三清洗女性用户的配偶要求.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_columns = None   # 取消最大行列显示\n",
    "#pd.options.display.max_rows = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 导入之前的 女性.csv 数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>区域</th>\n",
       "      <th>年龄</th>\n",
       "      <th>民族</th>\n",
       "      <th>籍贯</th>\n",
       "      <th>星座</th>\n",
       "      <th>学历</th>\n",
       "      <th>婚姻状况</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>体型</th>\n",
       "      <th>职业</th>\n",
       "      <th>收入</th>\n",
       "      <th>是否吸烟</th>\n",
       "      <th>是否喝酒</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>车辆情况</th>\n",
       "      <th>子女情况</th>\n",
       "      <th>内心独白</th>\n",
       "      <th>兴趣爱好</th>\n",
       "      <th>择偶条件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>玉水福兰</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>33岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>吉林通化</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>165cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>3000元以下</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>88年属龙的，摩羯座，寻找有眼缘的聊得来的他共度余生</td>\n",
       "      <td>喜欢的一道菜：土豆丝|欣赏的一个名人：特斯拉|喜欢做的事：跳拉丁舞|喜欢的一首歌：未填写|喜...</td>\n",
       "      <td>33-40岁|175-195cm|不要吸烟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>找爱的玫瑰</td>\n",
       "      <td>北京</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>47岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北张家口</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>158cm</td>\n",
       "      <td>55kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>和家人同住</td>\n",
       "      <td>已买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>生活规律，按时睡觉，就是爱美，出的厅堂下得厨房！喜欢厨艺，喜欢跳东方舞！</td>\n",
       "      <td>喜欢的一道菜：酸菜牛肉汤|欣赏的一个名人：马云|喜欢的一首歌：甜蜜蜜|喜欢的一本书：水浒传|...</td>\n",
       "      <td>45-54岁|170-188cm|月薪:1.2万以上|大学本科|不要吸烟|是否想要孩子:以后...</td>\n",
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      ],
      "text/plain": [
       "      名称  城市   区域     年龄  民族     籍贯                星座       学历  婚姻状况       身高  \\\n",
       "0   玉水福兰  北京  朝阳区   33岁   汉族   吉林通化  魔羯座(12.22-01.19)      中专    离异    165cm    \n",
       "1  找爱的玫瑰  北京  海淀区   47岁   汉族  河北张家口  魔羯座(12.22-01.19)   高中及以下    离异    158cm    \n",
       "\n",
       "     体重    体型    职业            收入 是否吸烟 是否喝酒   住房情况 车辆情况      子女情况  \\\n",
       "0  52kg  富线条美  其他职业       3000元以下  不吸烟  不喝酒     租房  未买车  有孩子且住在一起   \n",
       "1  55kg  富线条美  其他职业   8001-12000元  不吸烟  不喝酒  和家人同住  已买车  有孩子但不在身边   \n",
       "\n",
       "                                   内心独白  \\\n",
       "0            88年属龙的，摩羯座，寻找有眼缘的聊得来的他共度余生   \n",
       "1  生活规律，按时睡觉，就是爱美，出的厅堂下得厨房！喜欢厨艺，喜欢跳东方舞！   \n",
       "\n",
       "                                                兴趣爱好  \\\n",
       "0  喜欢的一道菜：土豆丝|欣赏的一个名人：特斯拉|喜欢做的事：跳拉丁舞|喜欢的一首歌：未填写|喜...   \n",
       "1  喜欢的一道菜：酸菜牛肉汤|欣赏的一个名人：马云|喜欢的一首歌：甜蜜蜜|喜欢的一本书：水浒传|...   \n",
       "\n",
       "                                                择偶条件  \n",
       "0                              33-40岁|175-195cm|不要吸烟  \n",
       "1  45-54岁|170-188cm|月薪:1.2万以上|大学本科|不要吸烟|是否想要孩子:以后...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r\"C:\\Users\\EDZ\\Desktop\\案列\\珍爱网各城市小姐姐分析\\code\\女性.csv\")\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4370, 22)"
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 22 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "内心独白    4370 non-null object\n",
      "兴趣爱好    4370 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(22)\n",
      "memory usage: 751.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 删除 内心独白 兴趣爱好"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns = ['内心独白', '兴趣爱好'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>区域</th>\n",
       "      <th>年龄</th>\n",
       "      <th>民族</th>\n",
       "      <th>籍贯</th>\n",
       "      <th>星座</th>\n",
       "      <th>学历</th>\n",
       "      <th>婚姻状况</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>体型</th>\n",
       "      <th>职业</th>\n",
       "      <th>收入</th>\n",
       "      <th>是否吸烟</th>\n",
       "      <th>是否喝酒</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>车辆情况</th>\n",
       "      <th>子女情况</th>\n",
       "      <th>择偶条件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>玉水福兰</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>33岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>吉林通化</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>165cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>3000元以下</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>33-40岁|175-195cm|不要吸烟</td>\n",
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       "     名称  城市   区域     年龄  民族    籍贯                星座    学历  婚姻状况       身高  \\\n",
       "0  玉水福兰  北京  朝阳区   33岁   汉族  吉林通化  魔羯座(12.22-01.19)   中专    离异    165cm    \n",
       "\n",
       "     体重    体型    职业        收入 是否吸烟 是否喝酒 住房情况 车辆情况      子女情况  \\\n",
       "0  52kg  富线条美  其他职业   3000元以下  不吸烟  不喝酒   租房  未买车  有孩子且住在一起   \n",
       "\n",
       "                    择偶条件  \n",
       "0  33-40岁|175-195cm|不要吸烟  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 拆分 择偶条件"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 新增 年龄要求  \n",
    "位置在子女情况前面"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                               [33-40岁, 175-195cm, 不要吸烟]\n",
       "1       [45-54岁, 170-188cm, 月薪:1.2万以上, 大学本科, 不要吸烟, 是否想...\n",
       "2                        [31-45岁, 工作地:北京朝阳区, 月薪:8千以上, 未婚]\n",
       "3       [46-53岁, 170-180cm, 工作地:北京朝阳区, 月薪:8千以上, 离异, 体型...\n",
       "4                                       [39-54岁, 月薪:5千以上]\n",
       "                              ...                        \n",
       "4365    [40-47岁, 170-178cm, 工作地:广东珠海, 月薪:2万以上, 体型:一般, ...\n",
       "4366                         [31-45岁, 172-182cm, 月薪:2万以上]\n",
       "4367                 [33-43岁, 170-180cm, 工作地:广东珠海香洲区, 未婚]\n",
       "4368    [29-35岁, 170-185cm, 工作地:广东珠海, 月薪:1.2万以上, 大学本科,...\n",
       "4369                   [49-63岁, 工作地:广东珠海香洲区, 月薪:5万以上, 未婚]\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = df.择偶条件.str.split('|')\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.insert(19, '年龄要求', '不明')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def x(s):\n",
    "    for i in s:\n",
    "        if '岁' in i:\n",
    "            return i\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       33-40岁\n",
       "1       45-54岁\n",
       "2       31-45岁\n",
       "3       46-53岁\n",
       "4       39-54岁\n",
       "         ...  \n",
       "4365    40-47岁\n",
       "4366    31-45岁\n",
       "4367    33-43岁\n",
       "4368    29-35岁\n",
       "4369    49-63岁\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['年龄要求'] = a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 21 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4307 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(21)\n",
