拉勾网数据清洗.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "%matplotlib inline\n",
    "plt.rcParams['font.sans-serif']='simhei'\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine('mysql+pymysql://pandas:12345678@localhost:3306/pandas_mysql?charset=utf8',\n",
    "                      echo=True,encoding='utf-8',convert_unicode=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-03-05 15:52:26,881 INFO sqlalchemy.engine.base.Engine SHOW VARIABLES LIKE 'sql_mode'\n",
      "2021-03-05 15:52:26,884 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:26,997 INFO sqlalchemy.engine.base.Engine SHOW VARIABLES LIKE 'lower_case_table_names'\n",
      "2021-03-05 15:52:26,998 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,004 INFO sqlalchemy.engine.base.Engine SELECT DATABASE()\n",
      "2021-03-05 15:52:27,006 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,008 INFO sqlalchemy.engine.base.Engine show collation where `Charset` = 'utf8mb4' and `Collation` = 'utf8mb4_bin'\n",
      "2021-03-05 15:52:27,009 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,025 INFO sqlalchemy.engine.base.Engine SELECT CAST('test plain returns' AS CHAR(60)) AS anon_1\n",
      "2021-03-05 15:52:27,027 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,029 INFO sqlalchemy.engine.base.Engine SELECT CAST('test unicode returns' AS CHAR(60)) AS anon_1\n",
      "2021-03-05 15:52:27,031 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,034 INFO sqlalchemy.engine.base.Engine SELECT CAST('test collated returns' AS CHAR CHARACTER SET utf8mb4) COLLATE utf8mb4_bin AS anon_1\n",
      "2021-03-05 15:52:27,036 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,042 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 15:52:27,044 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,066 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 15:52:27,068 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,094 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `shanghai_拉钩数据`\n",
      "2021-03-05 15:52:27,096 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 15:52:27,121 INFO sqlalchemy.engine.base.Engine SELECT `shanghai_拉钩数据`.`index`, `shanghai_拉钩数据`.`职位名称`, `shanghai_拉钩数据`.`公司地址`, `shanghai_拉钩数据`.`发布时间`, `shanghai_拉钩数据`.`薪资待遇`, `shanghai_拉钩数据`.`岗位要求`, `shanghai_拉钩数据`.`岗位标签`, `shanghai_拉钩数据`.`公司福利`, `shanghai_拉钩数据`.`所属行业`, `shanghai_拉钩数据`.`公司名称` \n",
      "FROM `shanghai_拉钩数据`\n",
      "2021-03-05 15:52:27,124 INFO sqlalchemy.engine.base.Engine {}\n"
     ]
    },
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
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       "      <td>0</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>北蔡</td>\n",
       "      <td>19:56发布</td>\n",
       "      <td>10k-20k</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>金融 数据分析</td>\n",
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       "      <td>数据分析师</td>\n",
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       "      <td>17:02发布</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>徐家汇</td>\n",
       "      <td>17:41发布</td>\n",
       "      <td>12k-20k</td>\n",
       "      <td>12k-20k 经验不限 / 本科</td>\n",
       "      <td>大数据 新零售</td>\n",
       "      <td>“福利待遇优厚，发展空间大，团队氛围好”</td>\n",
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       "      <td>数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>17:01发布</td>\n",
       "      <td>10k-18k</td>\n",
       "      <td>10k-18k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
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       "      <td>移动互联网 / A轮 / 50-150人</td>\n",
       "      <td>上海众调科技</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>六里</td>\n",
