 NaN NaN NaN NaN NaN \n", | |
| "1883 NaN NaN NaN 105.0 NaN NaN NaN NaN NaN \n", | |
| "1884 NaN NaN NaN 97.0 NaN NaN NaN NaN NaN \n", | |
| "1885 NaN NaN NaN 88.0 NaN 6.0 NaN NaN NaN \n", | |
| "1886 NaN NaN NaN 86.0 NaN NaN NaN NaN NaN \n", | |
| "1887 NaN NaN NaN 78.0 NaN NaN NaN NaN NaN \n", | |
| "1888 NaN NaN NaN 90.0 NaN NaN NaN NaN NaN \n", | |
| "1889 NaN NaN NaN 85.0 NaN NaN NaN NaN NaN \n", | |
| "1890 NaN NaN NaN 96.0 NaN NaN NaN 6.0 NaN \n", | |
| "1891 NaN NaN NaN 69.0 NaN NaN NaN NaN NaN \n", | |
| "1892 NaN NaN NaN 95.0 NaN NaN NaN NaN NaN \n", | |
| "1893 NaN NaN NaN 81.0 NaN NaN NaN NaN NaN \n", | |
| "1894 NaN NaN NaN 79.0 NaN NaN NaN NaN NaN \n", | |
| "1895 NaN NaN NaN 94.0 NaN NaN NaN NaN NaN \n", | |
| "1896 NaN NaN NaN 69.0 NaN NaN NaN NaN NaN \n", | |
| "1897 NaN NaN NaN 87.0 NaN NaN NaN NaN NaN \n", | |
| "1898 NaN NaN NaN 89.0 NaN NaN NaN NaN NaN \n", | |
| "1899 NaN NaN NaN 71.0 NaN NaN NaN NaN NaN \n", | |
| "1900 NaN NaN NaN 104.0 NaN NaN NaN NaN NaN \n", | |
| "1901 NaN NaN NaN 80.0 NaN NaN NaN NaN NaN \n", | |
| "1902 NaN NaN NaN 78.0 NaN NaN NaN NaN NaN \n", | |
| "1903 NaN NaN NaN 93.0 NaN NaN NaN NaN NaN \n", | |
| "1904 NaN NaN NaN 117.0 NaN NaN NaN NaN NaN \n", | |
| "1905 NaN NaN NaN 96.0 NaN NaN NaN NaN NaN \n", | |
| "1906 NaN NaN NaN 96.0 NaN NaN NaN NaN NaN \n", | |
| "1907 NaN NaN NaN 130.0 NaN NaN NaN NaN NaN \n", | |
| "1908 NaN NaN NaN 114.0 NaN NaN NaN NaN NaN \n", | |
| "1909 NaN NaN NaN 142.0 NaN NaN NaN NaN NaN \n", | |
| "... ... ... ... ... ... ... ... ... ... \n", | |
| "1981 NaN NaN NaN 14832.0 NaN NaN NaN NaN 383.0 \n", | |
| "1982 NaN NaN NaN 14538.0 NaN NaN NaN NaN 372.0 \n", | |
| "1983 NaN NaN NaN 14627.0 NaN NaN NaN NaN 419.0 \n", | |
| "1984 NaN NaN NaN 13387.0 NaN NaN NaN NaN 357.0 \n", | |
| "1985 NaN NaN NaN 13123.0 NaN NaN NaN NaN 314.0 \n", | |
| "1986 NaN NaN NaN 12685.0 NaN NaN NaN NaN 369.0 \n", | |
| "1987 NaN NaN NaN 12676.0 NaN NaN NaN NaN 327.0 \n", | |
| "1988 NaN NaN NaN 14393.0 NaN NaN NaN NaN 404.0 \n", | |
| "1989 NaN NaN NaN 15312.0 NaN NaN NaN NaN 470.0 \n", | |
| "1990 NaN NaN NaN 14545.0 NaN NaN NaN NaN 507.0 \n", | |
| "1991 NaN NaN NaN 14240.0 NaN NaN NaN NaN 451.0 \n", | |
| "1992 NaN NaN NaN 14494.0 NaN NaN NaN NaN 430.0 \n", | |
| "1993 NaN NaN NaN 13819.0 NaN NaN NaN NaN 503.0 \n", | |
| "1994 NaN 1451.0 NaN 14379.0 NaN NaN NaN NaN 597.0 \n", | |
| "1995 NaN 1254.0 NaN 13277.0 NaN NaN NaN NaN 549.0 \n", | |
| "1996 NaN 831.0 NaN 11956.0 NaN NaN NaN NaN 552.0 \n", | |
| "1997 NaN 1737.0 NaN 11156.0 NaN NaN NaN NaN 645.0 \n", | |
| "1998 NaN 1399.0 NaN 10539.0 NaN NaN NaN NaN 661.0 \n", | |
| "1999 NaN 1088.0 NaN 9846.0 NaN NaN 211.0 NaN 710.0 \n", | |
| "2000 NaN 1494.0 NaN 9548.0 NaN NaN 222.0 NaN 660.0 \n", | |
| "2001 NaN 3351.0 NaN 9529.0 NaN NaN 244.0 NaN 687.0 \n", | |
| "2002 NaN 4775.0 NaN 8993.0 NaN NaN 256.0 NaN 600.0 \n", | |
| "2003 NaN 3670.0 NaN 8851.0 NaN NaN 276.0 NaN 625.0 \n", | |
| "2004 NaN 3482.0 NaN 8381.0 NaN NaN 258.0 NaN 504.0 \n", | |
| "2005 NaN 3452.0 NaN 7796.0 NaN NaN 287.0 NaN 451.0 \n", | |
| "2006 NaN 3737.0 NaN 8279.0 NaN NaN 297.0 NaN 404.0 \n", | |
| "2007 NaN 3941.0 NaN 8914.0 NaN NaN 313.0 NaN 349.0 \n", | |
| "2008 955.0 4028.0 219.0 8511.0 NaN NaN 317.0 NaN 344.0 \n", | |
| "2009 1265.0 4352.0 270.0 7936.0 NaN NaN 296.0 NaN 307.0 \n", | |
| "2010 448.0 4628.0 438.0 7374.0 226.0 NaN 277.0 NaN 295.0 \n", | |
| "\n", | |
| "name Abbie ... Zoa Zoe Zoey Zoie Zola Zollie Zona Zora \\\n", | |
| "year ... \n", | |
| "1880 71.0 ... 8.0 23.0 NaN NaN 7.0 NaN 8.0 28.0 \n", | |
| "1881 81.0 ... NaN 22.0 NaN NaN 10.0 NaN 9.0 21.0 \n", | |
| "1882 80.0 ... 8.0 25.0 NaN NaN 9.0 NaN 17.0 32.0 \n", | |
| "1883 79.0 ... NaN 23.0 NaN NaN 10.0 NaN 11.0 35.0 \n", | |
| "1884 98.0 ... 13.0 31.0 NaN NaN 14.0 6.0 8.0 58.0 \n", | |
| "1885 88.0 ... 6.0 27.0 NaN NaN 12.0 6.0 14.0 48.0 \n", | |
| "1886 84.0 ... 13.0 25.0 NaN NaN 8.0 NaN 20.0 52.0 \n", | |
| "1887 104.0 ... 9.0 34.0 NaN NaN 23.0 NaN 28.0 46.0 \n", | |
| "1888 137.0 ... 11.0 42.0 NaN NaN 23.0 7.0 30.0 42.0 \n", | |
| "1889 107.0 ... 14.0 29.0 NaN NaN 22.0 NaN 29.0 53.0 \n", | |
| "1890 140.0 ... NaN 42.0 NaN NaN 32.0 7.0 27.0 60.0 \n", | |
| "1891 124.0 ... NaN 34.0 NaN NaN 29.0 6.0 14.0 52.0 \n", | |
| "1892 119.0 ... NaN 34.0 NaN NaN 27.0 NaN 25.0 66.0 \n", | |
| "1893 115.0 ... NaN 23.0 NaN NaN 34.0 6.0 15.0 67.0 \n", | |
| "1894 118.0 ... NaN 28.0 NaN NaN 51.0 NaN 23.0 66.0 \n", | |
| "1895 92.0 ... NaN 34.0 NaN NaN 60.0 11.0 38.0 55.0 \n", | |
| "1896 121.0 ... NaN 36.0 NaN NaN 47.0 NaN 38.0 72.0 \n", | |
| "1897 97.0 ... NaN 35.0 NaN NaN 51.0 NaN 28.0 67.0 \n", | |
| "1898 120.0 ... NaN 30.0 NaN NaN 62.0 NaN 28.0 65.0 \n", | |
| "1899 87.0 ... NaN 27.0 NaN NaN 49.0 6.0 31.0 56.0 \n", | |
| "1900 112.0 ... NaN 26.0 NaN NaN 48.0 9.0 44.0 99.0 \n", | |
| "1901 87.0 ... NaN 26.0 NaN NaN 56.0 NaN 31.0 58.0 \n", | |
| "1902 91.0 ... NaN 34.0 NaN NaN 58.0 NaN 23.0 58.0 \n", | |
| "1903 91.0 ... NaN 19.0 NaN NaN 64.0 NaN 41.0 83.0 \n", | |
| "1904 80.0 ... NaN 27.0 NaN NaN 46.0 NaN 35.0 54.0 \n", | |
| "1905 73.0 ... NaN 24.0 NaN NaN 66.0 8.0 24.0 55.0 \n", | |
| "1906 72.0 ... NaN 19.0 NaN NaN 59.0 NaN 37.0 64.0 \n", | |
| "1907 79.0 ... NaN 19.0 NaN NaN 53.0 11.0 39.0 92.0 \n", | |
| "1908 84.0 ... NaN 23.0 NaN NaN 70.0 NaN 31.0 59.0 \n", | |
| "1909 57.0 ... NaN 22.0 NaN NaN 59.0 NaN 39.0 57.0 \n", | |
| "... ... ... ... ... ... ... ... ... ... ... \n", | |
| "1981 292.0 ... NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
| "1982 275.0 ... NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
| "1983 223.0 ... NaN 174.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1984 249.0 ... NaN 200.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1985 233.0 ... NaN 193.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1986 228.0 ... NaN 213.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1987 228.0 ... NaN 248.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1988 226.0 ... NaN 238.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1989 265.0 ... NaN 376.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1990 311.0 ... NaN 478.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1991 278.0 ... NaN 722.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1992 260.0 ... NaN 978.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1993 291.0 ... NaN 1194.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1994 351.0 ... NaN 1332.0 NaN NaN NaN NaN NaN NaN \n", | |
| "1995 351.0 ... NaN 1726.0 219.0 NaN NaN NaN NaN NaN \n", | |
| "1996 349.0 ... NaN 2063.0 339.0 NaN NaN NaN NaN NaN \n", | |
| "1997 386.0 ... NaN 2363.0 407.0 NaN NaN NaN NaN NaN \n", | |
| "1998 398.0 ... NaN 2690.0 478.0 225.0 NaN NaN NaN NaN \n", | |
| "1999 430.0 ... NaN 3238.0 561.0 257.0 NaN NaN NaN NaN \n", | |
| "2000 432.0 ... NaN 3783.0 691.0 320.0 NaN NaN NaN NaN \n", | |
| "2001 526.0 ... NaN 4642.0 822.0 439.0 NaN NaN NaN NaN \n", | |
| "2002 514.0 ... NaN 4883.0 1182.0 438.0 NaN NaN NaN NaN \n", | |
| "2003 536.0 ... NaN 5080.0 1465.0 448.0 NaN NaN NaN NaN \n", | |
| "2004 500.0 ... NaN 5359.0 1621.0 515.0 NaN NaN NaN NaN \n", | |
| "2005 445.0 ... NaN 4953.0 2266.0 502.0 NaN NaN NaN NaN \n", | |
| "2006 440.0 ... NaN 5145.0 2839.0 530.0 NaN NaN NaN NaN \n", | |
| "2007 468.0 ... NaN 4925.0 3028.0 526.0 NaN NaN NaN NaN \n", | |
| "2008 400.0 ... NaN 4764.0 3438.0 492.0 NaN NaN NaN NaN \n", | |
| "2009 369.0 ... NaN 5120.0 3981.0 496.0 NaN NaN NaN NaN \n", | |
| "2010 324.0 ... NaN 6200.0 5164.0 504.0 NaN NaN NaN NaN \n", | |
| "\n", | |
| "name Zula Zuri \n", | |
| "year \n", | |
| "1880 27.0 NaN \n", | |
| "1881 27.0 NaN \n", | |
| "1882 21.0 NaN \n", | |
| "1883 25.0 NaN \n", | |
| "1884 27.0 NaN \n", | |
| "1885 38.0 NaN \n", | |
| "1886 43.0 NaN \n", | |
| "1887 33.0 NaN \n", | |
| "1888 45.0 NaN \n", | |
| "1889 55.0 NaN \n", | |
| "1890 65.0 NaN \n", | |
| "1891 45.0 NaN \n", | |
| "1892 53.0 NaN \n", | |
| "1893 70.0 NaN \n", | |
| "1894 64.0 NaN \n", | |
| "1895 55.0 NaN \n", | |
| "1896 65.0 NaN \n", | |
| "1897 79.0 NaN \n", | |
| "1898 83.0 NaN \n", | |
| "1899 60.0 NaN \n", | |
| "1900 71.0 NaN \n", | |
| "1901 57.0 NaN \n", | |
| "1902 66.0 NaN \n", | |
| "1903 74.0 NaN \n", | |
| "1904 74.0 NaN \n", | |
| "1905 61.0 NaN \n", | |
| "1906 58.0 NaN \n", | |
| "1907 72.0 NaN \n", | |
| "1908 53.0 NaN \n", | |
| "1909 76.0 NaN \n", | |
| "... ... ... \n", | |
| "1981 NaN NaN \n", | |
| "1982 NaN NaN \n", | |
| "1983 NaN NaN \n", | |
| "1984 NaN NaN \n", | |
| "1985 NaN NaN \n", | |
| "1986 NaN NaN \n", | |
| "1987 NaN NaN \n", | |
| "1988 NaN NaN \n", | |
| "1989 NaN NaN \n", | |
| "1990 NaN NaN \n", | |
| "1991 NaN NaN \n", | |
| "1992 NaN NaN \n", | |
| "1993 NaN NaN \n", | |
| "1994 NaN NaN \n", | |
| "1995 NaN NaN \n", | |
| "1996 NaN NaN \n", | |
| "1997 NaN NaN \n", | |
| "1998 NaN NaN \n", | |
| "1999 NaN NaN \n", | |
| "2000 NaN NaN \n", | |
| "2001 NaN NaN \n", | |
| "2002 NaN NaN \n", | |
| "2003 NaN NaN \n", | |
| "2004 NaN NaN \n", | |
| "2005 NaN NaN \n", | |
| "2006 NaN NaN \n", | |
| "2007 NaN NaN \n", | |
| "2008 NaN NaN \n", | |
| "2009 NaN NaN \n", | |
| "2010 NaN 258.0 \n", | |
| "\n", | |
| "[131 rows x 6868 columns]" | |
| ] | |
| }, | |
| "execution_count": 19, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "total_births" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "이름이 너무 많으니, 관심있는 이름 John, Harry, Mary, Marilyn만 확인해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 20, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "subset = total_births[['John', 'Harry', 'Mary', 'Marilyn']]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "이 4명을 차트로 표시해보면," | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 21, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "array([<matplotlib.axes._subplots.AxesSubplot object at 0x10bce0a20>,\n", | |
| " <matplotlib.axes._subplots.AxesSubplot object at 0x10c1cccf8>,\n", | |
| " <matplotlib.axes._subplots.AxesSubplot object at 0x10beb8f28>,\n", | |
| " <matplotlib.axes._subplots.AxesSubplot object at 0x10bef54e0>], dtype=object)" | |
| ] | |
| }, | |
| "execution_count": 21, | |
| "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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\nbWKXtU3ssraJXdY2sWuotE2sB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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10bce0240>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "subset.plot(subplots=True, figsize=(12, 10), grid=False, title='Number of births per year')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "각 이름별로 매년 어떻게 변화하는지 한눈에 확인이 가능하다.\n", | |
| "\n", | |
| "## 이름 다양성 증가 확인\n", | |
| "\n", | |
| "위 차트의 설명 가운데 하나는 부모들이 점점 일반적인 이름을 쓰지 않기 때문일 수 있다. 정말 그러한지 확인해보자. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 22, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "table = top1000.pivot_table('prop', index='year', columns='sex', aggfunc=sum)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 24, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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>1.000000</td>\n", | |