      "memory usage: 717.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
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       "      <th>是否喝酒</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>车辆情况</th>\n",
       "      <th>子女情况</th>\n",
       "      <th>年龄要求</th>\n",
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       "    <tr>\n",
       "      <td>107</td>\n",
       "      <td>Mia啦啦啦</td>\n",
       "      <td>北京</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>27岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>黑龙江大庆</td>\n",
       "      <td>天秤座(09.23-10.22)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>164cm</td>\n",
       "      <td>45kg</td>\n",
       "      <td>瘦长</td>\n",
       "      <td>医疗管理</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>不明</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>打算婚后购房</td>\n",
       "      <td>不明</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>None</td>\n",
       "      <td>工作地:北京|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>米谷</td>\n",
       "      <td>上海</td>\n",
       "      <td>长宁区</td>\n",
       "      <td>39岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>海南三亚</td>\n",
       "      <td>天秤座(09.23-10.22)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>166cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>丰满</td>\n",
       "      <td>外贸经理</td>\n",
       "      <td>3000元以下</td>\n",
       "      <td>不明</td>\n",
       "      <td>社交场合会喝酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>None</td>\n",
       "      <td>工作地:上海长宁区|未婚|不要吸烟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>170</td>\n",
       "      <td>格调</td>\n",
       "      <td>上海</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>42岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>不明</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>中专</td>\n",
       "      <td>3001-5000元</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>None</td>\n",
       "      <td>工作地:安徽淮南田家庵区|月薪:5千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>326</td>\n",
       "      <td>Sherry</td>\n",
       "      <td>广州</td>\n",
       "      <td>番禺区</td>\n",
       "      <td>23岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东广州</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>158cm</td>\n",
       "      <td>40kg</td>\n",
       "      <td>保密</td>\n",
       "      <td>外贸专员</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>打算婚后购房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>None</td>\n",
       "      <td>170cm以上|未婚|体型:一般|没有小孩</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>429</td>\n",
       "      <td>清沐宸汐</td>\n",
       "      <td>深圳</td>\n",
       "      <td>龙岗区</td>\n",
       "      <td>23岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>不明</td>\n",
       "      <td>射手座(11.22-12.21)</td>\n",
       "      <td>大专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>150cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>None</td>\n",
       "      <td>170-175cm|工作地:广东深圳龙岗区|月薪:8千以下|大专|未婚|不要吸烟|没有小孩</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4156</td>\n",
       "      <td>依娜</td>\n",
       "      <td>中山</td>\n",
       "      <td>东区街道</td>\n",
       "      <td>38岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>湖南益阳</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>165cm</td>\n",
       "      <td>51kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>销售</td>\n",
       "      <td>3001-5000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>None</td>\n",
       "      <td>167-199cm|工作地:广东中山石岐街道|月薪:2万-5万</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4172</td>\n",
       "      <td>丽Li</td>\n",
       "      <td>中山</td>\n",
       "      <td>东区街道</td>\n",
       "      <td>34岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东湛江</td>\n",
       "      <td>射手座(11.22-12.21)</td>\n",
       "      <td>大专</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>55kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>服务业</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>有孩子且偶尔会一起住</td>\n",
       "      <td>None</td>\n",
       "      <td>170-179cm|工作地:广东中山东区街道|体型:壮实|是否想要孩子:不想要孩子</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4278</td>\n",
       "      <td>喵喵</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>32岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东珠海</td>\n",
       "      <td>天蝎座(10.23-11.21)</td>\n",
       "      <td>大专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>159cm</td>\n",
       "      <td>45kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>设计师</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>社交场合会喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>None</td>\n",
       "      <td>170-190cm|月薪:1.2万以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4295</td>\n",
       "      <td>开心每一天</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>44岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东珠海</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大专</td>\n",
       "      <td>离异</td>\n",
       "      <td>155cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>一般</td>\n",
       "      <td>大专</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>社交场合会喝酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>None</td>\n",
       "      <td>170-175cm|工作地:广东珠海香洲区|月薪:1.2万以上|大专|离异|不要吸烟|是否想...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4328</td>\n",
       "      <td>相遇并非偶然</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>33岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东湛江</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>165cm</td>\n",
       "      <td>48kg</td>\n",
       "      <td>瘦长</td>\n",
       "      <td>中专</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>有孩子且偶尔会一起住</td>\n",
       "      <td>None</td>\n",
       "      <td>173cm以上|工作地:广东珠海|不要吸烟</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          名称  城市    区域     年龄  民族     籍贯                星座      学历  婚姻状况  \\\n",
       "107   Mia啦啦啦  北京   海淀区   27岁   汉族  黑龙江大庆  天秤座(09.23-10.22)   大学本科    未婚    \n",
       "136       米谷  上海   长宁区   39岁   汉族   海南三亚  天秤座(09.23-10.22)   大学本科    未婚    \n",
       "170       格调  上海   闵行区   42岁   汉族     不明  魔羯座(12.22-01.19)     中专    离异    \n",
       "326   Sherry  广州   番禺区   23岁   汉族   广东广州  魔羯座(12.22-01.19)     大专    未婚    \n",
       "429     清沐宸汐  深圳   龙岗区   23岁   汉族     不明  射手座(11.22-12.21)     大专    未婚    \n",
       "...      ...  ..   ...    ...  ..    ...               ...     ...   ...   \n",
       "4156      依娜  中山  东区街道   38岁   汉族   湖南益阳  魔羯座(12.22-01.19)     中专    离异    \n",
       "4172     丽Li  中山  东区街道   34岁   汉族   广东湛江  射手座(11.22-12.21)     大专    离异    \n",
