{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 美国婴儿名字数据\n",
    "* 数据来源： https://www.ssa.gov/oact/babynames/limits.html\n",
    "* 包括1880至2016所有年份出生的婴儿名。\n",
    "* 我们使用这个例子来展示python强大的数据总结和可视化功能，代码细节将在后续课程中讲解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import re as re\n",
    "import scipy\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取数据\n",
    "\n",
    "years = range(1880, 2017) # range函数：第三节课讲解\n",
    "pieces = [] # 列表：第二节课讲解\n",
    "columns = ['name', 'gender', 'frequency']\n",
    "\n",
    "for year in years: # for循环：第二节课讲解\n",
    "    path = './names/yob%d.txt' % year \n",
    "    frame = pd.read_csv(path, names=columns) # 数据读取： 第八节课讲解\n",
    "    frame['year'] = year # 增加变量year：第八节课讲解\n",
    "    pieces.append(frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "baby_names = pd.concat(pieces, ignore_index=True) # 转换为pd数据： 第五节课讲解"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>frequency</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>796</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>1891864</th>\n",
       "      <td>Zariyan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891865</th>\n",
       "      <td>Zarren</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891866</th>\n",
       "      <td>Zaryn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891867</th>\n",
       "      <td>Zaxon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891868</th>\n",
       "      <td>Zaxtyn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891869</th>\n",
       "      <td>Zaye</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891870</th>\n",
       "      <td>Zaymar</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891871</th>\n",
       "      <td>Zaymir</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891872</th>\n",
       "      <td>Zaynn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891873</th>\n",
       "      <td>Zayshaun</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891874</th>\n",
       "      <td>Zedric</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891875</th>\n",
       "      <td>Zekariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891876</th>\n",
       "      <td>Zelan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891877</th>\n",
       "      <td>Zephen</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891878</th>\n",
       "      <td>Zephyrus</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891879</th>\n",
       "      <td>Zeric</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891880</th>\n",
       "      <td>Zerin</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891881</th>\n",
       "      <td>Zethan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891882</th>\n",
       "      <td>Zihao</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891883</th>\n",
       "      <td>Zimo</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891884</th>\n",
       "      <td>Zinn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891885</th>\n",
       "      <td>Zirui</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891886</th>\n",
       "      <td>Ziya</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891887</th>\n",
       "      <td>Ziyang</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891888</th>\n",
       "      <td>Zoel</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891889</th>\n",
       "      <td>Zolton</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891890</th>\n",
       "      <td>Zurich</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891891</th>\n",
       "      <td>Zyahir</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891892</th>\n",
       "      <td>Zyel</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891893</th>\n",
       "      <td>Zylyn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1891894 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name gender  frequency  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        796  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",
       "1891864    Zariyan      M          5  2016\n",
       "1891865     Zarren      M          5  2016\n",
       "1891866      Zaryn      M          5  2016\n",
       "1891867      Zaxon      M          5  2016\n",
       "1891868     Zaxtyn      M          5  2016\n",
       "1891869       Zaye      M          5  2016\n",
       "1891870     Zaymar      M          5  2016\n",
       "1891871     Zaymir      M          5  2016\n",
       "1891872      Zaynn      M          5  2016\n",
       "1891873   Zayshaun      M          5  2016\n",
       "1891874     Zedric      M          5  2016\n",
       "1891875   Zekariah      M          5  2016\n",
       "1891876      Zelan      M          5  2016\n",
       "1891877     Zephen      M          5  2016\n",
       "1891878   Zephyrus      M          5  2016\n",
       "1891879      Zeric      M          5  2016\n",
       "1891880      Zerin      M          5  2016\n",
       "1891881     Zethan      M          5  2016\n",
       "1891882      Zihao      M          5  2016\n",
       "1891883       Zimo      M          5  2016\n",
       "1891884       Zinn      M          5  2016\n",
       "1891885      Zirui      M          5  2016\n",
       "1891886       Ziya      M          5  2016\n",
       "1891887     Ziyang      M          5  2016\n",
       "1891888       Zoel      M          5  2016\n",
       "1891889     Zolton      M          5  2016\n",
       "1891890     Zurich      M          5  2016\n",
       "1891891     Zyahir      M          5  2016\n",
       "1891892       Zyel      M          5  2016\n",
       "1891893      Zylyn      M          5  2016\n",
       "\n",