| " <td>0.997375</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1881</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>1.000000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1882</th>\n", | |
| " <td>0.998702</td>\n", | |
| " <td>0.995646</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1883</th>\n", | |
| " <td>0.997596</td>\n", | |
| " <td>0.998566</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1884</th>\n", | |
| " <td>0.993156</td>\n", | |
| " <td>0.994539</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1885</th>\n", | |
| " <td>0.992251</td>\n", | |
| " <td>0.995501</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1886</th>\n", | |
| " <td>0.989504</td>\n", | |
| " <td>0.995035</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1887</th>\n", | |
| " <td>0.988279</td>\n", | |
| " <td>0.996697</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1888</th>\n", | |
| " <td>0.984241</td>\n", | |
| " <td>0.992429</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1889</th>\n", | |
| " <td>0.984061</td>\n", | |
| " <td>0.994981</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>0.982566</td>\n", | |
| " <td>0.992749</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>0.982177</td>\n", | |
| " <td>0.993725</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>0.979746</td>\n", | |
| " <td>0.988815</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>0.980001</td>\n", | |
| " <td>0.991720</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>0.978571</td>\n", | |
| " <td>0.989048</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>0.975479</td>\n", | |
| " <td>0.989071</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>0.975660</td>\n", | |
| " <td>0.988041</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>0.976558</td>\n", | |
| " <td>0.989349</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>0.972806</td>\n", | |
| " <td>0.987197</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>0.975170</td>\n", | |
| " <td>0.990115</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>0.967760</td>\n", | |
| " <td>0.979702</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>0.972304</td>\n", | |
| " <td>0.989603</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>0.970467</td>\n", | |
| " <td>0.985749</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>0.969490</td>\n", | |
| " <td>0.986020</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>0.968142</td>\n", | |
| " <td>0.982502</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>0.967038</td>\n", | |
| " <td>0.981650</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>0.967535</td>\n", | |
| " <td>0.981759</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>0.964942</td>\n", | |
| " <td>0.976975</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>0.964500</td>\n", | |
| " <td>0.976409</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>0.962744</td>\n", | |
| " <td>0.973412</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>0.867232</td>\n", | |
| " <td>0.944762</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>0.868208</td>\n", | |
| " <td>0.944435</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>0.871602</td>\n", | |
| " <td>0.945170</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>0.870201</td>\n", | |
| " <td>0.944705</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>0.866046</td>\n", | |
| " <td>0.942412</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>0.862619</td>\n", | |
| " <td>0.939833</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>0.858719</td>\n", | |
| " <td>0.937574</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>0.852520</td>\n", | |
| " <td>0.934236</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>0.846535</td>\n", | |
| " <td>0.928314</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>0.840591</td>\n", | |
| " <td>0.926585</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>0.835156</td>\n", | |
| " <td>0.923316</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>0.829654</td>\n", | |
| " <td>0.919513</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>0.826035</td>\n", | |
| " <td>0.915127</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>0.823227</td>\n", | |
| " <td>0.911285</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>0.821738</td>\n", | |
| " <td>0.909356</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>0.817149</td>\n", | |
| " <td>0.905296</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>0.811416</td>\n", | |
| " <td>0.901020</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>0.805665</td>\n", | |
| " <td>0.896381</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>0.799804</td>\n", | |
| " <td>0.892714</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>0.791455</td>\n", | |
| " <td>0.887008</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>0.784125</td>\n", | |
| " <td>0.882799</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>0.780403</td>\n", | |
| " <td>0.879775</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>0.774850</td>\n", | |
| " <td>0.876747</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>0.767291</td>\n", | |
| " <td>0.870077</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>0.762426</td>\n", | |
| " <td>0.866514</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2006</th>\n", | |
| " <td>0.753153</td>\n", | |
| " <td>0.860368</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2007</th>\n", | |
| " <td>0.745959</td>\n", | |
| " <td>0.855159</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2008</th>\n", | |
| " <td>0.740933</td>\n", | |
| " <td>0.850003</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2009</th>\n", | |
| " <td>0.737290</td>\n", | |
| " <td>0.845256</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2010</th>\n", | |
| " <td>0.736780</td>\n", | |
| " <td>0.843156</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>131 rows × 2 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "sex F M\n", | |
| "year \n", | |
| "1880 1.000000 0.997375\n", | |
| "1881 1.000000 1.000000\n", | |
| "1882 0.998702 0.995646\n", | |
| "1883 0.997596 0.998566\n", | |
| "1884 0.993156 0.994539\n", | |
| "1885 0.992251 0.995501\n", | |
| "1886 0.989504 0.995035\n", | |
| "1887 0.988279 0.996697\n", | |
| "1888 0.984241 0.992429\n", | |
| "1889 0.984061 0.994981\n", | |
| "1890 0.982566 0.992749\n", | |
| "1891 0.982177 0.993725\n", | |
| "1892 0.979746 0.988815\n", | |
| "1893 0.980001 0.991720\n", | |
| "1894 0.978571 0.989048\n", | |
| "1895 0.975479 0.989071\n", | |
| "1896 0.975660 0.988041\n", | |
| "1897 0.976558 0.989349\n", | |
| "1898 0.972806 0.987197\n", | |
| "1899 0.975170 0.990115\n", | |
| "1900 0.967760 0.979702\n", | |
| "1901 0.972304 0.989603\n", | |
| "1902 0.970467 0.985749\n", | |
| "1903 0.969490 0.986020\n", | |
| "1904 0.968142 0.982502\n", | |
| "1905 0.967038 0.981650\n", | |
| "1906 0.967535 0.981759\n", | |
| "1907 0.964942 0.976975\n", | |
| "1908 0.964500 0.976409\n", | |
| "1909 0.962744 0.973412\n", | |
| "... ... ...\n", | |
| "1981 0.867232 0.944762\n", | |
| "1982 0.868208 0.944435\n", | |
| "1983 0.871602 0.945170\n", | |
| "1984 0.870201 0.944705\n", | |
| "1985 0.866046 0.942412\n", | |
| "1986 0.862619 0.939833\n", | |
| "1987 0.858719 0.937574\n", | |
| "1988 0.852520 0.934236\n", | |
| "1989 0.846535 0.928314\n", | |
| "1990 0.840591 0.926585\n", | |
| "1991 0.835156 0.923316\n", | |
| "1992 0.829654 0.919513\n", | |
| "1993 0.826035 0.915127\n", | |
| "1994 0.823227 0.911285\n", | |
| "1995 0.821738 0.909356\n", | |
| "1996 0.817149 0.905296\n", | |
| "1997 0.811416 0.901020\n", | |
| "1998 0.805665 0.896381\n", | |
| "1999 0.799804 0.892714\n", | |
| "2000 0.791455 0.887008\n", | |
| "2001 0.784125 0.882799\n", | |
| "2002 0.780403 0.879775\n", | |
| "2003 0.774850 0.876747\n", | |
| "2004 0.767291 0.870077\n", | |
| "2005 0.762426 0.866514\n", | |
| "2006 0.753153 0.860368\n", | |
| "2007 0.745959 0.855159\n", | |
| "2008 0.740933 0.850003\n", | |
| "2009 0.737290 0.845256\n", | |
| "2010 0.736780 0.843156\n", | |
| "\n", | |
| "[131 rows x 2 columns]" | |
| ] | |
| }, | |
| "execution_count": 24, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "table" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 25, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x10c7dc1d0>" | |
| ] | |
| }, | |
| "execution_count": 25, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10ce3f0b8>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "table.plot(title='Sum of table1000.prop by year and sex', yticks=np.linspace(0, 1.2, 13), xticks=range(1880, 2020, 10))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "그룹별 1000개 레코드의 이름빈도의 합계가 시간이 지날수록 1에서 멀어지는 걸 보아, 다양성이 증가하고 있음을 유추할 수 있다.\n", | |
| "\n", | |
| "또 다른 계산방법으로, 이름빈도로 정렬했을 때, 50%에 도달할 때, 몇명이 있는지 확인할 수 있다. 많을수록 다양하다고 유추할 수 있다. 예를 들어 2010년 출생 남자들은," | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 26, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "df = boys[boys.year == 2010]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 27, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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": 27, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 28, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "prop_cumsum = df.sort_values(by='prop', ascending=False).prop.cumsum()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 30, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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", | |
| " 1676654 0.097648\n", | |
| " 1676655 0.105406\n", | |
| " 1676656 0.112852\n", | |
| " 1676657 0.120276\n", | |
| " 1676658 0.127672\n", | |
| " 1676659 0.135023\n", | |
| " 1676660 0.142368\n", | |
| " 1676661 0.149603\n", | |
| " 1676662 0.156827\n", | |
| " 1676663 0.164021\n", | |
| " 1676664 0.170722\n", | |
| " 1676665 0.177191\n", | |
| " 1676666 0.183452\n", | |
| " 1676667 0.189655\n", | |
| " 1676668 0.195815\n", | |
| " 1676669 0.201832\n", | |
| " 1676670 0.207769\n", | |
| " 1676671 0.213578\n", | |
| " 1676672 0.219354\n", | |
| " 1676673 0.225070\n", | |
| " ... \n", | |
| " 1677613 0.840147\n", | |
| " 1677615 0.840252\n", | |
| " 1677616 0.840358\n", | |
| " 1677617 0.840464\n", | |
| " 1677618 0.840569\n", | |
| " 1677619 0.840675\n", | |
| " 1677620 0.840780\n", | |
| " 1677621 0.840885\n", | |
| " 1677622 0.840990\n", | |
| " 1677623 0.841095\n", | |
| " 1677624 0.841199\n", | |
| " 1677625 0.841303\n", | |
| " 1677628 0.841407\n", | |
| " 1677626 0.841511\n", | |
| " 1677627 0.841615\n", | |
| " 1677630 0.841718\n", | |
| " 1677631 0.841822\n", | |
| " 1677629 0.841926\n", | |
| " 1677634 0.842029\n", | |
| " 1677632 0.842132\n", | |
| " 1677633 0.842236\n", | |
| " 1677636 0.842338\n", | |
| " 1677637 0.842441\n", | |
| " 1677635 0.842544\n", | |
| " 1677638 0.842646\n", | |
| " 1677639 0.842748\n", | |
| " 1677640 0.842850\n", | |
| " 1677641 0.842953\n", | |
| " 1677642 0.843055\n", | |
| " 1677645 0.843156\n", | |
| "Name: prop, dtype: float64" | |
| ] | |
| }, | |