       "4278      喵喵  珠海   香洲区   32岁   汉族   广东珠海  天蝎座(10.23-11.21)     大专    未婚    \n",
       "4295   开心每一天  珠海   香洲区   44岁   汉族   广东珠海  魔羯座(12.22-01.19)     大专    离异    \n",
       "4328  相遇并非偶然  珠海   香洲区   33岁   汉族   广东湛江  魔羯座(12.22-01.19)     中专    离异    \n",
       "\n",
       "           身高    体重    体型    职业             收入 是否吸烟     是否喝酒    住房情况 车辆情况  \\\n",
       "107    164cm   45kg    瘦长  医疗管理   12001-20000元   不明   稍微喝一点酒  打算婚后购房   不明   \n",
       "136    166cm   52kg    丰满  外贸经理        3000元以下   不明  社交场合会喝酒     已购房  已买车   \n",
       "170    160cm     不明    不明    中专     3001-5000元   不明       不明      不明   不明   \n",
       "326    158cm   40kg    保密  外贸专员    8001-12000元  不吸烟      不喝酒  打算婚后购房  未买车   \n",
       "429    150cm     不明    不明  其他职业     5001-8000元  不吸烟       不明      不明   不明   \n",
       "...       ...   ...   ...   ...            ...  ...      ...     ...  ...   \n",
       "4156   165cm   51kg    苗条    销售     3001-5000元  不吸烟      不喝酒      租房  未买车   \n",
       "4172   160cm   55kg  富线条美   服务业     5001-8000元  不吸烟      不喝酒      租房  已买车   \n",
       "4278   159cm   45kg    苗条   设计师    8001-12000元  不吸烟  社交场合会喝酒      租房  未买车   \n",
       "4295   155cm     不明    一般    大专    8001-12000元  不吸烟  社交场合会喝酒     已购房  已买车   \n",
       "4328   165cm   48kg    瘦长    中专   12001-20000元  不吸烟      不喝酒      不明   不明   \n",
       "\n",
       "            子女情况  年龄要求                                               择偶条件  \n",
       "107         没有小孩  None                                          工作地:北京|未婚  \n",
       "136         没有小孩  None                                  工作地:上海长宁区|未婚|不要吸烟  \n",
       "170           不明  None                               工作地:安徽淮南田家庵区|月薪:5千以上  \n",
       "326         没有小孩  None                              170cm以上|未婚|体型:一般|没有小孩  \n",
       "429         没有小孩  None      170-175cm|工作地:广东深圳龙岗区|月薪:8千以下|大专|未婚|不要吸烟|没有小孩  \n",
       "...          ...   ...                                                ...  \n",
       "4156    有孩子且住在一起  None                    167-199cm|工作地:广东中山石岐街道|月薪:2万-5万  \n",
       "4172  有孩子且偶尔会一起住  None          170-179cm|工作地:广东中山东区街道|体型:壮实|是否想要孩子:不想要孩子  \n",
       "4278        没有小孩  None                                170-190cm|月薪:1.2万以上  \n",
       "4295    有孩子且住在一起  None  170-175cm|工作地:广东珠海香洲区|月薪:1.2万以上|大专|离异|不要吸烟|是否想...  \n",
       "4328  有孩子且偶尔会一起住  None                              173cm以上|工作地:广东珠海|不要吸烟  \n",
       "\n",
       "[63 rows x 21 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 提取出 年龄要求有缺失的行\n",
    "df[df.年龄要求.isna()]    # 那我们以 不明 填写"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.年龄要求.fillna('不明', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 21 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4370 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(21)\n",
      "memory usage: 717.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'18-18岁',\n",
       " '18-23岁',\n",
       " '18-25岁',\n",
       " '18-26岁',\n",
       " '18-27岁',\n",
       " '18-28岁',\n",
       " '18-29岁',\n",
       " '18-30岁',\n",
       " '18-31岁',\n",
       " '18-32岁',\n",
       " '18-33岁',\n",
       " '18-40岁',\n",
       " '19-20岁',\n",
       " '19-26岁',\n",
       " '19-30岁',\n",
       " '19-31岁',\n",
       " '19-33岁',\n",
       " '19-34岁',\n",
       " '19-36岁',\n",
       " '20-21岁',\n",
       " '20-24岁',\n",
       " '20-27岁',\n",
       " '20-28岁',\n",
       " '20-30岁',\n",
       " '20-31岁',\n",
       " '20-33岁',\n",
       " '20-34岁',\n",
       " '20-35岁',\n",
       " '20-36岁',\n",
       " '20-40岁',\n",
       " '21-25岁',\n",
       " '21-28岁',\n",
       " '21-30岁',\n",
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       " '57-62岁',\n",
       " '57-65岁',\n",
       " '57-67岁',\n",
       " '57-68岁',\n",
       " '57-71岁',\n",
       " '57岁以上',\n",
       " '57岁以下',\n",
       " '58-60岁',\n",
       " '58-62岁',\n",
       " '58-63岁',\n",
       " '58-64岁',\n",
       " '58-65岁',\n",
       " '58-66岁',\n",
       " '58-68岁',\n",
       " '58-70岁',\n",
       " '58岁以上',\n",
       " '58岁以下',\n",
       " '59-63岁',\n",
       " '59-65岁',\n",
       " '59-66岁',\n",
       " '59-68岁',\n",
       " '59-73岁',\n",
       " '59-75岁',\n",
       " '60-61岁',\n",
       " '60-62岁',\n",
       " '60-63岁',\n",
       " '60-65岁',\n",
       " '60-66岁',\n",
       " '60-68岁',\n",
       " '60-70岁',\n",
       " '60岁以上',\n",
       " '60岁以下',\n",
       " '61-70岁',\n",
       " '61-75岁',\n",
       " '62-65岁',\n",
       " '62-67岁',\n",
       " '62-68岁',\n",
       " '62岁以上',\n",
       " '62岁以下',\n",
       " '63-72岁',\n",
       " '63-76岁',\n",
       " '63-77岁',\n",
       " '63岁以上',\n",
       " '63岁以下',\n",
       " '64-65岁',\n",
       " '64-67岁',\n",
       " '64-71岁',\n",
       " '65-70岁',\n",
       " '65-73岁',\n",
       " '65-74岁',\n",
       " '65-80岁',\n",
       " '65岁以下',\n",
       " '66-70岁',\n",
       " '66-72岁',\n",
       " '66-73岁',\n",
       " '66-80岁',\n",
       " '66岁以上',\n",
       " '66岁以下',\n",
       " '67-72岁',\n",
       " '68-72岁',\n",
       " '68-76岁',\n",
       " '68岁以下',\n",
       " '69-83岁',\n",
       " '70-80岁',\n",
       " '71-83岁',\n",
       " '72岁以下',\n",
       " '73-75岁',\n",
       " '74-79岁',\n",
       " '76-98岁',\n",
       " '不明'}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(df.年龄要求.value_counts().index)  # 无异常值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 新增 身高 要求  \n",
    "位置放在 年龄要求 后面"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                               [33-40岁, 175-195cm, 不要吸烟]\n",
       "1       [45-54岁, 170-188cm, 月薪:1.2万以上, 大学本科, 不要吸烟, 是否想...\n",
       "2                        [31-45岁, 工作地:北京朝阳区, 月薪:8千以上, 未婚]\n",
       "3       [46-53岁, 170-180cm, 工作地:北京朝阳区, 月薪:8千以上, 离异, 体型...\n",
       "4                                       [39-54岁, 月薪:5千以上]\n",
       "                              ...                        \n",
       "4365    [40-47岁, 170-178cm, 工作地:广东珠海, 月薪:2万以上, 体型:一般, ...\n",
       "4366                         [31-45岁, 172-182cm, 月薪:2万以上]\n",
       "4367                 [33-43岁, 170-180cm, 工作地:广东珠海香洲区, 未婚]\n",
       "4368    [29-35岁, 170-185cm, 工作地:广东珠海, 月薪:1.2万以上, 大学本科,...\n",
       "4369                   [49-63岁, 工作地:广东珠海香洲区, 月薪:5万以上, 未婚]\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = df.择偶条件.str.split('|')\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.insert(20, '身高要求', '不明')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def x(s):\n",
    "    for i in s:\n",
    "        if 'cm' in i:\n",
    "            return i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       175-195cm\n",
       "1       170-188cm\n",
       "2            None\n",
       "3       170-180cm\n",
       "4            None\n",
       "          ...    \n",
       "4365    170-178cm\n",
       "4366    172-182cm\n",
       "4367    170-180cm\n",