       "      <td>18:02发布</td>\n",
       "      <td>10k-16k</td>\n",
       "      <td>10k-16k 经验1-3年 / 本科</td>\n",
       "      <td>电商 数据分析</td>\n",
       "      <td>“发展前景好 团队氛围佳 注重个人成长”</td>\n",
       "      <td>软件开发 / 未融资 / 150-500人</td>\n",
       "      <td>杉欣集团</td>\n",
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       "      <th>...</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>445</td>\n",
       "      <td>【21届校招】质量数据分析专员/上海(J13720)</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>15k-20k</td>\n",
       "      <td>15k-20k 经验在校/应届 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“0-12个月年终奖，一线互联网公司”</td>\n",
       "      <td>移动互联网,硬件 / D轮及以上 / 2000人以上</td>\n",
       "      <td>哈啰出行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>446</td>\n",
       "      <td>EI8467-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>13k-26k</td>\n",
       "      <td>13k-26k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析 业务理解</td>\n",
       "      <td>“发展前景,晋升机会,能力发挥”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>447</td>\n",
       "      <td>游戏数据分析师</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验1-3年 / 本科</td>\n",
       "      <td>数据分析 SQL/Hive 数据挖掘 算法</td>\n",
       "      <td>“福利待遇好，晋升空间大”</td>\n",
       "      <td>游戏 / 不需要融资 / 500-2000人</td>\n",
       "      <td>沐瞳游戏</td>\n",
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       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>448</td>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>漕河泾</td>\n",
       "      <td>2020-07-25</td>\n",
       "      <td>20k-40k</td>\n",
       "      <td>20k-40k 经验3-5年 / 本科</td>\n",
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       "      <td>企业服务,数据服务 / B轮 / 150-500人</td>\n",
       "      <td>GrowingIO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>449</td>\n",
       "      <td>JA5738-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>互联网</td>\n",
       "      <td>“上市公司,五险一金”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>450 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index                        职位名称 公司地址        发布时间     薪资待遇  \\\n",
       "0        0                       数据分析师   北蔡     19:56发布  10k-20k   \n",
       "1        1                       数据分析师   华漕     17:02发布  12k-18k   \n",
       "2        2                       数据分析师  徐家汇     17:41发布  12k-20k   \n",
       "3        3                       数据分析师  杨浦区     17:01发布  10k-18k   \n",
       "4        4                       数据分析师   六里     18:02发布  10k-16k   \n",
       "..     ...                         ...  ...         ...      ...   \n",
       "445    445  【21届校招】质量数据分析专员/上海(J13720)  闵行区  2020-12-21  15k-20k   \n",
       "446    446              EI8467-资深数据分析师  杨浦区  2020-12-09  13k-26k   \n",
       "447    447                     游戏数据分析师  闵行区  2020-12-18  15k-25k   \n",
       "448    448                      数据分析专家  漕河泾  2020-07-25  20k-40k   \n",
       "449    449              JA5738-资深数据分析师  杨浦区  2020-12-18  15k-30k   \n",
       "\n",
       "                     岗位要求                     岗位标签                      公司福利  \\\n",
       "0     10k-20k 经验1-3年 / 本科                  金融 数据分析               “氛围好,商业医疗险”   \n",
       "1     12k-18k 经验3-5年 / 本科  教育 企业服务 数据库 BI SQL 数据分析  “上市公司、创新氛围强、团队凝聚力、发展空间大”   \n",
       "2       12k-20k 经验不限 / 本科                  大数据 新零售      “福利待遇优厚，发展空间大，团队氛围好”   \n",
       "3     10k-18k 经验3-5年 / 本科                     数据分析     “交通便利 待遇良好 晋升机会 技术大牛”   \n",
       "4     10k-16k 经验1-3年 / 本科                  电商 数据分析      “发展前景好 团队氛围佳 注重个人成长”   \n",
       "..                    ...                      ...                       ...   \n",