| "execution_count": 30, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "prop_cumsum" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "cumsum 메쏘드는 누적합을 의미한다. 위 데이터에서 0.5에 도달할 때의 index는 searchsorted 메쏘드로 확인한다. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 31, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "array([116])" | |
| ] | |
| }, | |
| "execution_count": 31, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "prop_cumsum.searchsorted(0.5)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "파이썬이 0부터 카운팅하므로, 117개의 이름이 50%를 차지함을 알 수 있다. 반면에, " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 32, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "array([25])" | |
| ] | |
| }, | |
| "execution_count": 32, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df = boys[boys.year == 1900]\n", | |
| "in1900 = df.sort_values(by='prop', ascending=False).prop.cumsum()\n", | |
| "in1900.searchsorted(0.5) + 1" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "1900년생은 25명이다. 확실히 다양성이 증가했다. \n", | |
| "\n", | |
| "이를 종합하여 매년 어떻게 변화하는지 살펴보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 33, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "def get_quantile_count(group, q=0.5):\n", | |
| " group = group.sort_values(by='prop', ascending=False)\n", | |
| " return (group.prop.cumsum().searchsorted(q) + 1)[0]\n", | |
| "\n", | |
| "diversity = top1000.groupby(['year', 'sex']).apply(get_quantile_count)\n", | |
| "diversity = diversity.unstack('sex')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 34, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>44</td>\n", | |
| " <td>19</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>44</td>\n", | |
| " <td>20</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>44</td>\n", | |
| " <td>20</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>44</td>\n", | |
| " <td>21</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>45</td>\n", | |
| " <td>22</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>46</td>\n", | |
| " <td>22</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>46</td>\n", | |
| " <td>23</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>46</td>\n", | |
| " <td>23</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>47</td>\n", | |
| " <td>24</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>47</td>\n", | |
| " <td>25</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>49</td>\n", | |
| " <td>25</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>49</td>\n", | |
| " <td>25</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>49</td>\n", | |
| " <td>26</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>49</td>\n", | |
| " <td>27</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>50</td>\n", | |
| " <td>28</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>50</td>\n", | |
| " <td>28</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>49</td>\n", | |
| " <td>28</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>50</td>\n", | |
| " <td>30</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>49</td>\n", | |
| " <td>30</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>49</td>\n", | |
| " <td>30</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>78</td>\n", | |
| " <td>35</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>75</td>\n", | |
| " <td>35</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>71</td>\n", | |
| " <td>34</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>71</td>\n", | |
| " <td>35</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>72</td>\n", | |
| " <td>36</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>74</td>\n", | |
| " <td>37</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>75</td>\n", | |
| " <td>39</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>78</td>\n", | |
| " <td>40</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>83</td>\n", | |
| " <td>43</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>90</td>\n", | |
| " <td>45</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>95</td>\n", | |
| " <td>48</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>102</td>\n", | |
| " <td>51</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>107</td>\n", | |
| " <td>54</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>111</td>\n", | |
| " <td>57</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>115</td>\n", | |
| " <td>60</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>122</td>\n", | |
| " <td>64</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>129</td>\n", | |
| " <td>67</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>138</td>\n", | |
| " <td>70</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>146</td>\n", | |
| " <td>73</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>155</td>\n", | |
| " <td>77</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>164</td>\n", | |
| " <td>81</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>170</td>\n", | |
| " <td>83</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>178</td>\n", | |
| " <td>87</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>191</td>\n", | |
| " <td>92</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>199</td>\n", | |
| " <td>96</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2006</th>\n", | |
| " <td>209</td>\n", | |
| " <td>99</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2007</th>\n", | |
| " <td>223</td>\n", | |
| " <td>103</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2008</th>\n", | |
| " <td>234</td>\n", | |
| " <td>109</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2009</th>\n", | |
| " <td>241</td>\n", | |
| " <td>114</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2010</th>\n", | |
| " <td>246</td>\n", | |
| " <td>117</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>131 rows × 2 columns</p>\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\n", | |
| "1890 44 19\n", | |
| "1891 44 20\n", | |
| "1892 44 20\n", | |
| "1893 44 21\n", | |
| "1894 45 22\n", | |
| "1895 46 22\n", | |
| "1896 46 23\n", | |
| "1897 46 23\n", | |
| "1898 47 24\n", | |
| "1899 47 25\n", | |
| "1900 49 25\n", | |
| "1901 49 25\n", | |
| "1902 49 26\n", | |
| "1903 49 27\n", | |
| "1904 50 28\n", | |
| "1905 50 28\n", | |
| "1906 49 28\n", | |
| "1907 50 30\n", | |
| "1908 49 30\n", | |
| "1909 49 30\n", | |
| "... ... ...\n", | |
| "1981 78 35\n", | |
| "1982 75 35\n", | |
| "1983 71 34\n", | |
| "1984 71 35\n", | |
| "1985 72 36\n", | |
| "1986 74 37\n", | |
| "1987 75 39\n", | |
| "1988 78 40\n", | |
| "1989 83 43\n", | |
| "1990 90 45\n", | |
| "1991 95 48\n", | |
| "1992 102 51\n", | |
| "1993 107 54\n", | |
| "1994 111 57\n", | |
| "1995 115 60\n", | |
| "1996 122 64\n", | |
| "1997 129 67\n", | |
| "1998 138 70\n", | |
| "1999 146 73\n", | |
| "2000 155 77\n", | |
| "2001 164 81\n", | |
| "2002 170 83\n", | |
| "2003 178 87\n", | |
| "2004 191 92\n", | |
| "2005 199 96\n", | |
| "2006 209 99\n", | |
| "2007 223 103\n", | |
| "2008 234 109\n", | |
| "2009 241 114\n", | |
| "2010 246 117\n", | |
| "\n", | |
| "[131 rows x 2 columns]" | |
| ] | |
| }, | |
| "execution_count": 34, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "diversity" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 35, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x10ce56940>" | |
| ] | |
| }, | |
| "execution_count": 35, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10ce4da58>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "diversity.plot(title=\"Number of popular names in top 50%\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "남자이름 보단 여자이름이 더 다양한 것으로 나옴. 1980년대 이후 특히 증가함을 알 수 있다.\n", | |
| "\n", | |
| "## The \"Last letter\" Revolution\n", | |
| "\n", | |
| "2007년에 출생아 이름 연구가 Laura Wattenberg는 남자이름의 마지막 글자 분포가 지난 100년에 걸처 유의하게 변해왔다고 한다. 확인해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 36, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0 y\n", | |
| "1 a\n", | |
| "2 a\n", | |
| "3 h\n", | |
| "4 e\n", | |
| "5 t\n", | |
| "6 a\n", | |
| "7 e\n", | |
| "8 a\n", | |
| "9 h\n", | |
| "10 e\n", | |
| "11 a\n", | |
| "12 a\n", | |
| "13 e\n", | |
| "14 a\n", | |
| "15 a\n", | |
| "16 a\n", | |
| "17 e\n", | |
| "18 e\n", | |
| "19 e\n", | |
| "20 e\n", | |
| "21 l\n", | |
| "22 e\n", | |
| "23 e\n", | |
| "24 e\n", | |
| "25 a\n", | |
| "26 e\n", | |
| "27 h\n", | |
| "28 e\n", | |
| "29 e\n", | |
| " ..\n", | |
| "1690754 n\n", | |
| "1690755 n\n", | |
| "1690756 n\n", | |
| "1690757 n\n", | |
| "1690758 l\n", | |
| "1690759 n\n", | |
| "1690760 a\n", | |
| "1690761 o\n", | |
| "1690762 h\n", | |
| "1690763 i\n", | |
| "1690764 h\n", | |
| "1690765 n\n", | |
| "1690766 r\n", | |
| "1690767 n\n", | |
| "1690768 n\n", | |
| "1690769 n\n", | |
| "1690770 n\n", | |
| "1690771 i\n", | |
| "1690772 n\n", | |
| "1690773 b\n", | |
| "1690774 e\n", | |
| "1690775 t\n", | |
| "1690776 n\n", | |
| "1690777 r\n", | |
| "1690778 n\n", | |
| "1690779 e\n", | |
| "1690780 e\n", | |
| "1690781 s\n", | |
| "1690782 n\n", | |
| "1690783 x\n", | |
| "Name: last_letter, dtype: object" | |
| ] | |
| }, | |
| "execution_count": 36, | |
| "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", | |
| "last_letters" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 37, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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>31446.0</td>\n", | |
| " <td>31581.0</td>\n", | |
| " <td>36536.0</td>\n", | |
| " <td>38330.0</td>\n", | |
| " <td>43680.0</td>\n", | |
| " <td>45408.0</td>\n", | |
| " <td>49100.0</td>\n", | |
| " <td>48942.0</td>\n", | |
| " <td>59442.0</td>\n", | |
| " <td>58631.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>39124.0</td>\n", | |
| " <td>38815.0</td>\n", | |
| " <td>37825.0</td>\n", | |
| " <td>38650.0</td>\n", | |
| " <td>36838.0</td>\n", | |
| " <td>36156.0</td>\n", | |
| " <td>34654.0</td>\n", | |
| " <td>32901.0</td>\n", | |
| " <td>31430.0</td>\n", | |
| " <td>28438.0</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>50950.0</td>\n", | |
| " <td>49284.0</td>\n", | |
| " <td>48065.0</td>\n", | |
| " <td>45914.0</td>\n", | |
| " <td>43144.0</td>\n", | |
| " <td>42600.0</td>\n", | |
| " <td>42123.0</td>\n", | |
| " <td>39945.0</td>\n", | |
| " <td>38862.0</td>\n", | |
| " <td>38859.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>c</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5.0</td>\n", | |
| " <td>5.0</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>27113.0</td>\n", | |
| " <td>27238.0</td>\n", | |
| " <td>27697.0</td>\n", | |
| " <td>26778.0</td>\n", | |
| " <td>26078.0</td>\n", | |
| " <td>26635.0</td>\n", | |
| " <td>26864.0</td>\n", | |
| " <td>25318.0</td>\n", | |
| " <td>24048.0</td>\n", | |
| " <td>23125.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>d</th>\n", | |
| " <td>609.0</td>\n", | |
| " <td>607.0</td>\n", | |
| " <td>734.0</td>\n", | |
| " <td>810.0</td>\n", | |
| " <td>916.0</td>\n", | |
| " <td>862.0</td>\n", | |
| " <td>1007.0</td>\n", | |
| " <td>1027.0</td>\n", | |
| " <td>1298.0</td>\n", | |