       "4368    170-185cm\n",
       "4369         None\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['身高要求'] = a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 22 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4370 non-null object\n",
      "身高要求    3090 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(22)\n",
      "memory usage: 751.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>区域</th>\n",
       "      <th>年龄</th>\n",
       "      <th>民族</th>\n",
       "      <th>籍贯</th>\n",
       "      <th>星座</th>\n",
       "      <th>学历</th>\n",
       "      <th>婚姻状况</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>体型</th>\n",
       "      <th>职业</th>\n",
       "      <th>收入</th>\n",
       "      <th>是否吸烟</th>\n",
       "      <th>是否喝酒</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>车辆情况</th>\n",
       "      <th>子女情况</th>\n",
       "      <th>年龄要求</th>\n",
       "      <th>身高要求</th>\n",
       "      <th>择偶条件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>芯儿</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>36岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北保定</td>\n",
       "      <td>天蝎座(10.23-11.21)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>160cm</td>\n",
       "      <td>45kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>传媒/艺术</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>31-45岁</td>\n",
       "      <td>None</td>\n",
       "      <td>31-45岁|工作地:北京朝阳区|月薪:8千以上|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>冰心</td>\n",
       "      <td>北京</td>\n",
       "      <td>石景山区</td>\n",
       "      <td>48岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>黑龙江牡丹江</td>\n",
       "      <td>射手座(11.22-12.21)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>3001-5000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>和家人同住</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>39-54岁</td>\n",
       "      <td>None</td>\n",
       "      <td>39-54岁|月薪:5千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>五七</td>\n",
       "      <td>北京</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>25岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>江苏徐州</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>165cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>20-34岁</td>\n",
       "      <td>None</td>\n",
       "      <td>20-34岁|工作地:安徽合肥蜀山区|月薪:1.2万以上|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>六六</td>\n",
       "      <td>北京</td>\n",
       "      <td>石景山区</td>\n",
       "      <td>51岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>吉林吉林</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>58kg</td>\n",
       "      <td>不明</td>\n",
       "      <td>销售总监</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>53-63岁</td>\n",
       "      <td>None</td>\n",
       "      <td>53-63岁|工作地:北京石景山区|月薪:8千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>卓越</td>\n",
       "      <td>北京</td>\n",
       "      <td>东城区</td>\n",
       "      <td>34岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北张家口</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>硕士</td>\n",
       "      <td>离异</td>\n",
       "      <td>170cm</td>\n",
       "      <td>55kg</td>\n",
       "      <td>高大美丽</td>\n",
       "      <td>高级管理</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>30-47岁</td>\n",
       "      <td>None</td>\n",
       "      <td>30-47岁</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4357</td>\n",
       "      <td>天使的眼泪</td>\n",
       "      <td>珠海</td>\n",
       "      <td>金湾区</td>\n",
       "      <td>32岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>湖南娄底</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大专</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>49kg</td>\n",
       "      <td>不明</td>\n",
       "      <td>业务跟单</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>28-42岁</td>\n",
       "      <td>None</td>\n",
       "      <td>28-42岁|工作地:广东珠海金湾区|月薪:8千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4358</td>\n",
       "      <td>菁菁</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>35岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>不明</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>156cm</td>\n",
       "      <td>45kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>中专</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>30-44岁</td>\n",
       "      <td>None</td>\n",
       "      <td>30-44岁|工作地:广东|月薪:8千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4363</td>\n",
       "      <td>逗逗</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>30岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>湖北孝感</td>\n",
       "      <td>射手座(11.22-12.21)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>160cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>26-40岁</td>\n",
       "      <td>None</td>\n",
       "      <td>26-40岁|工作地:广东珠海香洲区|月薪:2万以上|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4364</td>\n",
       "      <td>澜纸清兰</td>\n",
       "      <td>珠海</td>\n",
       "      <td>金湾区</td>\n",
       "      <td>43岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东珠海</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>157cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>3000元以下</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>不明</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>39-53岁</td>\n",
       "      <td>None</td>\n",
       "      <td>39-53岁|工作地:广东珠海金湾区|月薪:3千以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4369</td>\n",
       "      <td>Mask</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>54岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>北京</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>165cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>保密</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>20001-50000元</td>\n",
       "      <td>不明</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>49-63岁</td>\n",
       "      <td>None</td>\n",
       "      <td>49-63岁|工作地:广东珠海香洲区|月薪:5万以上|未婚</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1280 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         名称  城市    区域     年龄  民族      籍贯                星座       学历  婚姻状况  \\\n",
       "2        芯儿  北京   朝阳区   36岁   汉族    河北保定  天蝎座(10.23-11.21)    大学本科    未婚    \n",
       "4        冰心  北京  石景山区   48岁   汉族  黑龙江牡丹江  射手座(11.22-12.21)   高中及以下    离异    \n",
       "8        五七  北京   海淀区   25岁   汉族    江苏徐州  魔羯座(12.22-01.19)    大学本科    未婚    \n",
       "9        六六  北京  石景山区   51岁   汉族    吉林吉林  魔羯座(12.22-01.19)      中专    离异    \n",
       "14       卓越  北京   东城区   34岁   汉族   河北张家口  魔羯座(12.22-01.19)      硕士    离异    \n",
       "...     ...  ..   ...    ...  ..     ...               ...      ...   ...   \n",
       "4357  天使的眼泪  珠海   金湾区   32岁   汉族    湖南娄底  魔羯座(12.22-01.19)      大专    离异    \n",