       "[1891894 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>frequency</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name gender  frequency  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"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 总共189万行数据\n",
    "# 查看前十行数据\n",
    "# 注意：python默认的索引从0开始\n",
    "# 第一行：Mary是个女性名字（gender为F），在1880年总共有7065个婴儿取名叫Mary\n",
    "baby_names.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.891894e+06</td>\n",
       "      <td>1.891894e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.821106e+02</td>\n",
       "      <td>1.974122e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.544197e+03</td>\n",
       "      <td>3.386497e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>1.880000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.000000e+00</td>\n",
       "      <td>1.951000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.200000e+01</td>\n",
       "      <td>1.984000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.200000e+01</td>\n",
       "      <td>2.002000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.968500e+04</td>\n",
       "      <td>2.016000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          frequency          year\n",
       "count  1.891894e+06  1.891894e+06\n",
       "mean   1.821106e+02  1.974122e+03\n",
       "std    1.544197e+03  3.386497e+01\n",
       "min    5.000000e+00  1.880000e+03\n",
       "25%    7.000000e+00  1.951000e+03\n",
       "50%    1.200000e+01  1.984000e+03\n",
       "75%    3.200000e+01  2.002000e+03\n",
       "max    9.968500e+04  2.016000e+03"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_names.describe() # 使用describe方法查看数据基本信息"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据科学的一个特征是通过数据回答问题\n",
    "### 哪些名字出现的频率最高？ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>frequency</th>\n",
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       "      <th>name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Aaban</th>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aabha</th>\n",
       "      <td>35</td>\n",
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       "      <th>Aabid</th>\n",
       "      <td>10</td>\n",
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       "      <th>Aabir</th>\n",
       "      <td>5</td>\n",
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       "      <th>Aabriella</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aada</th>\n",
       "      <td>5</td>\n",
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       "      <th>Aadam</th>\n",
       "      <td>236</td>\n",
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       "      <th>Aadan</th>\n",
       "      <td>122</td>\n",
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       "      <th>Aadarsh</th>\n",
       "      <td>184</td>\n",
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       "      <th>Aaden</th>\n",
       "      <td>4414</td>\n",
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       "      <th>Aadesh</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhav</th>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhavan</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhi</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhira</th>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhvik</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhvika</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhya</th>\n",
       "      <td>1188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadhyan</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadi</th>\n",
       "      <td>781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadian</th>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>Aadil</th>\n",
       "      <td>326</td>\n",
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       "    <tr>\n",
       "      <th>Aadin</th>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadish</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadison</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
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       "      <th>Aadit</th>\n",
       "      <td>313</td>\n",
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       "      <th>Aadith</th>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aadithya</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaditri</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaditya</th>\n",
       "      <td>524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyria</th>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyriah</th>\n",
       "      <td>372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrian</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyriana</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrianna</th>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrie</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyriel</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrielle</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrihanna</th>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrin</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrion</th>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyriyah</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyron</th>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyrus</th>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zysean</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyshaun</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyshawn</th>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyshon</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyshonne</th>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zytaevius</th>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>Zytaveon</th>\n",