| " <td>1374.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>60838.0</td>\n", | |
| " <td>55829.0</td>\n", | |
| " <td>53391.0</td>\n", | |
| " <td>51754.0</td>\n", | |
| " <td>50670.0</td>\n", | |
| " <td>51410.0</td>\n", | |
| " <td>50595.0</td>\n", | |
| " <td>47910.0</td>\n", | |
| " <td>46172.0</td>\n", | |
| " <td>44398.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>e</th>\n", | |
| " <td>33378.0</td>\n", | |
| " <td>34080.0</td>\n", | |
| " <td>40399.0</td>\n", | |
| " <td>41914.0</td>\n", | |
| " <td>48089.0</td>\n", | |
| " <td>49616.0</td>\n", | |
| " <td>53884.0</td>\n", | |
| " <td>54353.0</td>\n", | |
| " <td>66750.0</td>\n", | |
| " <td>66663.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>145395.0</td>\n", | |
| " <td>144651.0</td>\n", | |
| " <td>144769.0</td>\n", | |
| " <td>142098.0</td>\n", | |
| " <td>141123.0</td>\n", | |
| " <td>142999.0</td>\n", | |
| " <td>143698.0</td>\n", | |
| " <td>140966.0</td>\n", | |
| " <td>135496.0</td>\n", | |
| " <td>129012.0</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>1758.0</td>\n", | |
| " <td>1817.0</td>\n", | |
| " <td>1819.0</td>\n", | |
| " <td>1904.0</td>\n", | |
| " <td>1985.0</td>\n", | |
| " <td>1968.0</td>\n", | |
| " <td>2090.0</td>\n", | |
| " <td>2195.0</td>\n", | |
| " <td>2212.0</td>\n", | |
| " <td>2255.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>g</th>\n", | |
| " <td>7.0</td>\n", | |
| " <td>5.0</td>\n", | |
| " <td>12.0</td>\n", | |
| " <td>8.0</td>\n", | |
| " <td>24.0</td>\n", | |
| " <td>11.0</td>\n", | |
| " <td>18.0</td>\n", | |
| " <td>25.0</td>\n", | |
| " <td>44.0</td>\n", | |
| " <td>28.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>2151.0</td>\n", | |
| " <td>2084.0</td>\n", | |
| " <td>2009.0</td>\n", | |
| " <td>1837.0</td>\n", | |
| " <td>1882.0</td>\n", | |
| " <td>1929.0</td>\n", | |
| " <td>2040.0</td>\n", | |
| " <td>2059.0</td>\n", | |
| " <td>2396.0</td>\n", | |
| " <td>2666.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>h</th>\n", | |
| " <td>4863.0</td>\n", | |
| " <td>4784.0</td>\n", | |
| " <td>5567.0</td>\n", | |
| " <td>5701.0</td>\n", | |
| " <td>6602.0</td>\n", | |
| " <td>6624.0</td>\n", | |
| " <td>7146.0</td>\n", | |
| " <td>7141.0</td>\n", | |
| " <td>8630.0</td>\n", | |
| " <td>8826.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>85959.0</td>\n", | |
| " <td>88085.0</td>\n", | |
| " <td>88226.0</td>\n", | |
| " <td>89620.0</td>\n", | |
| " <td>92497.0</td>\n", | |
| " <td>98477.0</td>\n", | |
| " <td>99414.0</td>\n", | |
| " <td>100250.0</td>\n", | |
| " <td>99979.0</td>\n", | |
| " <td>98090.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>i</th>\n", | |
| " <td>61.0</td>\n", | |
| " <td>78.0</td>\n", | |
| " <td>81.0</td>\n", | |
| " <td>76.0</td>\n", | |
| " <td>84.0</td>\n", | |
| " <td>92.0</td>\n", | |
| " <td>85.0</td>\n", | |
| " <td>105.0</td>\n", | |
| " <td>141.0</td>\n", | |
| " <td>134.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>20980.0</td>\n", | |
| " <td>23610.0</td>\n", | |
| " <td>26011.0</td>\n", | |
| " <td>28500.0</td>\n", | |
| " <td>31317.0</td>\n", | |
| " <td>33558.0</td>\n", | |
| " <td>35231.0</td>\n", | |
| " <td>38151.0</td>\n", | |
| " <td>40912.0</td>\n", | |
| " <td>42956.0</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>1069.0</td>\n", | |
| " <td>1088.0</td>\n", | |
| " <td>1203.0</td>\n", | |
| " <td>1094.0</td>\n", | |
| " <td>1291.0</td>\n", | |
| " <td>1241.0</td>\n", | |
| " <td>1254.0</td>\n", | |
| " <td>1381.0</td>\n", | |
| " <td>1416.0</td>\n", | |
| " <td>1459.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>k</th>\n", | |
| " <td>13.0</td>\n", | |
| " <td>15.0</td>\n", | |
| " <td>11.0</td>\n", | |
| " <td>17.0</td>\n", | |
| " <td>21.0</td>\n", | |
| " <td>18.0</td>\n", | |
| " <td>27.0</td>\n", | |
| " <td>19.0</td>\n", | |
| " <td>21.0</td>\n", | |
| " <td>22.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>42477.0</td>\n", | |
| " <td>42043.0</td>\n", | |
| " <td>42296.0</td>\n", | |
| " <td>41400.0</td>\n", | |
| " <td>42151.0</td>\n", | |
| " <td>42537.0</td>\n", | |
| " <td>42136.0</td>\n", | |
| " <td>39563.0</td>\n", | |
| " <td>37507.0</td>\n", | |
| " <td>35198.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>l</th>\n", | |
| " <td>2541.0</td>\n", | |
| " <td>2911.0</td>\n", | |
| " <td>3527.0</td>\n", | |
| " <td>3848.0</td>\n", | |
| " <td>4808.0</td>\n", | |
| " <td>5144.0</td>\n", | |
| " <td>5721.0</td>\n", | |
| " <td>6175.0</td>\n", | |
| " <td>7900.0</td>\n", | |
| " <td>8395.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>153648.0</td>\n", | |
| " <td>153493.0</td>\n", | |
| " <td>153862.0</td>\n", | |
| " <td>152800.0</td>\n", | |
| " <td>155312.0</td>\n", | |
| " <td>156234.0</td>\n", | |
| " <td>155203.0</td>\n", | |
| " <td>150791.0</td>\n", | |
| " <td>143751.0</td>\n", | |
| " <td>133583.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>m</th>\n", | |
| " <td>58.0</td>\n", | |
| " <td>57.0</td>\n", | |
| " <td>81.0</td>\n", | |
| " <td>86.0</td>\n", | |
| " <td>79.0</td>\n", | |
| " <td>75.0</td>\n", | |
| " <td>103.0</td>\n", | |
| " <td>90.0</td>\n", | |
| " <td>123.0</td>\n", | |
| " <td>137.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>41967.0</td>\n", | |
| " <td>42663.0</td>\n", | |
| " <td>42790.0</td>\n", | |
| " <td>43054.0</td>\n", | |
| " <td>41600.0</td>\n", | |
| " <td>42503.0</td>\n", | |
| " <td>43860.0</td>\n", | |
| " <td>44316.0</td>\n", | |
| " <td>46278.0</td>\n", | |
| " <td>46808.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>n</th>\n", | |
| " <td>3008.0</td>\n", | |
| " <td>2959.0</td>\n", | |
| " <td>3576.0</td>\n", | |
| " <td>3837.0</td>\n", | |
| " <td>4507.0</td>\n", | |
| " <td>4735.0</td>\n", | |
| " <td>5242.0</td>\n", | |
| " <td>5512.0</td>\n", | |
| " <td>6833.0</td>\n", | |
| " <td>7103.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>616099.0</td>\n", | |
| " <td>630322.0</td>\n", | |
| " <td>663419.0</td>\n", | |
| " <td>676011.0</td>\n", | |
| " <td>686326.0</td>\n", | |
| " <td>720998.0</td>\n", | |
| " <td>741355.0</td>\n", | |
| " <td>733869.0</td>\n", | |
| " <td>715388.0</td>\n", | |
| " <td>688677.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>o</th>\n", | |
| " <td>30.0</td>\n", | |
| " <td>49.0</td>\n", | |
| " <td>35.0</td>\n", | |
| " <td>47.0</td>\n", | |
| " <td>74.0</td>\n", | |
| " <td>84.0</td>\n", | |
| " <td>93.0</td>\n", | |
| " <td>97.0</td>\n", | |
| " <td>134.0</td>\n", | |
| " <td>142.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>82146.0</td>\n", | |
| " <td>83180.0</td>\n", | |
| " <td>85423.0</td>\n", | |
| " <td>88822.0</td>\n", | |
| " <td>92001.0</td>\n", | |
| " <td>96350.0</td>\n", | |
| " <td>96895.0</td>\n", | |
| " <td>91485.0</td>\n", | |
| " <td>86423.0</td>\n", | |
| " <td>81025.0</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>3419.0</td>\n", | |
| " <td>3157.0</td>\n", | |
| " <td>2982.0</td>\n", | |
| " <td>2841.0</td>\n", | |
| " <td>2768.0</td>\n", | |
| " <td>2721.0</td>\n", | |
| " <td>2739.0</td>\n", | |
| " <td>2637.0</td>\n", | |
| " <td>2595.0</td>\n", | |
| " <td>2409.0</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>602.0</td>\n", | |
| " <td>618.0</td>\n", | |
| " <td>585.0</td>\n", | |
| " <td>523.0</td>\n", | |
| " <td>446.0</td>\n", | |
| " <td>430.0</td>\n", | |
| " <td>431.0</td>\n", | |
| " <td>339.0</td>\n", | |
| " <td>377.0</td>\n", | |
| " <td>342.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>r</th>\n", | |
| " <td>481.0</td>\n", | |
| " <td>417.0</td>\n", | |
| " <td>590.0</td>\n", | |
| " <td>640.0</td>\n", | |
| " <td>718.0</td>\n", | |
| " <td>799.0</td>\n", | |
| " <td>917.0</td>\n", | |
| " <td>910.0</td>\n", | |
| " <td>1207.0</td>\n", | |
| " <td>1214.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>165377.0</td>\n", | |
| " <td>164821.0</td>\n", | |
| " <td>169878.0</td>\n", | |
| " <td>169452.0</td>\n", | |
| " <td>172069.0</td>\n", | |
| " <td>176490.0</td>\n", | |
| " <td>177207.0</td>\n", | |
| " <td>174632.0</td>\n", | |
| " <td>173200.0</td>\n", | |
| " <td>166064.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>s</th>\n", | |
| " <td>1391.0</td>\n", | |
| " <td>1316.0</td>\n", | |
| " <td>1637.0</td>\n", | |
| " <td>1794.0</td>\n", | |
| " <td>2039.0</td>\n", | |
| " <td>2127.0</td>\n", | |
| " <td>2524.0</td>\n", | |
| " <td>2803.0</td>\n", | |
| " <td>3582.0</td>\n", | |
| " <td>3569.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>143791.0</td>\n", | |
| " <td>139595.0</td>\n", | |
| " <td>138632.0</td>\n", | |
| " <td>139642.0</td>\n", | |
| " <td>139913.0</td>\n", | |
| " <td>143232.0</td>\n", | |
| " <td>142155.0</td>\n", | |
| " <td>137056.0</td>\n", | |
| " <td>129861.0</td>\n", | |
| " <td>123670.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>t</th>\n", | |
| " <td>2152.0</td>\n", | |
| " <td>2165.0</td>\n", | |
| " <td>2399.0</td>\n", | |
| " <td>2554.0</td>\n", | |
| " <td>2825.0</td>\n", | |
| " <td>2889.0</td>\n", | |
| " <td>3017.0</td>\n", | |
| " <td>3140.0</td>\n", | |
| " <td>3816.0</td>\n", | |
| " <td>3784.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>47688.0</td>\n", | |
| " <td>44991.0</td>\n", | |
| " <td>43765.0</td>\n", | |
| " <td>43870.0</td>\n", | |
| " <td>43369.0</td>\n", | |
| " <td>43553.0</td>\n", | |
| " <td>43437.0</td>\n", | |
| " <td>43846.0</td>\n", | |
| " <td>43674.0</td>\n", | |
| " <td>43398.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>u</th>\n", | |
| " <td>380.0</td>\n", | |
| " <td>427.0</td>\n", | |
| " <td>410.0</td>\n", | |
| " <td>444.0</td>\n", | |
| " <td>490.0</td>\n", | |
| " <td>495.0</td>\n", | |
| " <td>511.0</td>\n", | |
| " <td>476.0</td>\n", | |
| " <td>541.0</td>\n", | |
| " <td>469.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1833.0</td>\n", | |
| " <td>1819.0</td>\n", | |
| " <td>2052.0</td>\n", | |
| " <td>2138.0</td>\n", | |
| " <td>2129.0</td>\n", | |
| " <td>2201.0</td>\n", | |
| " <td>2311.0</td>\n", | |
| " <td>2405.0</td>\n", | |
| " <td>2417.0</td>\n", | |
| " <td>2318.0</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>1209.0</td>\n", | |
| " <td>1332.0</td>\n", | |
| " <td>1652.0</td>\n", | |
| " <td>1823.0</td>\n", | |
| " <td>1794.0</td>\n", | |
| " <td>2010.0</td>\n", | |
| " <td>2295.0</td>\n", | |
| " <td>2418.0</td>\n", | |
| " <td>2589.0</td>\n", | |
| " <td>2723.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>w</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>5.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>...</td>\n", | |
| " <td>52265.0</td>\n", | |
| " <td>50103.0</td>\n", | |
| " <td>49079.0</td>\n", | |
| " <td>47556.0</td>\n", | |
| " <td>45464.0</td>\n", | |
| " <td>43217.0</td>\n", | |
| " <td>40251.0</td>\n", | |
| " <td>36937.0</td>\n", | |
| " <td>33181.0</td>\n", | |
| " <td>30656.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>x</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>7.0</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>10691.0</td>\n", | |
| " <td>11009.0</td>\n", | |
| " <td>11718.0</td>\n", | |
| " <td>12399.0</td>\n", | |
| " <td>13025.0</td>\n", | |
| " <td>13992.0</td>\n", | |