       "4358     菁菁  珠海   香洲区   35岁   汉族      不明  魔羯座(12.22-01.19)      中专    离异    \n",
       "4363     逗逗  珠海   香洲区   30岁   汉族    湖北孝感  射手座(11.22-12.21)    大学本科    未婚    \n",
       "4364   澜纸清兰  珠海   金湾区   43岁   汉族    广东珠海  魔羯座(12.22-01.19)   高中及以下    离异    \n",
       "4369   Mask  珠海   香洲区   54岁   汉族      北京  魔羯座(12.22-01.19)      大专    未婚    \n",
       "\n",
       "           身高    体重    体型     职业             收入 是否吸烟    是否喝酒   住房情况 车辆情况  \\\n",
       "2      160cm   45kg    苗条  传媒/艺术     5001-8000元  不吸烟  稍微喝一点酒     租房  未买车   \n",
       "4      160cm     不明    不明  高中及以下     3001-5000元  不吸烟     不喝酒  和家人同住  未买车   \n",
       "8      165cm     不明    不明   大学本科    8001-12000元  不吸烟     不喝酒     不明   不明   \n",
       "9      160cm   58kg    不明   销售总监     5001-8000元  不吸烟     不喝酒     租房  未买车   \n",
       "14     170cm   55kg  高大美丽   高级管理   12001-20000元  不吸烟     不喝酒    已购房  已买车   \n",
       "...       ...   ...   ...    ...            ...  ...     ...    ...  ...   \n",
       "4357   160cm   49kg    不明   业务跟单     5001-8000元  不吸烟     不喝酒     租房  未买车   \n",
       "4358   156cm   45kg    苗条     中专     5001-8000元  不吸烟  稍微喝一点酒     不明   不明   \n",
       "4363   160cm     不明    不明   大学本科   12001-20000元  不吸烟     不喝酒     租房  未买车   \n",
       "4364   157cm     不明    不明  高中及以下        3000元以下  不吸烟     不喝酒     租房   不明   \n",
       "4369   165cm   52kg    保密   其他职业   20001-50000元   不明  稍微喝一点酒    已购房  已买车   \n",
       "\n",
       "          子女情况    年龄要求  身高要求                             择偶条件  \n",
       "2         没有小孩  31-45岁  None      31-45岁|工作地:北京朝阳区|月薪:8千以上|未婚  \n",
       "4     有孩子但不在身边  39-54岁  None                   39-54岁|月薪:5千以上  \n",
       "8           不明  20-34岁  None  20-34岁|工作地:安徽合肥蜀山区|月薪:1.2万以上|未婚  \n",
       "9     有孩子但不在身边  53-63岁  None        53-63岁|工作地:北京石景山区|月薪:8千以上  \n",
       "14    有孩子且住在一起  30-47岁  None                           30-47岁  \n",
       "...        ...     ...   ...                              ...  \n",
       "4357      没有小孩  28-42岁  None       28-42岁|工作地:广东珠海金湾区|月薪:8千以上  \n",
       "4358        不明  30-44岁  None            30-44岁|工作地:广东|月薪:8千以上  \n",
       "4363      没有小孩  26-40岁  None    26-40岁|工作地:广东珠海香洲区|月薪:2万以上|未婚  \n",
       "4364      没有小孩  39-53岁  None       39-53岁|工作地:广东珠海金湾区|月薪:3千以上  \n",
       "4369      没有小孩  49-63岁  None    49-63岁|工作地:广东珠海香洲区|月薪:5万以上|未婚  \n",
       "\n",
       "[1280 rows x 22 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 提取出身高要求有缺失的行\n",
    "df[df.身高要求.isna()]  # 填充不明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.身高要求.fillna('不明', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 22 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4370 non-null object\n",
      "身高要求    4370 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(22)\n",
      "memory usage: 751.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'129-180cm',\n",
       " '130-210cm',\n",
       " '133-172cm',\n",
       " '140cm以上',\n",
       " '145-160cm',\n",
       " '146cm以上',\n",
       " '150-158cm',\n",
       " '150-160cm',\n",
       " '150-161cm',\n",
       " '150-165cm',\n",
       " '150cm以上',\n",
       " '151-164cm',\n",
       " '151-167cm',\n",
       " '152-165cm',\n",
       " '153-164cm',\n",
       " '155-163cm',\n",
       " '155-165cm',\n",
       " '155-166cm',\n",
       " '155-168cm',\n",
       " '155-170cm',\n",
       " '155-175cm',\n",
       " '155-186cm',\n",
       " '155-189cm',\n",
       " '155-200cm',\n",
       " '155cm以上',\n",
       " '156-165cm',\n",
       " '156-170cm',\n",
       " '156-181cm',\n",
       " '156cm以上',\n",
       " '157-172cm',\n",
       " '157-178cm',\n",
       " '158-165cm',\n",
       " '158-168cm',\n",
       " '158-170cm',\n",
       " '158-173cm',\n",
       " '158-175cm',\n",
       " '158cm以上',\n",
       " '160-160cm',\n",
       " '160-164cm',\n",
       " '160-165cm',\n",
       " '160-168cm',\n",
       " '160-169cm',\n",
       " '160-170cm',\n",
       " '160-173cm',\n",
       " '160-174cm',\n",
       " '160-175cm',\n",
       " '160-178cm',\n",
       " '160-180cm',\n",
       " '160-183cm',\n",
       " '160-185cm',\n",
       " '160-187cm',\n",
       " '160-190cm',\n",
       " '160cm以上',\n",
       " '160cm以下',\n",
       " '161-180cm',\n",
       " '161-190cm',\n",
       " '161cm以上',\n",
       " '162-168cm',\n",
       " '162-175cm',\n",
       " '162-180cm',\n",
       " '162-181cm',\n",
       " '164-172cm',\n",
       " '164cm以上',\n",
       " '165-170cm',\n",
       " '165-172cm',\n",
       " '165-175cm',\n",
       " '165-176cm',\n",
       " '165-177cm',\n",
       " '165-178cm',\n",
       " '165-179cm',\n",
       " '165-180cm',\n",
       " '165-181cm',\n",
       " '165-185cm',\n",
       " '165-190cm',\n",
       " '165cm以上',\n",
       " '165cm以下',\n",
       " '166-170cm',\n",
       " '166-172cm',\n",
       " '166-173cm',\n",
       " '166-175cm',\n",
       " '166-176cm',\n",
       " '166-177cm',\n",
       " '166-178cm',\n",
       " '166-179cm',\n",
       " '166-180cm',\n",
       " '166-185cm',\n",
       " '166-190cm',\n",
       " '166cm以上',\n",
       " '166cm以下',\n",
       " '167-172cm',\n",
       " '167-175cm',\n",
       " '167-176cm',\n",
       " '167-180cm',\n",
       " '167-181cm',\n",
       " '167-199cm',\n",
       " '167cm以上',\n",
       " '168-168cm',\n",
       " '168-169cm',\n",
       " '168-170cm',\n",
       " '168-171cm',\n",
       " '168-172cm',\n",
       " '168-173cm',\n",
       " '168-174cm',\n",
       " '168-175cm',\n",
       " '168-176cm',\n",
       " '168-178cm',\n",
       " '168-180cm',\n",
       " '168-182cm',\n",
       " '168-183cm',\n",
       " '168-184cm',\n",
       " '168-185cm',\n",
       " '168-186cm',\n",
       " '168-188cm',\n",
       " '168-189cm',\n",
       " '168-190cm',\n",
       " '168-211cm',\n",
       " '168cm以上',\n",
       " '168cm以下',\n",
       " '169-169cm',\n",
       " '169-170cm',\n",
       " '169-173cm',\n",
       " '169-175cm',\n",
       " '169-177cm',\n",
       " '169-178cm',\n",
       " '169-180cm',\n",
       " '169-182cm',\n",
       " '169-186cm',\n",
       " '169cm以上',\n",
       " '170-170cm',\n",
       " '170-171cm',\n",
       " '170-173cm',\n",
       " '170-174cm',\n",
       " '170-175cm',\n",
       " '170-176cm',\n",
       " '170-177cm',\n",
       " '170-178cm',\n",
       " '170-179cm',\n",
       " '170-180cm',\n",
       " '170-181cm',\n",
       " '170-182cm',\n",
       " '170-183cm',\n",
       " '170-184cm',\n",
       " '170-185cm',\n",
       " '170-186cm',\n",
       " '170-187cm',\n",
       " '170-188cm',\n",
       " '170-189cm',\n",
       " '170-190cm',\n",
       " '170-194cm',\n",
       " '170-195cm',\n",
       " '170-200cm',\n",
       " '170-206cm',\n",
       " '170-211cm',\n",
       " '170cm以上',\n",
       " '170cm以下',\n",
       " '171-173cm',\n",