       "      <td>16</td>\n",
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       "    <tr>\n",
       "      <th>Zytavion</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>43</td>\n",
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       "    <tr>\n",
       "      <th>Zyus</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyva</th>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>Zyvion</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyvon</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyyanna</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zyyon</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zzyzx</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96174 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           frequency\n",
       "name                \n",
       "Aaban             96\n",
       "Aabha             35\n",
       "Aabid             10\n",
       "Aabir              5\n",
       "Aabriella         26\n",
       "Aada               5\n",
       "Aadam            236\n",
       "Aadan            122\n",
       "Aadarsh          184\n",
       "Aaden           4414\n",
       "Aadesh            15\n",
       "Aadhav           161\n",
       "Aadhavan          30\n",
       "Aadhi             28\n",
       "Aadhira           51\n",
       "Aadhvik           28\n",
       "Aadhvika           9\n",
       "Aadhya          1188\n",
       "Aadhyan           12\n",
       "Aadi             781\n",
       "Aadian             5\n",
       "Aadil            326\n",
       "Aadin            117\n",
       "Aadish            22\n",
       "Aadison           11\n",
       "Aadit            313\n",
       "Aadith            61\n",
       "Aadithya          11\n",
       "Aaditri           37\n",
       "Aaditya          524\n",
       "...              ...\n",
       "Zyria            356\n",
       "Zyriah           372\n",
       "Zyrian            10\n",
       "Zyriana           30\n",
       "Zyrianna          41\n",
       "Zyrie             25\n",
       "Zyriel            16\n",
       "Zyrielle          27\n",
       "Zyrihanna         45\n",
       "Zyrin             10\n",
       "Zyrion           101\n",
       "Zyriyah           16\n",
       "Zyron            188\n",
       "Zyrus             62\n",
       "Zysean             5\n",
       "Zyshaun           34\n",
       "Zyshawn          146\n",
       "Zyshon            19\n",
       "Zyshonne         101\n",
       "Zytaevius          5\n",
       "Zytaveon          16\n",
       "Zytavion           5\n",
       "Zytavious         43\n",
       "Zyus               5\n",
       "Zyva               8\n",
       "Zyvion             5\n",
       "Zyvon              6\n",
       "Zyyanna            6\n",
       "Zyyon              6\n",
       "Zzyzx              5\n",
       "\n",
       "[96174 rows x 1 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_names.groupby('name').agg({'frequency': sum})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Michael</th>\n",
       "      <td>4359820</td>\n",
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       "      <th>Mary</th>\n",
       "      <td>4135851</td>\n",
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       "      <th>William</th>\n",
       "      <td>4103456</td>\n",
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       "      <th>Richard</th>\n",
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       "      <th>Charles</th>\n",
       "      <td>2391199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thomas</th>\n",
       "      <td>2306216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Christopher</th>\n",
       "      <td>2023318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daniel</th>\n",
       "      <td>1903647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elizabeth</th>\n",
       "      <td>1625783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matthew</th>\n",
       "      <td>1584209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Patricia</th>\n",
       "      <td>1576343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>George</th>\n",
       "      <td>1470933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jennifer</th>\n",
       "      <td>1470081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Linda</th>\n",
       "      <td>1455566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barbara</th>\n",
       "      <td>1437865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anthony</th>\n",
       "      <td>1430880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Donald</th>\n",
       "      <td>1415938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paul</th>\n",
       "      <td>1390956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mark</th>\n",
       "      <td>1352418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edward</th>\n",
       "      <td>1291786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steven</th>\n",
       "      <td>1282770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andrew</th>\n",
       "      <td>1280459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kenneth</th>\n",
       "      <td>1276188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Margaret</th>\n",
       "      <td>1248131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Joshua</th>\n",