| " <td>14306.0</td>\n", | |
| " <td>14834.0</td>\n", | |
| " <td>16640.0</td>\n", | |
| " <td>16352.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>y</th>\n", | |
| " <td>10469.0</td>\n", | |
| " <td>10404.0</td>\n", | |
| " <td>12145.0</td>\n", | |
| " <td>12063.0</td>\n", | |
| " <td>13917.0</td>\n", | |
| " <td>13927.0</td>\n", | |
| " <td>14936.0</td>\n", | |
| " <td>14980.0</td>\n", | |
| " <td>17931.0</td>\n", | |
| " <td>17601.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>139109.0</td>\n", | |
| " <td>134557.0</td>\n", | |
| " <td>130569.0</td>\n", | |
| " <td>128367.0</td>\n", | |
| " <td>125190.0</td>\n", | |
| " <td>123707.0</td>\n", | |
| " <td>123397.0</td>\n", | |
| " <td>122633.0</td>\n", | |
| " <td>112922.0</td>\n", | |
| " <td>110425.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>z</th>\n", | |
| " <td>106.0</td>\n", | |
| " <td>95.0</td>\n", | |
| " <td>106.0</td>\n", | |
| " <td>141.0</td>\n", | |
| " <td>148.0</td>\n", | |
| " <td>150.0</td>\n", | |
| " <td>202.0</td>\n", | |
| " <td>188.0</td>\n", | |
| " <td>238.0</td>\n", | |
| " <td>277.0</td>\n", | |
| " <td>...</td>\n", | |
| " <td>2840.0</td>\n", | |
| " <td>2737.0</td>\n", | |
| " <td>2722.0</td>\n", | |
| " <td>2710.0</td>\n", | |
| " <td>2903.0</td>\n", | |
| " <td>3086.0</td>\n", | |
| " <td>3301.0</td>\n", | |
| " <td>3473.0</td>\n", | |
| " <td>3633.0</td>\n", | |
| " <td>3476.0</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 \n", | |
| "last_letter \n", | |
| "a 31446.0 31581.0 36536.0 38330.0 43680.0 45408.0 49100.0 \n", | |
| "b NaN NaN NaN NaN NaN NaN NaN \n", | |
| "c NaN NaN 5.0 5.0 NaN NaN NaN \n", | |
| "d 609.0 607.0 734.0 810.0 916.0 862.0 1007.0 \n", | |
| "e 33378.0 34080.0 40399.0 41914.0 48089.0 49616.0 53884.0 \n", | |
| "f NaN NaN NaN NaN NaN NaN NaN \n", | |
| "g 7.0 5.0 12.0 8.0 24.0 11.0 18.0 \n", | |
| "h 4863.0 4784.0 5567.0 5701.0 6602.0 6624.0 7146.0 \n", | |
| "i 61.0 78.0 81.0 76.0 84.0 92.0 85.0 \n", | |
| "j NaN NaN NaN NaN NaN NaN NaN \n", | |
| "k 13.0 15.0 11.0 17.0 21.0 18.0 27.0 \n", | |
| "l 2541.0 2911.0 3527.0 3848.0 4808.0 5144.0 5721.0 \n", | |
| "m 58.0 57.0 81.0 86.0 79.0 75.0 103.0 \n", | |
| "n 3008.0 2959.0 3576.0 3837.0 4507.0 4735.0 5242.0 \n", | |
| "o 30.0 49.0 35.0 47.0 74.0 84.0 93.0 \n", | |
| "p NaN NaN NaN NaN NaN NaN NaN \n", | |
| "q NaN NaN NaN NaN NaN NaN NaN \n", | |
| "r 481.0 417.0 590.0 640.0 718.0 799.0 917.0 \n", | |
| "s 1391.0 1316.0 1637.0 1794.0 2039.0 2127.0 2524.0 \n", | |
| "t 2152.0 2165.0 2399.0 2554.0 2825.0 2889.0 3017.0 \n", | |
| "u 380.0 427.0 410.0 444.0 490.0 495.0 511.0 \n", | |
| "v NaN NaN NaN NaN NaN NaN NaN \n", | |
| "w NaN 5.0 NaN NaN NaN NaN 5.0 \n", | |
| "x NaN NaN NaN 7.0 NaN NaN NaN \n", | |
| "y 10469.0 10404.0 12145.0 12063.0 13917.0 13927.0 14936.0 \n", | |
| "z 106.0 95.0 106.0 141.0 148.0 150.0 202.0 \n", | |
| "\n", | |
| "sex ... M \\\n", | |
| "year 1887 1888 1889 ... 2001 2002 \n", | |
| "last_letter ... \n", | |
| "a 48942.0 59442.0 58631.0 ... 39124.0 38815.0 \n", | |
| "b NaN NaN NaN ... 50950.0 49284.0 \n", | |
| "c NaN NaN NaN ... 27113.0 27238.0 \n", | |
| "d 1027.0 1298.0 1374.0 ... 60838.0 55829.0 \n", | |
| "e 54353.0 66750.0 66663.0 ... 145395.0 144651.0 \n", | |
| "f NaN NaN NaN ... 1758.0 1817.0 \n", | |
| "g 25.0 44.0 28.0 ... 2151.0 2084.0 \n", | |
| "h 7141.0 8630.0 8826.0 ... 85959.0 88085.0 \n", | |
| "i 105.0 141.0 134.0 ... 20980.0 23610.0 \n", | |
| "j NaN NaN NaN ... 1069.0 1088.0 \n", | |
| "k 19.0 21.0 22.0 ... 42477.0 42043.0 \n", | |
| "l 6175.0 7900.0 8395.0 ... 153648.0 153493.0 \n", | |
| "m 90.0 123.0 137.0 ... 41967.0 42663.0 \n", | |
| "n 5512.0 6833.0 7103.0 ... 616099.0 630322.0 \n", | |
| "o 97.0 134.0 142.0 ... 82146.0 83180.0 \n", | |
| "p NaN NaN NaN ... 3419.0 3157.0 \n", | |
| "q NaN NaN NaN ... 602.0 618.0 \n", | |
| "r 910.0 1207.0 1214.0 ... 165377.0 164821.0 \n", | |
| "s 2803.0 3582.0 3569.0 ... 143791.0 139595.0 \n", | |
| "t 3140.0 3816.0 3784.0 ... 47688.0 44991.0 \n", | |
| "u 476.0 541.0 469.0 ... 1833.0 1819.0 \n", | |
| "v NaN NaN NaN ... 1209.0 1332.0 \n", | |
| "w NaN NaN NaN ... 52265.0 50103.0 \n", | |
| "x NaN NaN NaN ... 10691.0 11009.0 \n", | |
| "y 14980.0 17931.0 17601.0 ... 139109.0 134557.0 \n", | |
| "z 188.0 238.0 277.0 ... 2840.0 2737.0 \n", | |
| "\n", | |
| "sex \\\n", | |
| "year 2003 2004 2005 2006 2007 2008 \n", | |
| "last_letter \n", | |
| "a 37825.0 38650.0 36838.0 36156.0 34654.0 32901.0 \n", | |
| "b 48065.0 45914.0 43144.0 42600.0 42123.0 39945.0 \n", | |
| "c 27697.0 26778.0 26078.0 26635.0 26864.0 25318.0 \n", | |
| "d 53391.0 51754.0 50670.0 51410.0 50595.0 47910.0 \n", | |
| "e 144769.0 142098.0 141123.0 142999.0 143698.0 140966.0 \n", | |
| "f 1819.0 1904.0 1985.0 1968.0 2090.0 2195.0 \n", | |
| "g 2009.0 1837.0 1882.0 1929.0 2040.0 2059.0 \n", | |
| "h 88226.0 89620.0 92497.0 98477.0 99414.0 100250.0 \n", | |
| "i 26011.0 28500.0 31317.0 33558.0 35231.0 38151.0 \n", | |
| "j 1203.0 1094.0 1291.0 1241.0 1254.0 1381.0 \n", | |
| "k 42296.0 41400.0 42151.0 42537.0 42136.0 39563.0 \n", | |
| "l 153862.0 152800.0 155312.0 156234.0 155203.0 150791.0 \n", | |
| "m 42790.0 43054.0 41600.0 42503.0 43860.0 44316.0 \n", | |
| "n 663419.0 676011.0 686326.0 720998.0 741355.0 733869.0 \n", | |
| "o 85423.0 88822.0 92001.0 96350.0 96895.0 91485.0 \n", | |
| "p 2982.0 2841.0 2768.0 2721.0 2739.0 2637.0 \n", | |
| "q 585.0 523.0 446.0 430.0 431.0 339.0 \n", | |
| "r 169878.0 169452.0 172069.0 176490.0 177207.0 174632.0 \n", | |
| "s 138632.0 139642.0 139913.0 143232.0 142155.0 137056.0 \n", | |
| "t 43765.0 43870.0 43369.0 43553.0 43437.0 43846.0 \n", | |
| "u 2052.0 2138.0 2129.0 2201.0 2311.0 2405.0 \n", | |
| "v 1652.0 1823.0 1794.0 2010.0 2295.0 2418.0 \n", | |
| "w 49079.0 47556.0 45464.0 43217.0 40251.0 36937.0 \n", | |
| "x 11718.0 12399.0 13025.0 13992.0 14306.0 14834.0 \n", | |
| "y 130569.0 128367.0 125190.0 123707.0 123397.0 122633.0 \n", | |
| "z 2722.0 2710.0 2903.0 3086.0 3301.0 3473.0 \n", | |
| "\n", | |
| "sex \n", | |
| "year 2009 2010 \n", | |
| "last_letter \n", | |
| "a 31430.0 28438.0 \n", | |
| "b 38862.0 38859.0 \n", | |
| "c 24048.0 23125.0 \n", | |
| "d 46172.0 44398.0 \n", | |
| "e 135496.0 129012.0 \n", | |
| "f 2212.0 2255.0 \n", | |
| "g 2396.0 2666.0 \n", | |
| "h 99979.0 98090.0 \n", | |
| "i 40912.0 42956.0 \n", | |
| "j 1416.0 1459.0 \n", | |
| "k 37507.0 35198.0 \n", | |
| "l 143751.0 133583.0 \n", | |
| "m 46278.0 46808.0 \n", | |
| "n 715388.0 688677.0 \n", | |
| "o 86423.0 81025.0 \n", | |
| "p 2595.0 2409.0 \n", | |
| "q 377.0 342.0 \n", | |
| "r 173200.0 166064.0 \n", | |
| "s 129861.0 123670.0 \n", | |
| "t 43674.0 43398.0 \n", | |
| "u 2417.0 2318.0 \n", | |
| "v 2589.0 2723.0 \n", | |
| "w 33181.0 30656.0 \n", | |
| "x 16640.0 16352.0 \n", | |
| "y 112922.0 110425.0 \n", | |
| "z 3633.0 3476.0 \n", | |
| "\n", | |
| "[26 rows x 262 columns]" | |
| ] | |
| }, | |
| "execution_count": 37, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "table = names.pivot_table('births', index=last_letters, columns=['sex', 'year'], aggfunc=sum)\n", | |
| "table" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "연도가 너무 많으니 대표적은 3개의 연도만 확인해보기로 하자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 38, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "subtable = table.reindex(columns=[1910, 1960, 2010], level='year')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 39, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "sex year\n", | |
| "F 1910 396416.0\n", | |
| " 1960 2022062.0\n", | |
| " 2010 1759010.0\n", | |
| "M 1910 194198.0\n", | |
| " 1960 2132588.0\n", | |
| " 2010 1898382.0\n", | |
| "dtype: float64" | |
| ] | |
| }, | |
| "execution_count": 39, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "subtable.sum()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 40, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "letter_prop = subtable / subtable.sum()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 41, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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>0.273390</td>\n", | |
| " <td>0.341853</td>\n", | |
| " <td>0.381240</td>\n", | |
| " <td>0.005031</td>\n", | |
| " <td>0.002440</td>\n", | |
| " <td>0.014980</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>b</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000343</td>\n", | |
| " <td>0.000256</td>\n", | |
| " <td>0.002116</td>\n", | |
| " <td>0.001834</td>\n", | |
| " <td>0.020470</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>c</th>\n", | |
| " <td>0.000013</td>\n", | |
| " <td>0.000024</td>\n", | |
| " <td>0.000538</td>\n", | |
| " <td>0.002482</td>\n", | |
| " <td>0.007257</td>\n", | |
| " <td>0.012181</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>d</th>\n", | |
| " <td>0.017028</td>\n", | |
| " <td>0.001844</td>\n", | |
| " <td>0.001482</td>\n", | |
| " <td>0.113858</td>\n", | |
| " <td>0.122908</td>\n", | |
| " <td>0.023387</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>e</th>\n", | |
| " <td>0.336941</td>\n", | |
| " <td>0.215133</td>\n", | |
| " <td>0.178415</td>\n", | |
| " <td>0.147556</td>\n", | |
| " <td>0.083853</td>\n", | |
| " <td>0.067959</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>f</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000010</td>\n", | |
| " <td>0.000055</td>\n", | |
| " <td>0.000783</td>\n", | |
| " <td>0.004325</td>\n", | |
| " <td>0.001188</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>g</th>\n", | |
| " <td>0.000144</td>\n", | |
| " <td>0.000157</td>\n", | |
| " <td>0.000374</td>\n", | |
| " <td>0.002250</td>\n", | |
| " <td>0.009488</td>\n", | |
| " <td>0.001404</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>h</th>\n", | |
| " <td>0.051529</td>\n", | |
| " <td>0.036224</td>\n", | |
| " <td>0.075852</td>\n", | |
| " <td>0.045562</td>\n", | |
| " <td>0.037907</td>\n", | |
| " <td>0.051670</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>i</th>\n", | |
| " <td>0.001526</td>\n", | |
| " <td>0.039965</td>\n", | |
| " <td>0.031734</td>\n", | |
| " <td>0.000844</td>\n", | |
| " <td>0.000603</td>\n", | |
| " <td>0.022628</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>j</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000090</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000769</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>k</th>\n", | |
| " <td>0.000121</td>\n", | |
| " <td>0.000156</td>\n", | |
| " <td>0.000356</td>\n", | |
| " <td>0.036581</td>\n", | |
| " <td>0.049384</td>\n", | |
| " <td>0.018541</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>l</th>\n", | |
| " <td>0.043189</td>\n", | |
| " <td>0.033867</td>\n", | |
| " <td>0.026356</td>\n", | |
| " <td>0.065016</td>\n", | |
| " <td>0.104904</td>\n", | |
| " <td>0.070367</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>m</th>\n", | |
| " <td>0.001201</td>\n", | |
| " <td>0.008613</td>\n", | |
| " <td>0.002588</td>\n", | |
| " <td>0.058044</td>\n", | |
| " <td>0.033827</td>\n", | |
| " <td>0.024657</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>n</th>\n", | |