       " '171-175cm',\n",
       " '171-177cm',\n",
       " '171-178cm',\n",
       " '171-179cm',\n",
       " '171-180cm',\n",
       " '171-181cm',\n",
       " '171-182cm',\n",
       " '171-185cm',\n",
       " '171-188cm',\n",
       " '171-211cm',\n",
       " '171cm以上',\n",
       " '172-172cm',\n",
       " '172-173cm',\n",
       " '172-175cm',\n",
       " '172-176cm',\n",
       " '172-177cm',\n",
       " '172-178cm',\n",
       " '172-179cm',\n",
       " '172-180cm',\n",
       " '172-181cm',\n",
       " '172-182cm',\n",
       " '172-183cm',\n",
       " '172-185cm',\n",
       " '172-186cm',\n",
       " '172-187cm',\n",
       " '172-188cm',\n",
       " '172-189cm',\n",
       " '172-190cm',\n",
       " '172-196cm',\n",
       " '172-210cm',\n",
       " '172cm以上',\n",
       " '172cm以下',\n",
       " '173-173cm',\n",
       " '173-175cm',\n",
       " '173-176cm',\n",
       " '173-177cm',\n",
       " '173-178cm',\n",
       " '173-179cm',\n",
       " '173-180cm',\n",
       " '173-181cm',\n",
       " '173-182cm',\n",
       " '173-183cm',\n",
       " '173-184cm',\n",
       " '173-185cm',\n",
       " '173-186cm',\n",
       " '173-187cm',\n",
       " '173-188cm',\n",
       " '173-189cm',\n",
       " '173-190cm',\n",
       " '173-193cm',\n",
       " '173-195cm',\n",
       " '173-203cm',\n",
       " '173cm以上',\n",
       " '173cm以下',\n",
       " '174-177cm',\n",
       " '174-178cm',\n",
       " '174-179cm',\n",
       " '174-180cm',\n",
       " '174-181cm',\n",
       " '174-182cm',\n",
       " '174-183cm',\n",
       " '174-184cm',\n",
       " '174-185cm',\n",
       " '174-188cm',\n",
       " '174-189cm',\n",
       " '174-211cm',\n",
       " '174cm以上',\n",
       " '175-175cm',\n",
       " '175-176cm',\n",
       " '175-177cm',\n",
       " '175-178cm',\n",
       " '175-179cm',\n",
       " '175-180cm',\n",
       " '175-181cm',\n",
       " '175-182cm',\n",
       " '175-183cm',\n",
       " '175-184cm',\n",
       " '175-185cm',\n",
       " '175-186cm',\n",
       " '175-187cm',\n",
       " '175-188cm',\n",
       " '175-189cm',\n",
       " '175-190cm',\n",
       " '175-192cm',\n",
       " '175-193cm',\n",
       " '175-195cm',\n",
       " '175-196cm',\n",
       " '175-198cm',\n",
       " '175-199cm',\n",
       " '175-211cm',\n",
       " '175cm以上',\n",
       " '175cm以下',\n",
       " '176-176cm',\n",
       " '176-178cm',\n",
       " '176-180cm',\n",
       " '176-181cm',\n",
       " '176-182cm',\n",
       " '176-183cm',\n",
       " '176-185cm',\n",
       " '176-186cm',\n",
       " '176-188cm',\n",
       " '176-189cm',\n",
       " '176-190cm',\n",
       " '176-196cm',\n",
       " '176cm以上',\n",
       " '176cm以下',\n",
       " '177-177cm',\n",
       " '177-182cm',\n",
       " '177-183cm',\n",
       " '177-184cm',\n",
       " '177-185cm',\n",
       " '177-187cm',\n",
       " '177-188cm',\n",
       " '177-189cm',\n",
       " '177-190cm',\n",
       " '177cm以上',\n",
       " '177cm以下',\n",
       " '178-178cm',\n",
       " '178-180cm',\n",
       " '178-181cm',\n",
       " '178-182cm',\n",
       " '178-183cm',\n",
       " '178-185cm',\n",
       " '178-186cm',\n",
       " '178-187cm',\n",
       " '178-188cm',\n",
       " '178-189cm',\n",
       " '178-190cm',\n",
       " '178-195cm',\n",
       " '178-210cm',\n",
       " '178cm以上',\n",
       " '178cm以下',\n",
       " '179-183cm',\n",
       " '179-185cm',\n",
       " '179-189cm',\n",
       " '179-190cm',\n",
       " '179-192cm',\n",
       " '179cm以上',\n",
       " '179cm以下',\n",
       " '180-180cm',\n",
       " '180-182cm',\n",
       " '180-183cm',\n",
       " '180-185cm',\n",
       " '180-186cm',\n",
       " '180-189cm',\n",
       " '180-190cm',\n",
       " '180-191cm',\n",
       " '180-192cm',\n",
       " '180-195cm',\n",
       " '180cm以上',\n",
       " '180cm以下',\n",
       " '181-187cm',\n",
       " '181-188cm',\n",
       " '181cm以上',\n",
       " '181cm以下',\n",
       " '182-195cm',\n",
       " '182cm以上',\n",
       " '183cm以上',\n",
       " '185-187cm',\n",
       " '185cm以上',\n",
       " '185cm以下',\n",
       " '188cm以下',\n",
       " '202-208cm',\n",
       " '不明'}"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(df.身高要求.value_counts().index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 新增 收入要求  \n",
    "位置放在 身高要求 后面"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                               [33-40岁, 175-195cm, 不要吸烟]\n",
       "1       [45-54岁, 170-188cm, 月薪:1.2万以上, 大学本科, 不要吸烟, 是否想...\n",
       "2                        [31-45岁, 工作地:北京朝阳区, 月薪:8千以上, 未婚]\n",
       "3       [46-53岁, 170-180cm, 工作地:北京朝阳区, 月薪:8千以上, 离异, 体型...\n",
       "4                                       [39-54岁, 月薪:5千以上]\n",
       "                              ...                        \n",
       "4365    [40-47岁, 170-178cm, 工作地:广东珠海, 月薪:2万以上, 体型:一般, ...\n",
       "4366                         [31-45岁, 172-182cm, 月薪:2万以上]\n",
       "4367                 [33-43岁, 170-180cm, 工作地:广东珠海香洲区, 未婚]\n",
       "4368    [29-35岁, 170-185cm, 工作地:广东珠海, 月薪:1.2万以上, 大学本科,...\n",
       "4369                   [49-63岁, 工作地:广东珠海香洲区, 月薪:5万以上, 未婚]\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = df.择偶条件.str.split('|')\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.insert(21, '收入要求', '不明')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "def x(s):\n",
    "    for i in s:\n",
    "        if '月薪' in i:\n",
    "            return i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            None\n",
       "1       月薪:1.2万以上\n",
       "2         月薪:8千以上\n",
       "3         月薪:8千以上\n",
       "4         月薪:5千以上\n",
       "          ...    \n",
       "4365      月薪:2万以上\n",
       "4366      月薪:2万以上\n",
       "4367         None\n",
       "4368    月薪:1.2万以上\n",
       "4369      月薪:5万以上\n",
       "Name: 择偶条件, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['收入要求'] = a.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 23 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4370 non-null object\n",
      "身高要求    4370 non-null object\n",
      "收入要求    3889 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(23)\n",
      "memory usage: 785.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.收入要求.fillna('不明', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4370 entries, 0 to 4369\n",
      "Data columns (total 23 columns):\n",
      "名称      4370 non-null object\n",
      "城市      4370 non-null object\n",
      "区域      4370 non-null object\n",
      "年龄      4370 non-null object\n",
      "民族      4370 non-null object\n",
      "籍贯      4370 non-null object\n",
      "星座      4370 non-null object\n",
      "学历      4370 non-null object\n",
      "婚姻状况    4370 non-null object\n",
      "身高      4370 non-null object\n",
      "体重      4370 non-null object\n",
      "体型      4370 non-null object\n",