       "      <td>1198955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luxanna</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luvonne</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luvonia</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luvert</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luvender</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luvella</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyddia</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lydya</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lytzi</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyelah</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lytina</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyshon</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyrric</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyron</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynnete</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynnessa</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynneann</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynndsey</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyniya</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynissa</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynis</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyndyn</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyndsae</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynder</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lynal</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyllyan</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyllianna</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyliann</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyjah</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zzyzx</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96174 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             frequency\n",
       "name                  \n",
       "James          5159306\n",
       "John           5127501\n",
       "Robert         4829274\n",
       "Michael        4359820\n",
       "Mary           4135851\n",
       "William        4103456\n",
       "David          3613916\n",
       "Joseph         2603475\n",
       "Richard        2570304\n",
       "Charles        2391199\n",
       "Thomas         2306216\n",
       "Christopher    2023318\n",
       "Daniel         1903647\n",
       "Elizabeth      1625783\n",
       "Matthew        1584209\n",
       "Patricia       1576343\n",
       "George         1470933\n",
       "Jennifer       1470081\n",
       "Linda          1455566\n",
       "Barbara        1437865\n",
       "Anthony        1430880\n",
       "Donald         1415938\n",
       "Paul           1390956\n",
       "Mark           1352418\n",
       "Edward         1291786\n",
       "Steven         1282770\n",
       "Andrew         1280459\n",
       "Kenneth        1276188\n",
       "Margaret       1248131\n",
       "Joshua         1198955\n",
       "...                ...\n",
       "Luxanna              5\n",
       "Luvonne              5\n",
       "Luvonia              5\n",
       "Luvert               5\n",
       "Luvender             5\n",
       "Luvella              5\n",
       "Lyddia               5\n",
       "Lydya                5\n",
       "Lytzi                5\n",
       "Lyelah               5\n",
       "Lytina               5\n",
       "Lyshon               5\n",
       "Lyrric               5\n",
       "Lyron                5\n",
       "Lynnete              5\n",
       "Lynnessa             5\n",
       "Lynneann             5\n",
       "Lynndsey             5\n",
       "Lyniya               5\n",
       "Lynissa              5\n",
       "Lynis                5\n",
       "Lyndyn               5\n",
       "Lyndsae              5\n",
       "Lynder               5\n",
       "Lynal                5\n",
       "Lyllyan              5\n",
       "Lyllianna            5\n",
       "Lyliann              5\n",
       "Lyjah                5\n",
       "Zzyzx                5\n",
       "\n",
       "[96174 rows x 1 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# James, John, Robert, Micheal, Mary...都是耳熟能详的名字\n",
    "baby_names.groupby('name').agg({'frequency': sum}).sort_values(by=['frequency'], ascending=[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 每年出生的男孩和女孩的个数分别是多少？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用pivot_table方法查看（第六节课讲解）\n",
    "freq_by_gender_year = baby_names.pivot_table(index ='year', columns='gender',\n",
    "                                             values = 'frequency', aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</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>2012</th>\n",
       "      <td>1756347</td>\n",
       "      <td>1892094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>1749061</td>\n",
       "      <td>1885683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>1779496</td>\n",
       "      <td>1913434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>1776538</td>\n",
       "      <td>1907211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>1756647</td>\n",
       "      <td>1880674</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "gender        F        M\n",
       "year                    \n",
       "2012    1756347  1892094\n",
       "2013    1749061  1885683\n",
       "2014    1779496  1913434\n",
       "2015    1776538  1907211\n",
       "2016    1756647  1880674"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用tail方法查看最近几年出生人数\n",
    "freq_by_gender_year.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据可视化往往是数据分析的第一步"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1253081d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LRj4FOz+Djf9zdqksBfnWiL7WQ6Fl73PHm7SGwQ/A/mVwYk+dF6siNZR84GFjTFdgIHCf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\nGoUVFGOMMY3CCooxxphGYQXFGGNMo/h/lG4nvsaxzzwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x125308f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 一行命令即可做出高质量图形\n",