| " <td>0.079240</td>\n", | |
| " <td>0.130687</td>\n", | |
| " <td>0.140210</td>\n", | |
| " <td>0.143415</td>\n", | |
| " <td>0.152522</td>\n", | |
| " <td>0.362771</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>o</th>\n", | |
| " <td>0.001660</td>\n", | |
| " <td>0.002439</td>\n", | |
| " <td>0.001243</td>\n", | |
| " <td>0.017065</td>\n", | |
| " <td>0.012829</td>\n", | |
| " <td>0.042681</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>p</th>\n", | |
| " <td>0.000018</td>\n", | |
| " <td>0.000023</td>\n", | |
| " <td>0.000020</td>\n", | |
| " <td>0.003172</td>\n", | |
| " <td>0.005675</td>\n", | |
| " <td>0.001269</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>q</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000030</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000180</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>r</th>\n", | |
| " <td>0.013390</td>\n", | |
| " <td>0.006764</td>\n", | |
| " <td>0.018025</td>\n", | |
| " <td>0.064481</td>\n", | |
| " <td>0.031034</td>\n", | |
| " <td>0.087477</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>s</th>\n", | |
| " <td>0.039042</td>\n", | |
| " <td>0.012764</td>\n", | |
| " <td>0.013332</td>\n", | |
| " <td>0.130815</td>\n", | |
| " <td>0.102730</td>\n", | |
| " <td>0.065145</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>t</th>\n", | |
| " <td>0.027438</td>\n", | |
| " <td>0.015201</td>\n", | |
| " <td>0.007830</td>\n", | |
| " <td>0.072879</td>\n", | |
| " <td>0.065655</td>\n", | |
| " <td>0.022861</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>u</th>\n", | |
| " <td>0.000684</td>\n", | |
| " <td>0.000574</td>\n", | |
| " <td>0.000417</td>\n", | |
| " <td>0.000124</td>\n", | |
| " <td>0.000057</td>\n", | |
| " <td>0.001221</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>v</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>0.000060</td>\n", | |
| " <td>0.000117</td>\n", | |
| " <td>0.000113</td>\n", | |
| " <td>0.000037</td>\n", | |
| " <td>0.001434</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>w</th>\n", | |
| " <td>0.000020</td>\n", | |
| " <td>0.000031</td>\n", | |
| " <td>0.001182</td>\n", | |
| " <td>0.006329</td>\n", | |
| " <td>0.007711</td>\n", | |
| " <td>0.016148</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>x</th>\n", | |
| " <td>0.000015</td>\n", | |
| " <td>0.000037</td>\n", | |
| " <td>0.000727</td>\n", | |
| " <td>0.003965</td>\n", | |
| " <td>0.001851</td>\n", | |
| " <td>0.008614</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>y</th>\n", | |
| " <td>0.110972</td>\n", | |
| " <td>0.152569</td>\n", | |
| " <td>0.116828</td>\n", | |
| " <td>0.077349</td>\n", | |
| " <td>0.160987</td>\n", | |
| " <td>0.058168</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>z</th>\n", | |
| " <td>0.002439</td>\n", | |
| " <td>0.000659</td>\n", | |
| " <td>0.000704</td>\n", | |
| " <td>0.000170</td>\n", | |
| " <td>0.000184</td>\n", | |
| " <td>0.001831</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 0.273390 0.341853 0.381240 0.005031 0.002440 0.014980\n", | |
| "b NaN 0.000343 0.000256 0.002116 0.001834 0.020470\n", | |
| "c 0.000013 0.000024 0.000538 0.002482 0.007257 0.012181\n", | |
| "d 0.017028 0.001844 0.001482 0.113858 0.122908 0.023387\n", | |
| "e 0.336941 0.215133 0.178415 0.147556 0.083853 0.067959\n", | |
| "f NaN 0.000010 0.000055 0.000783 0.004325 0.001188\n", | |
| "g 0.000144 0.000157 0.000374 0.002250 0.009488 0.001404\n", | |
| "h 0.051529 0.036224 0.075852 0.045562 0.037907 0.051670\n", | |
| "i 0.001526 0.039965 0.031734 0.000844 0.000603 0.022628\n", | |
| "j NaN NaN 0.000090 NaN NaN 0.000769\n", | |
| "k 0.000121 0.000156 0.000356 0.036581 0.049384 0.018541\n", | |
| "l 0.043189 0.033867 0.026356 0.065016 0.104904 0.070367\n", | |
| "m 0.001201 0.008613 0.002588 0.058044 0.033827 0.024657\n", | |
| "n 0.079240 0.130687 0.140210 0.143415 0.152522 0.362771\n", | |
| "o 0.001660 0.002439 0.001243 0.017065 0.012829 0.042681\n", | |
| "p 0.000018 0.000023 0.000020 0.003172 0.005675 0.001269\n", | |
| "q NaN NaN 0.000030 NaN NaN 0.000180\n", | |
| "r 0.013390 0.006764 0.018025 0.064481 0.031034 0.087477\n", | |
| "s 0.039042 0.012764 0.013332 0.130815 0.102730 0.065145\n", | |
| "t 0.027438 0.015201 0.007830 0.072879 0.065655 0.022861\n", | |
| "u 0.000684 0.000574 0.000417 0.000124 0.000057 0.001221\n", | |
| "v NaN 0.000060 0.000117 0.000113 0.000037 0.001434\n", | |
| "w 0.000020 0.000031 0.001182 0.006329 0.007711 0.016148\n", | |
| "x 0.000015 0.000037 0.000727 0.003965 0.001851 0.008614\n", | |
| "y 0.110972 0.152569 0.116828 0.077349 0.160987 0.058168\n", | |
| "z 0.002439 0.000659 0.000704 0.000170 0.000184 0.001831" | |
| ] | |
| }, | |
| "execution_count": 41, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "letter_prop" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "이를 차트로 표시해보면," | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 42, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x10d7b0d68>" | |
| ] | |
| }, | |
| "execution_count": 42, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
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T5jbgnQARcQLw68zsjIjxETGxWD8BeAOwanAvRSqXZ5pJkobLgCNWmbkjIi4H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\nZmZWiBtWZmZmZoX8D4bIutC+iqKVAAAAAElFTkSuQmCC\n", | |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10d1a1b70>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "import matplotlib.pyplot as plt\n", | |
| "\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": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "남자의 경우, 1960년대 이후, \"n\"으로 끝나는 이름이 현저히 늘었다. 이를 전체 그룹에 대해 확장해보자." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 43, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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", | |
| " <tr>\n", | |
| " <th>1885</th>\n", | |
| " <td>0.085472</td>\n", | |
| " <td>0.146361</td>\n", | |
| " <td>0.081882</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1886</th>\n", | |
| " <td>0.087647</td>\n", | |
| " <td>0.149659</td>\n", | |
| " <td>0.081681</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1887</th>\n", | |
| " <td>0.089072</td>\n", | |
| " <td>0.148838</td>\n", | |
| " <td>0.082870</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1888</th>\n", | |
| " <td>0.087707</td>\n", | |
| " <td>0.151286</td>\n", | |
| " <td>0.084919</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1889</th>\n", | |
| " <td>0.091934</td>\n", | |
| " <td>0.151976</td>\n", | |
| " <td>0.086328</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>0.093834</td>\n", | |
| " <td>0.146470</td>\n", | |
| " <td>0.086277</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>0.094478</td>\n", | |
| " <td>0.148353</td>\n", | |
| " <td>0.084933</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>0.096388</td>\n", | |
| " <td>0.144857</td>\n", | |
| " <td>0.084883</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>0.098318</td>\n", | |
| " <td>0.142558</td>\n", | |
| " <td>0.084643</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>0.100462</td>\n", | |
| " <td>0.142112</td>\n", | |
| " <td>0.085554</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>0.100019</td>\n", | |
| " <td>0.143350</td>\n", | |
| " <td>0.083332</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>0.102881</td>\n", | |
| " <td>0.140631</td>\n", | |
| " <td>0.083922</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>0.101987</td>\n", | |
| " <td>0.140112</td>\n", | |
| " <td>0.083283</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>0.104887</td>\n", | |
| " <td>0.139614</td>\n", | |
| " <td>0.090633</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>0.105020</td>\n", | |
| " <td>0.140607</td>\n", | |
| " <td>0.084807</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>0.102946</td>\n", | |
| " <td>0.137645</td>\n", | |
| " <td>0.084661</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>0.106792</td>\n", | |
| " <td>0.141428</td>\n", | |
| " <td>0.081754</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>0.108022</td>\n", | |
| " <td>0.140641</td>\n", | |
| " <td>0.081901</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>0.109577</td>\n", | |
| " <td>0.141337</td>\n", | |
| " <td>0.080309</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>0.109335</td>\n", | |
| " <td>0.143145</td>\n", | |
| " <td>0.080739</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>0.110226</td>\n", | |
| " <td>0.142429</td>\n", | |
| " <td>0.079331</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>0.111836</td>\n", | |
| " <td>0.141447</td>\n", | |
| " <td>0.078786</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>0.112689</td>\n", | |
| " <td>0.143328</td>\n", | |
| " <td>0.079046</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>0.113899</td>\n", | |
| " <td>0.143146</td>\n", | |
| " <td>0.078593</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>0.115500</td>\n", | |
| " <td>0.144204</td>\n", | |
| " <td>0.077386</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>0.069564</td>\n", | |
| " <td>0.247668</td>\n", | |
| " <td>0.109612</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>0.067343</td>\n", | |
| " <td>0.247982</td>\n", | |
| " <td>0.107810</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>0.064590</td>\n", | |
| " <td>0.250570</td>\n", | |
| " <td>0.103872</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>0.062247</td>\n", | |
| " <td>0.249121</td>\n", | |
| " <td>0.104434</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>0.060067</td>\n", | |
| " <td>0.249074</td>\n", | |
| " <td>0.106783</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>0.058999</td>\n", | |
| " <td>0.248461</td>\n", | |
| " <td>0.108102</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>0.057410</td>\n", | |
| " <td>0.248466</td>\n", | |
| " <td>0.108872</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>0.054987</td>\n", | |
| " <td>0.250193</td>\n", | |
| " <td>0.108163</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>0.052868</td>\n", | |
| " <td>0.251095</td>\n", | |
| " <td>0.106309</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>0.049690</td>\n", | |
| " <td>0.254481</td>\n", | |
| " <td>0.104817</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>0.046487</td>\n", | |
| " <td>0.260756</td>\n", | |
| " <td>0.103390</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>0.043886</td>\n", | |
| " <td>0.269240</td>\n", | |
| " <td>0.101575</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>0.042119</td>\n", | |
| " <td>0.271248</td>\n", | |
| " <td>0.100591</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>0.039973</td>\n", | |
| " <td>0.278569</td>\n", | |
| " <td>0.096975</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>0.038017</td>\n", | |
| " <td>0.284643</td>\n", | |
| " <td>0.091720</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>0.037067</td>\n", | |
| " <td>0.289856</td>\n", | |
| " <td>0.087609</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>0.036652</td>\n", | |
| " <td>0.293351</td>\n", | |