      "职业      4370 non-null object\n",
      "收入      4370 non-null object\n",
      "是否吸烟    4370 non-null object\n",
      "是否喝酒    4370 non-null object\n",
      "住房情况    4370 non-null object\n",
      "车辆情况    4370 non-null object\n",
      "子女情况    4370 non-null object\n",
      "年龄要求    4370 non-null object\n",
      "身高要求    4370 non-null object\n",
      "收入要求    4370 non-null object\n",
      "择偶条件    4370 non-null object\n",
      "dtypes: object(23)\n",
      "memory usage: 785.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "月薪:8千以上       875\n",
       "月薪:5千以上       767\n",
       "月薪:1.2万以上     670\n",
       "月薪:2万以上       502\n",
       "不明            481\n",
       "月薪:3千以上       237\n",
       "月薪:5万以上       146\n",
       "月薪:2万-5万      114\n",
       "月薪:1.2万-2万    112\n",
       "月薪:8千-1.2万     78\n",
       "月薪:8千-2万       77\n",
       "月薪:1.2万-5万     59\n",
       "月薪:5千-8千       57\n",
       "月薪:5千-1.2万     47\n",
       "月薪:8千-5万       36\n",
       "月薪:5千-2万       26\n",
       "月薪:3千-5千       23\n",
       "月薪:5千-5万       19\n",
       "月薪:2万以下         7\n",
       "月薪:3千-8千        6\n",
       "月薪:3千-1.2万      5\n",
       "月薪:3千以下         5\n",
       "月薪:8千以下         4\n",
       "月薪:1.2万以下       4\n",
       "月薪:5千以下         4\n",
       "月薪:3千-5万        3\n",
       "月薪:3千-3千        2\n",
       "月薪:5万以下         2\n",
       "月薪:3千-2万        1\n",
       "月薪:2万-2万        1\n",
       "Name: 收入要求, dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.收入要求.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "def x(s):\n",
    "    if '月薪' in s:\n",
    "        return s.replace('月薪:', '')\n",
    "    else:\n",
    "        return s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           不明\n",
       "1       1.2万以上\n",
       "2         8千以上\n",
       "3         8千以上\n",
       "4         5千以上\n",
       "         ...  \n",
       "4365      2万以上\n",
       "4366      2万以上\n",
       "4367        不明\n",
       "4368    1.2万以上\n",
       "4369      5万以上\n",
       "Name: 收入要求, Length: 4370, dtype: object"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.收入要求.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['收入要求'] = df.收入要求.map(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>区域</th>\n",
       "      <th>年龄</th>\n",
       "      <th>民族</th>\n",
       "      <th>籍贯</th>\n",
       "      <th>星座</th>\n",
       "      <th>学历</th>\n",
       "      <th>婚姻状况</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>体型</th>\n",
       "      <th>职业</th>\n",
       "      <th>收入</th>\n",
       "      <th>是否吸烟</th>\n",
       "      <th>是否喝酒</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>车辆情况</th>\n",
       "      <th>子女情况</th>\n",
       "      <th>年龄要求</th>\n",
       "      <th>身高要求</th>\n",
       "      <th>收入要求</th>\n",
       "      <th>择偶条件</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>玉水福兰</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>33岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>吉林通化</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>中专</td>\n",
       "      <td>离异</td>\n",
       "      <td>165cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>3000元以下</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>33-40岁</td>\n",
       "      <td>175-195cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>33-40岁|175-195cm|不要吸烟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>找爱的玫瑰</td>\n",
       "      <td>北京</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>47岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北张家口</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>158cm</td>\n",
       "      <td>55kg</td>\n",
       "      <td>富线条美</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>8001-12000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>和家人同住</td>\n",
       "      <td>已买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>45-54岁</td>\n",
       "      <td>170-188cm</td>\n",
       "      <td>1.2万以上</td>\n",
       "      <td>45-54岁|170-188cm|月薪:1.2万以上|大学本科|不要吸烟|是否想要孩子:以后...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>芯儿</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>36岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北保定</td>\n",
       "      <td>天蝎座(10.23-11.21)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>未婚</td>\n",
       "      <td>160cm</td>\n",
       "      <td>45kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>传媒/艺术</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>31-45岁</td>\n",
       "      <td>不明</td>\n",
       "      <td>8千以上</td>\n",
       "      <td>31-45岁|工作地:北京朝阳区|月薪:8千以上|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>沁心夜雨</td>\n",
       "      <td>北京</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>49岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>河北保定</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>168cm</td>\n",
       "      <td>58kg</td>\n",
       "      <td>苗条</td>\n",
       "      <td>自由职业</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子且住在一起</td>\n",
       "      <td>46-53岁</td>\n",
       "      <td>170-180cm</td>\n",
       "      <td>8千以上</td>\n",
       "      <td>46-53岁|170-180cm|工作地:北京朝阳区|月薪:8千以上|离异|体型:运动员型|...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>冰心</td>\n",
       "      <td>北京</td>\n",
       "      <td>石景山区</td>\n",
       "      <td>48岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>黑龙江牡丹江</td>\n",
       "      <td>射手座(11.22-12.21)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>160cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>3001-5000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不喝酒</td>\n",
       "      <td>和家人同住</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>39-54岁</td>\n",
       "      <td>不明</td>\n",
       "      <td>5千以上</td>\n",
       "      <td>39-54岁|月薪:5千以上</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4365</td>\n",
       "      <td>Miya</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>35岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>重庆</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>156cm</td>\n",
       "      <td>47kg</td>\n",
       "      <td>一般</td>\n",
       "      <td>服务业</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>稍微抽一点烟</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>租房</td>\n",
       "      <td>未买车</td>\n",
       "      <td>有孩子但不在身边</td>\n",
       "      <td>40-47岁</td>\n",
       "      <td>170-178cm</td>\n",
       "      <td>2万以上</td>\n",
       "      <td>40-47岁|170-178cm|工作地:广东珠海|月薪:2万以上|体型:一般|不要喝酒|有...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4366</td>\n",
       "      <td>薰薰</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>36岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>不明</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>高中及以下</td>\n",