    "freq_by_gender_year.plot(title='Frequency by year and gender')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 起名趋势分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "增加一个变量rank，这个是根据年份性别依据名字出现频率所产生的次序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "baby_names['ranked'] = baby_names.groupby(['year', 'gender'])['frequency'].rank(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>frequency</th>\n",
       "      <th>year</th>\n",
       "      <th>ranked</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>1.0</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>2.0</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>3.0</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>4.0</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>5.0</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>6.0</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>7.0</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>8.0</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>9.0</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>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name gender  frequency  year  ranked\n",
       "0       Mary      F       7065  1880     1.0\n",
       "1       Anna      F       2604  1880     2.0\n",
       "2       Emma      F       2003  1880     3.0\n",
       "3  Elizabeth      F       1939  1880     4.0\n",
       "4     Minnie      F       1746  1880     5.0\n",
       "5   Margaret      F       1578  1880     6.0\n",
       "6        Ida      F       1472  1880     7.0\n",
       "7      Alice      F       1414  1880     8.0\n",
       "8     Bertha      F       1320  1880     9.0\n",
       "9      Sarah      F       1288  1880    10.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baby_names.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算每个名每年按性别占总出生人数的百分比\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_pct(group):# 自定义函数，第三节课讲解\n",
    "    group['pct'] = group.frequency / group.frequency.sum()*100\n",
    "    return group\n",
    "\n",
    "# groupby和apply函数在课程第二部分讲解\n",
    "baby_names = baby_names.groupby(['year', 'gender']).apply(add_pct) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>gender</th>\n",
       "      <th>frequency</th>\n",
       "      <th>year</th>\n",
       "      <th>ranked</th>\n",
       "      <th>pct</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>1.0</td>\n",
       "      <td>7.764419</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>2.0</td>\n",
       "      <td>2.861790</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>3.0</td>\n",
       "      <td>2.201292</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>4.0</td>\n",
       "      <td>2.130957</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>5.0</td>\n",
       "      <td>1.918850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name gender  frequency  year  ranked       pct\n",
       "0       Mary      F       7065  1880     1.0  7.764419\n",
       "1       Anna      F       2604  1880     2.0  2.861790\n",
       "2       Emma      F       2003  1880     3.0  2.201292\n",
       "3  Elizabeth      F       1939  1880     4.0  2.130957\n",
       "4     Minnie      F       1746  1880     5.0  1.918850"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看新加的百分比（pct）\n",
    "baby_names.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 首先查看每先查看每年最流行的名字所占百分比趋势"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将数据分为男孩和女孩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dff = baby_names[baby_names.gender == 'F'] #逻辑判断 ==， 第二节课讲解\n",
    "dfm = baby_names[baby_names.gender == 'M']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "获取每年排名第一的名字"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rank1m = dfm[dfm.ranked == 1]\n",
    "rank1f = dff[dff.ranked == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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h8JoqY3OsUpUgvPxbYO3bc3EjkDNE6Ix5gJ2Fub/ekuL+m2Dt+bthfUCXaP4GcVwnWTUC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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120b45550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rank1m.year, rank1m.pct, color=\"blue\", linewidth = 2, label = 'Boys')\n",
    "plt.fill_between(rank1m.year, rank1m.pct, color=\"blue\", alpha = 0.1, interpolate=True)\n",
    "plt.xlim(1880,2012)\n",
    "plt.ylim(0,9)\n",
    "plt.xticks(scipy.arange(1880,2012,10), rotation=70)\n",
    "plt.title(\"Popularity of #1 boys' name by year\", size=18, color=\"blue\")\n",
    "plt.xlabel('Year', size=15)\n",
    "plt.ylabel('% of male births', size=15)\n",
    "plt.show()\n",
    "plt.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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indTyQRHMnm3T006zFszAgeb8diXgVBOynkW0slSblkCMO+6AV181J/F225mJ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\nHto4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120f51ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rank1f.year, rank1f.pct, color=\"red\", linewidth = 2, label = 'Girls')\n",
    "plt.fill_between(rank1f.year, rank1f.pct, color=\"red\", alpha = 0.1, interpolate=True)\n",
    "plt.xlim(1880,2012)\n",
    "plt.ylim(0,9)\n",
    "plt.xticks(scipy.arange(1880,2012,10), rotation=70)\n",
    "plt.title(\"Popularity of #1 girls' name by year\", size=18, color=\"red\")\n",
    "plt.xlabel('Year', size=15)\n",
    "plt.ylabel('% of female births', size=15)\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最流行每年名字所占百分比呈现递减趋势，是什么原因造成的呢？我们将在后续课程中分析！"
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    "## 在以上例子中，我们主要使用了python的可视化功能，以后我们还会介绍经典的统计/机器学习模型来更好得洞察数据中信息。"
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