| " <td>0.083793</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>0.035442</td>\n", | |
| " <td>0.298259</td>\n", | |
| " <td>0.079016</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>0.034149</td>\n", | |
| " <td>0.304703</td>\n", | |
| " <td>0.076184</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>0.032753</td>\n", | |
| " <td>0.313060</td>\n", | |
| " <td>0.073000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>0.031352</td>\n", | |
| " <td>0.317495</td>\n", | |
| " <td>0.071687</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>0.028794</td>\n", | |
| " <td>0.325086</td>\n", | |
| " <td>0.069397</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>0.027069</td>\n", | |
| " <td>0.336344</td>\n", | |
| " <td>0.066197</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>0.026118</td>\n", | |
| " <td>0.341151</td>\n", | |
| " <td>0.064781</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>0.025420</td>\n", | |
| " <td>0.344319</td>\n", | |
| " <td>0.062806</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2006</th>\n", | |
| " <td>0.025075</td>\n", | |
| " <td>0.351666</td>\n", | |
| " <td>0.060338</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2007</th>\n", | |
| " <td>0.024451</td>\n", | |
| " <td>0.358274</td>\n", | |
| " <td>0.059634</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2008</th>\n", | |
| " <td>0.023574</td>\n", | |
| " <td>0.361101</td>\n", | |
| " <td>0.060342</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2009</th>\n", | |
| " <td>0.023398</td>\n", | |
| " <td>0.362523</td>\n", | |
| " <td>0.057223</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2010</th>\n", | |
| " <td>0.023387</td>\n", | |
| " <td>0.362771</td>\n", | |
| " <td>0.058168</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>131 rows × 3 columns</p>\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\n", | |
| "1885 0.085472 0.146361 0.081882\n", | |
| "1886 0.087647 0.149659 0.081681\n", | |
| "1887 0.089072 0.148838 0.082870\n", | |
| "1888 0.087707 0.151286 0.084919\n", | |
| "1889 0.091934 0.151976 0.086328\n", | |
| "1890 0.093834 0.146470 0.086277\n", | |
| "1891 0.094478 0.148353 0.084933\n", | |
| "1892 0.096388 0.144857 0.084883\n", | |
| "1893 0.098318 0.142558 0.084643\n", | |
| "1894 0.100462 0.142112 0.085554\n", | |
| "1895 0.100019 0.143350 0.083332\n", | |
| "1896 0.102881 0.140631 0.083922\n", | |
| "1897 0.101987 0.140112 0.083283\n", | |
| "1898 0.104887 0.139614 0.090633\n", | |
| "1899 0.105020 0.140607 0.084807\n", | |
| "1900 0.102946 0.137645 0.084661\n", | |
| "1901 0.106792 0.141428 0.081754\n", | |
| "1902 0.108022 0.140641 0.081901\n", | |
| "1903 0.109577 0.141337 0.080309\n", | |
| "1904 0.109335 0.143145 0.080739\n", | |
| "1905 0.110226 0.142429 0.079331\n", | |
| "1906 0.111836 0.141447 0.078786\n", | |
| "1907 0.112689 0.143328 0.079046\n", | |
| "1908 0.113899 0.143146 0.078593\n", | |
| "1909 0.115500 0.144204 0.077386\n", | |
| "... ... ... ...\n", | |
| "1981 0.069564 0.247668 0.109612\n", | |
| "1982 0.067343 0.247982 0.107810\n", | |
| "1983 0.064590 0.250570 0.103872\n", | |
| "1984 0.062247 0.249121 0.104434\n", | |
| "1985 0.060067 0.249074 0.106783\n", | |
| "1986 0.058999 0.248461 0.108102\n", | |
| "1987 0.057410 0.248466 0.108872\n", | |
| "1988 0.054987 0.250193 0.108163\n", | |
| "1989 0.052868 0.251095 0.106309\n", | |
| "1990 0.049690 0.254481 0.104817\n", | |
| "1991 0.046487 0.260756 0.103390\n", | |
| "1992 0.043886 0.269240 0.101575\n", | |
| "1993 0.042119 0.271248 0.100591\n", | |
| "1994 0.039973 0.278569 0.096975\n", | |
| "1995 0.038017 0.284643 0.091720\n", | |
| "1996 0.037067 0.289856 0.087609\n", | |
| "1997 0.036652 0.293351 0.083793\n", | |
| "1998 0.035442 0.298259 0.079016\n", | |
| "1999 0.034149 0.304703 0.076184\n", | |
| "2000 0.032753 0.313060 0.073000\n", | |
| "2001 0.031352 0.317495 0.071687\n", | |
| "2002 0.028794 0.325086 0.069397\n", | |
| "2003 0.027069 0.336344 0.066197\n", | |
| "2004 0.026118 0.341151 0.064781\n", | |
| "2005 0.025420 0.344319 0.062806\n", | |
| "2006 0.025075 0.351666 0.060338\n", | |
| "2007 0.024451 0.358274 0.059634\n", | |
| "2008 0.023574 0.361101 0.060342\n", | |
| "2009 0.023398 0.362523 0.057223\n", | |
| "2010 0.023387 0.362771 0.058168\n", | |
| "\n", | |
| "[131 rows x 3 columns]" | |
| ] | |
| }, | |
| "execution_count": 43, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "letter_prop = table / table.sum()\n", | |
| "dny_ts = letter_prop.ix[['d', 'n', 'y'], 'M'].T\n", | |
| "dny_ts" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "이를 차트로 표시하면, " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 44, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x10fa79278>" | |
| ] | |
| }, | |
| "execution_count": 44, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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iP8v+Q3xKPNdddR2FAgpxKOYQK/61gsAigTn/CfmImMQYpm6ayoqIFfwV/RcH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\nd9mlsKtVs0MYU1Pt+GMfGFr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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10ce3feb8>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "dny_ts.plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "전체 연도로 패턴을 보니, 확실히 \"n\"으로 끝나는 빈도가 증가하고 있다.\n", | |
| "\n", | |
| "## 성별이 바뀌는 이름\n", | |
| "\n", | |
| "성별이 바뀌는 이름들이 있다. Lesley, Leslie 이름이 대표적인 예. 이를 구체적으로 확인해보자. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 45, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "array(['Leslie', 'Lesley', 'Leslee', 'Lesli', 'Lesly'], dtype=object)" | |
| ] | |
| }, | |
| "execution_count": 45, | |
| "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": 46, | |
| "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": 46, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "filtered = top1000[top1000.name.isin(lesley_like)]\n", | |
| "filtered.groupby('name').births.sum()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 47, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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>8.0</td>\n", | |
| " <td>79.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1881</th>\n", | |
| " <td>11.0</td>\n", | |
| " <td>92.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1882</th>\n", | |
| " <td>9.0</td>\n", | |
| " <td>128.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1883</th>\n", | |
| " <td>7.0</td>\n", | |
| " <td>125.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1884</th>\n", | |
| " <td>15.0</td>\n", | |
| " <td>125.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1885</th>\n", | |
| " <td>10.0</td>\n", | |
| " <td>122.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1886</th>\n", | |
| " <td>8.0</td>\n", | |
| " <td>136.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1887</th>\n", | |
| " <td>12.0</td>\n", | |
| " <td>166.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1888</th>\n", | |
| " <td>23.0</td>\n", | |
| " <td>175.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1889</th>\n", | |
| " <td>23.0</td>\n", | |
| " <td>155.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>20.0</td>\n", | |
| " <td>181.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>28.0</td>\n", | |
| " <td>164.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>22.0</td>\n", | |
| " <td>207.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>26.0</td>\n", | |
| " <td>185.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>36.0</td>\n", | |
| " <td>223.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>22.0</td>\n", | |
| " <td>235.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>27.0</td>\n", | |
| " <td>237.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>34.0</td>\n", | |
| " <td>222.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>24.0</td>\n", | |
| " <td>236.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>18.0</td>\n", | |
| " <td>181.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>30.0</td>\n", | |
| " <td>285.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>29.0</td>\n", | |
| " <td>204.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>37.0</td>\n", | |
| " <td>251.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>24.0</td>\n", | |
| " <td>244.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>30.0</td>\n", | |
| " <td>243.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>35.0</td>\n", | |
| " <td>247.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>29.0</td>\n", | |
| " <td>263.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>34.0</td>\n", | |
| " <td>273.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>41.0</td>\n", | |
| " <td>290.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>35.0</td>\n", | |
| " <td>292.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>5796.0</td>\n", | |
| " <td>500.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>5814.0</td>\n", | |
| " <td>430.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>4975.0</td>\n", | |
| " <td>414.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>4419.0</td>\n", | |
| " <td>367.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>4168.0</td>\n", | |
| " <td>331.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>3741.0</td>\n", | |
| " <td>379.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>3666.0</td>\n", | |
| " <td>290.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>3555.0</td>\n", | |
| " <td>318.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>3259.0</td>\n", | |
| " <td>327.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>3268.0</td>\n", | |
| " <td>295.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>2920.0</td>\n", | |
| " <td>277.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>2836.0</td>\n", | |
| " <td>216.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>2607.0</td>\n", | |
| " <td>201.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>2685.0</td>\n", | |
| " <td>207.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>2782.0</td>\n", | |
| " <td>186.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>3584.0</td>\n", | |
| " <td>176.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>3847.0</td>\n", | |
| " <td>158.0</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>4289.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>4693.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>5019.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>4920.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>4708.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>4924.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>4694.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>4284.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2006</th>\n", | |
| " <td>4166.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2007</th>\n", | |
| " <td>3805.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2008</th>\n", | |
| " <td>3022.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2009</th>\n", | |
| " <td>2573.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2010</th>\n", | |