       "      <td>离异</td>\n",
       "      <td>166cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>12001-20000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>不明</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>31-45岁</td>\n",
       "      <td>172-182cm</td>\n",
       "      <td>2万以上</td>\n",
       "      <td>31-45岁|172-182cm|月薪:2万以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4367</td>\n",
       "      <td>淡然</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>35岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东珠海</td>\n",
       "      <td>天秤座(09.23-10.22)</td>\n",
       "      <td>中专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>160cm</td>\n",
       "      <td>48kg</td>\n",
       "      <td>瘦长</td>\n",
       "      <td>房地产交易</td>\n",
       "      <td>20001-50000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>社交场合会喝酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>不明</td>\n",
       "      <td>33-43岁</td>\n",
       "      <td>170-180cm</td>\n",
       "      <td>不明</td>\n",
       "      <td>33-43岁|170-180cm|工作地:广东珠海香洲区|未婚</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4368</td>\n",
       "      <td>云宝贝</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>28岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>广东梅州</td>\n",
       "      <td>天秤座(09.23-10.22)</td>\n",
       "      <td>大学本科</td>\n",
       "      <td>离异</td>\n",
       "      <td>163cm</td>\n",
       "      <td>53kg</td>\n",
       "      <td>一般</td>\n",
       "      <td>心理医生</td>\n",
       "      <td>5001-8000元</td>\n",
       "      <td>不吸烟</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>住在单位宿舍</td>\n",
       "      <td>未买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>29-35岁</td>\n",
       "      <td>170-185cm</td>\n",
       "      <td>1.2万以上</td>\n",
       "      <td>29-35岁|170-185cm|工作地:广东珠海|月薪:1.2万以上|大学本科|不要喝酒|...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4369</td>\n",
       "      <td>Mask</td>\n",
       "      <td>珠海</td>\n",
       "      <td>香洲区</td>\n",
       "      <td>54岁</td>\n",
       "      <td>汉族</td>\n",
       "      <td>北京</td>\n",
       "      <td>魔羯座(12.22-01.19)</td>\n",
       "      <td>大专</td>\n",
       "      <td>未婚</td>\n",
       "      <td>165cm</td>\n",
       "      <td>52kg</td>\n",
       "      <td>保密</td>\n",
       "      <td>其他职业</td>\n",
       "      <td>20001-50000元</td>\n",
       "      <td>不明</td>\n",
       "      <td>稍微喝一点酒</td>\n",
       "      <td>已购房</td>\n",
       "      <td>已买车</td>\n",
       "      <td>没有小孩</td>\n",
       "      <td>49-63岁</td>\n",
       "      <td>不明</td>\n",
       "      <td>5万以上</td>\n",
       "      <td>49-63岁|工作地:广东珠海香洲区|月薪:5万以上|未婚</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4370 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         名称  城市    区域     年龄  民族      籍贯                星座       学历  婚姻状况  \\\n",
       "0      玉水福兰  北京   朝阳区   33岁   汉族    吉林通化  魔羯座(12.22-01.19)      中专    离异    \n",
       "1     找爱的玫瑰  北京   海淀区   47岁   汉族   河北张家口  魔羯座(12.22-01.19)   高中及以下    离异    \n",
       "2        芯儿  北京   朝阳区   36岁   汉族    河北保定  天蝎座(10.23-11.21)    大学本科    未婚    \n",
       "3      沁心夜雨  北京   朝阳区   49岁   汉族    河北保定  魔羯座(12.22-01.19)   高中及以下    离异    \n",
       "4        冰心  北京  石景山区   48岁   汉族  黑龙江牡丹江  射手座(11.22-12.21)   高中及以下    离异    \n",
       "...     ...  ..   ...    ...  ..     ...               ...      ...   ...   \n",
       "4365   Miya  珠海   香洲区   35岁   汉族      重庆  魔羯座(12.22-01.19)   高中及以下    离异    \n",
       "4366     薰薰  珠海   香洲区   36岁   汉族      不明  魔羯座(12.22-01.19)   高中及以下    离异    \n",
       "4367     淡然  珠海   香洲区   35岁   汉族    广东珠海  天秤座(09.23-10.22)      中专    未婚    \n",
       "4368    云宝贝  珠海   香洲区   28岁   汉族    广东梅州  天秤座(09.23-10.22)    大学本科    离异    \n",
       "4369   Mask  珠海   香洲区   54岁   汉族      北京  魔羯座(12.22-01.19)      大专    未婚    \n",
       "\n",
       "           身高    体重    体型     职业             收入    是否吸烟     是否喝酒    住房情况 车辆情况  \\\n",
       "0      165cm   52kg  富线条美   其他职业        3000元以下     不吸烟      不喝酒      租房  未买车   \n",
       "1      158cm   55kg  富线条美   其他职业    8001-12000元     不吸烟      不喝酒   和家人同住  已买车   \n",
       "2      160cm   45kg    苗条  传媒/艺术     5001-8000元     不吸烟   稍微喝一点酒      租房  未买车   \n",
       "3      168cm   58kg    苗条   自由职业     5001-8000元     不吸烟      不喝酒     已购房  未买车   \n",
       "4      160cm     不明    不明  高中及以下     3001-5000元     不吸烟      不喝酒   和家人同住  未买车   \n",
       "...       ...   ...   ...    ...            ...     ...      ...     ...  ...   \n",
       "4365   156cm   47kg    一般    服务业   12001-20000元  稍微抽一点烟   稍微喝一点酒      租房  未买车   \n",
       "4366   166cm     不明    不明   其他职业   12001-20000元     不吸烟       不明      不明   不明   \n",
       "4367   160cm   48kg    瘦长  房地产交易   20001-50000元     不吸烟  社交场合会喝酒     已购房  已买车   \n",
       "4368   163cm   53kg    一般   心理医生     5001-8000元     不吸烟   稍微喝一点酒  住在单位宿舍  未买车   \n",
       "4369   165cm   52kg    保密   其他职业   20001-50000元      不明   稍微喝一点酒     已购房  已买车   \n",
       "\n",
       "          子女情况    年龄要求       身高要求    收入要求  \\\n",
       "0     有孩子且住在一起  33-40岁  175-195cm      不明   \n",
       "1     有孩子但不在身边  45-54岁  170-188cm  1.2万以上   \n",
       "2         没有小孩  31-45岁         不明    8千以上   \n",
       "3     有孩子且住在一起  46-53岁  170-180cm    8千以上   \n",
       "4     有孩子但不在身边  39-54岁         不明    5千以上   \n",
       "...        ...     ...        ...     ...   \n",
       "4365  有孩子但不在身边  40-47岁  170-178cm    2万以上   \n",
       "4366      没有小孩  31-45岁  172-182cm    2万以上   \n",
       "4367        不明  33-43岁  170-180cm      不明   \n",
       "4368      没有小孩  29-35岁  170-185cm  1.2万以上   \n",
       "4369      没有小孩  49-63岁         不明    5万以上   \n",
       "\n",
       "                                                   择偶条件  \n",
       "0                                 33-40岁|175-195cm|不要吸烟  \n",
       "1     45-54岁|170-188cm|月薪:1.2万以上|大学本科|不要吸烟|是否想要孩子:以后...  \n",
       "2                           31-45岁|工作地:北京朝阳区|月薪:8千以上|未婚  \n",
       "3     46-53岁|170-180cm|工作地:北京朝阳区|月薪:8千以上|离异|体型:运动员型|...  \n",
       "4                                        39-54岁|月薪:5千以上  \n",
       "...                                                 ...  \n",
       "4365  40-47岁|170-178cm|工作地:广东珠海|月薪:2万以上|体型:一般|不要喝酒|有...  \n",
       "4366                           31-45岁|172-182cm|月薪:2万以上  \n",
       "4367                    33-43岁|170-180cm|工作地:广东珠海香洲区|未婚  \n",
       "4368  29-35岁|170-185cm|工作地:广东珠海|月薪:1.2万以上|大学本科|不要喝酒|...  \n",
       "4369                      49-63岁|工作地:广东珠海香洲区|月薪:5万以上|未婚  \n",
       "\n",
       "[4370 rows x 23 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导出数据为 珍爱网3.csv 不要行索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('珍爱网3.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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