| " <td>2060.0</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>131 rows × 2 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "sex F M\n", | |
| "year \n", | |
| "1880 8.0 79.0\n", | |
| "1881 11.0 92.0\n", | |
| "1882 9.0 128.0\n", | |
| "1883 7.0 125.0\n", | |
| "1884 15.0 125.0\n", | |
| "1885 10.0 122.0\n", | |
| "1886 8.0 136.0\n", | |
| "1887 12.0 166.0\n", | |
| "1888 23.0 175.0\n", | |
| "1889 23.0 155.0\n", | |
| "1890 20.0 181.0\n", | |
| "1891 28.0 164.0\n", | |
| "1892 22.0 207.0\n", | |
| "1893 26.0 185.0\n", | |
| "1894 36.0 223.0\n", | |
| "1895 22.0 235.0\n", | |
| "1896 27.0 237.0\n", | |
| "1897 34.0 222.0\n", | |
| "1898 24.0 236.0\n", | |
| "1899 18.0 181.0\n", | |
| "1900 30.0 285.0\n", | |
| "1901 29.0 204.0\n", | |
| "1902 37.0 251.0\n", | |
| "1903 24.0 244.0\n", | |
| "1904 30.0 243.0\n", | |
| "1905 35.0 247.0\n", | |
| "1906 29.0 263.0\n", | |
| "1907 34.0 273.0\n", | |
| "1908 41.0 290.0\n", | |
| "1909 35.0 292.0\n", | |
| "... ... ...\n", | |
| "1981 5796.0 500.0\n", | |
| "1982 5814.0 430.0\n", | |
| "1983 4975.0 414.0\n", | |
| "1984 4419.0 367.0\n", | |
| "1985 4168.0 331.0\n", | |
| "1986 3741.0 379.0\n", | |
| "1987 3666.0 290.0\n", | |
| "1988 3555.0 318.0\n", | |
| "1989 3259.0 327.0\n", | |
| "1990 3268.0 295.0\n", | |
| "1991 2920.0 277.0\n", | |
| "1992 2836.0 216.0\n", | |
| "1993 2607.0 201.0\n", | |
| "1994 2685.0 207.0\n", | |
| "1995 2782.0 186.0\n", | |
| "1996 3584.0 176.0\n", | |
| "1997 3847.0 158.0\n", | |
| "1998 4289.0 NaN\n", | |
| "1999 4693.0 NaN\n", | |
| "2000 5019.0 NaN\n", | |
| "2001 4920.0 NaN\n", | |
| "2002 4708.0 NaN\n", | |
| "2003 4924.0 NaN\n", | |
| "2004 4694.0 NaN\n", | |
| "2005 4284.0 NaN\n", | |
| "2006 4166.0 NaN\n", | |
| "2007 3805.0 NaN\n", | |
| "2008 3022.0 NaN\n", | |
| "2009 2573.0 NaN\n", | |
| "2010 2060.0 NaN\n", | |
| "\n", | |
| "[131 rows x 2 columns]" | |
| ] | |
| }, | |
| "execution_count": 47, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "table = filtered.pivot_table('births', index='year', columns='sex', aggfunc=sum)\n", | |
| "table" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 48, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": true | |
| }, | |
| "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", | |
| " <tr>\n", | |
| " <th>1885</th>\n", | |
| " <td>0.075758</td>\n", | |
| " <td>0.924242</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1886</th>\n", | |
| " <td>0.055556</td>\n", | |
| " <td>0.944444</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1887</th>\n", | |
| " <td>0.067416</td>\n", | |
| " <td>0.932584</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1888</th>\n", | |
| " <td>0.116162</td>\n", | |
| " <td>0.883838</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1889</th>\n", | |
| " <td>0.129213</td>\n", | |
| " <td>0.870787</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1890</th>\n", | |
| " <td>0.099502</td>\n", | |
| " <td>0.900498</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1891</th>\n", | |
| " <td>0.145833</td>\n", | |
| " <td>0.854167</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1892</th>\n", | |
| " <td>0.096070</td>\n", | |
| " <td>0.903930</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1893</th>\n", | |
| " <td>0.123223</td>\n", | |
| " <td>0.876777</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1894</th>\n", | |
| " <td>0.138996</td>\n", | |
| " <td>0.861004</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1895</th>\n", | |
| " <td>0.085603</td>\n", | |
| " <td>0.914397</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1896</th>\n", | |
| " <td>0.102273</td>\n", | |
| " <td>0.897727</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1897</th>\n", | |
| " <td>0.132812</td>\n", | |
| " <td>0.867188</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1898</th>\n", | |
| " <td>0.092308</td>\n", | |
| " <td>0.907692</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1899</th>\n", | |
| " <td>0.090452</td>\n", | |
| " <td>0.909548</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1900</th>\n", | |
| " <td>0.095238</td>\n", | |
| " <td>0.904762</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1901</th>\n", | |
| " <td>0.124464</td>\n", | |
| " <td>0.875536</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1902</th>\n", | |
| " <td>0.128472</td>\n", | |
| " <td>0.871528</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1903</th>\n", | |
| " <td>0.089552</td>\n", | |
| " <td>0.910448</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1904</th>\n", | |
| " <td>0.109890</td>\n", | |
| " <td>0.890110</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1905</th>\n", | |
| " <td>0.124113</td>\n", | |
| " <td>0.875887</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1906</th>\n", | |
| " <td>0.099315</td>\n", | |
| " <td>0.900685</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1907</th>\n", | |
| " <td>0.110749</td>\n", | |
| " <td>0.889251</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1908</th>\n", | |
| " <td>0.123867</td>\n", | |
| " <td>0.876133</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1909</th>\n", | |
| " <td>0.107034</td>\n", | |
| " <td>0.892966</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1981</th>\n", | |
| " <td>0.920584</td>\n", | |
| " <td>0.079416</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1982</th>\n", | |
| " <td>0.931134</td>\n", | |
| " <td>0.068866</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1983</th>\n", | |
| " <td>0.923177</td>\n", | |
| " <td>0.076823</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1984</th>\n", | |
| " <td>0.923318</td>\n", | |
| " <td>0.076682</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1985</th>\n", | |
| " <td>0.926428</td>\n", | |
| " <td>0.073572</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1986</th>\n", | |
| " <td>0.908010</td>\n", | |
| " <td>0.091990</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1987</th>\n", | |
| " <td>0.926694</td>\n", | |
| " <td>0.073306</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1988</th>\n", | |
| " <td>0.917893</td>\n", | |
| " <td>0.082107</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1989</th>\n", | |
| " <td>0.908812</td>\n", | |
| " <td>0.091188</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1990</th>\n", | |
| " <td>0.917205</td>\n", | |
| " <td>0.082795</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1991</th>\n", | |
| " <td>0.913356</td>\n", | |
| " <td>0.086644</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1992</th>\n", | |
| " <td>0.929227</td>\n", | |
| " <td>0.070773</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1993</th>\n", | |
| " <td>0.928419</td>\n", | |
| " <td>0.071581</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1994</th>\n", | |
| " <td>0.928423</td>\n", | |
| " <td>0.071577</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1995</th>\n", | |
| " <td>0.937332</td>\n", | |
| " <td>0.062668</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1996</th>\n", | |
| " <td>0.953191</td>\n", | |
| " <td>0.046809</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1997</th>\n", | |
| " <td>0.960549</td>\n", | |
| " <td>0.039451</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1998</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1999</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2000</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2001</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2002</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2003</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2004</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2005</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2006</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2007</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2008</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2009</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2010</th>\n", | |
| " <td>1.000000</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>131 rows × 2 columns</p>\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\n", | |
| "1885 0.075758 0.924242\n", | |
| "1886 0.055556 0.944444\n", | |
| "1887 0.067416 0.932584\n", | |
| "1888 0.116162 0.883838\n", | |
| "1889 0.129213 0.870787\n", | |
| "1890 0.099502 0.900498\n", | |
| "1891 0.145833 0.854167\n", | |
| "1892 0.096070 0.903930\n", | |
| "1893 0.123223 0.876777\n", | |
| "1894 0.138996 0.861004\n", | |
| "1895 0.085603 0.914397\n", | |
| "1896 0.102273 0.897727\n", | |
| "1897 0.132812 0.867188\n", | |
| "1898 0.092308 0.907692\n", | |
| "1899 0.090452 0.909548\n", | |
| "1900 0.095238 0.904762\n", | |
| "1901 0.124464 0.875536\n", | |
| "1902 0.128472 0.871528\n", | |
| "1903 0.089552 0.910448\n", | |
| "1904 0.109890 0.890110\n", | |
| "1905 0.124113 0.875887\n", | |
| "1906 0.099315 0.900685\n", | |
| "1907 0.110749 0.889251\n", | |
| "1908 0.123867 0.876133\n", | |
| "1909 0.107034 0.892966\n", | |
| "... ... ...\n", | |
| "1981 0.920584 0.079416\n", | |
| "1982 0.931134 0.068866\n", | |
| "1983 0.923177 0.076823\n", | |
| "1984 0.923318 0.076682\n", | |
| "1985 0.926428 0.073572\n", | |
| "1986 0.908010 0.091990\n", | |
| "1987 0.926694 0.073306\n", | |
| "1988 0.917893 0.082107\n", | |
| "1989 0.908812 0.091188\n", | |
| "1990 0.917205 0.082795\n", | |
| "1991 0.913356 0.086644\n", | |
| "1992 0.929227 0.070773\n", | |
| "1993 0.928419 0.071581\n", | |
| "1994 0.928423 0.071577\n", | |
| "1995 0.937332 0.062668\n", | |
| "1996 0.953191 0.046809\n", | |
| "1997 0.960549 0.039451\n", | |
| "1998 1.000000 NaN\n", | |
| "1999 1.000000 NaN\n", | |
| "2000 1.000000 NaN\n", | |
| "2001 1.000000 NaN\n", | |
| "2002 1.000000 NaN\n", | |
| "2003 1.000000 NaN\n", | |
| "2004 1.000000 NaN\n", | |
| "2005 1.000000 NaN\n", | |
| "2006 1.000000 NaN\n", | |
| "2007 1.000000 NaN\n", | |
| "2008 1.000000 NaN\n", | |
| "2009 1.000000 NaN\n", | |
| "2010 1.000000 NaN\n", | |
| "\n", | |
| "[131 rows x 2 columns]" | |
| ] | |
| }, | |
| "execution_count": 48, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "table = table.div(table.sum(1), axis=0)\n", | |
| "table" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 49, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.axes._subplots.AxesSubplot at 0x1102b5630>" | |
| ] | |
| }, | |
| "execution_count": 49, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
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INm7cSDKZjBo3bkwxMTFSh2vSPvjgA4qMjKTU1FQaPHiwWV1sl5JJJ3Eioj179lCnTp0K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\ngg==\n", | |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10fa5f4a8>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "table.plot(style={'M': 'k-', 'F': 'k--'})" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "\"Lesl~\"로 시작하는 이름은 1940년대에는 남자이름이었다가 그후 빠르게 여자이름으로 바뀜. " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.5.2" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 0 | |
| } |
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