       "445  15k-20k 经验在校/应届 / 本科                     数据分析       “0-12个月年终奖，一线互联网公司”   \n",
       "446   13k-26k 经验3-5年 / 本科                数据分析 业务理解          “发展前景,晋升机会,能力发挥”   \n",
       "447   15k-25k 经验1-3年 / 本科    数据分析 SQL/Hive 数据挖掘 算法             “福利待遇好，晋升空间大”   \n",
       "448   20k-40k 经验3-5年 / 本科        企业服务 机器学习 创业 数据挖掘             “数据科学，产品创新孵化”   \n",
       "449   15k-30k 经验1-3年 / 本科                      互联网               “上市公司,五险一金”   \n",
       "\n",
       "                             所属行业       公司名称  \n",
       "0              金融 / C轮 / 150-500人      萨摩耶数科  \n",
       "1          教育 / 不需要融资 / 500-2000人       行动教育  \n",
       "2       企业服务,数据服务 / 未融资 / 50-150人       久谦咨询  \n",
       "3            移动互联网 / A轮 / 50-150人     上海众调科技  \n",
       "4           软件开发 / 未融资 / 150-500人       杉欣集团  \n",
       "..                            ...        ...  \n",
       "445    移动互联网,硬件 / D轮及以上 / 2000人以上       哈啰出行  \n",
       "446  移动互联网,文娱丨内容 / 上市公司 / 2000人以上       哔哩哔哩  \n",
       "447        游戏 / 不需要融资 / 500-2000人       沐瞳游戏  \n",
       "448     企业服务,数据服务 / B轮 / 150-500人  GrowingIO  \n",
       "449  移动互联网,文娱丨内容 / 上市公司 / 2000人以上       哔哩哔哩  \n",
       "\n",
       "[450 rows x 10 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filename = pd.read_sql_table('shanghai_拉钩数据',con=engine,)\n",
    "filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "type(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-03-05 20:12:41,939 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:41,943 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:41,965 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:41,968 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:41,975 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `beijin_拉钩数据`\n",
      "2021-03-05 20:12:41,977 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:41,995 INFO sqlalchemy.engine.base.Engine SELECT `beijin_拉钩数据`.`index`, `beijin_拉钩数据`.`职位名称`, `beijin_拉钩数据`.`公司地址`, `beijin_拉钩数据`.`发布时间`, `beijin_拉钩数据`.`薪资待遇`, `beijin_拉钩数据`.`岗位要求`, `beijin_拉钩数据`.`岗位标签`, `beijin_拉钩数据`.`公司福利`, `beijin_拉钩数据`.`所属行业`, `beijin_拉钩数据`.`公司名称` \n",
      "FROM `beijin_拉钩数据`\n",
      "2021-03-05 20:12:41,998 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,053 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,055 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,063 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,065 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,072 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `chongqing_拉钩数据`\n",
      "2021-03-05 20:12:42,074 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,085 INFO sqlalchemy.engine.base.Engine SELECT `chongqing_拉钩数据`.`index`, `chongqing_拉钩数据`.`职位名称`, `chongqing_拉钩数据`.`公司地址`, `chongqing_拉钩数据`.`发布时间`, `chongqing_拉钩数据`.`薪资待遇`, `chongqing_拉钩数据`.`岗位要求`, `chongqing_拉钩数据`.`岗位标签`, `chongqing_拉钩数据`.`公司福利`, `chongqing_拉钩数据`.`所属行业`, `chongqing_拉钩数据`.`公司名称` \n",
      "FROM `chongqing_拉钩数据`\n",
      "2021-03-05 20:12:42,088 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,122 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,125 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,130 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,134 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,139 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `guanzghou_拉钩数据`\n",
      "2021-03-05 20:12:42,141 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,148 INFO sqlalchemy.engine.base.Engine SELECT `guanzghou_拉钩数据`.`index`, `guanzghou_拉钩数据`.`职位名称`, `guanzghou_拉钩数据`.`公司地址`, `guanzghou_拉钩数据`.`发布时间`, `guanzghou_拉钩数据`.`薪资待遇`, `guanzghou_拉钩数据`.`岗位要求`, `guanzghou_拉钩数据`.`岗位标签`, `guanzghou_拉钩数据`.`公司福利`, `guanzghou_拉钩数据`.`所属行业`, `guanzghou_拉钩数据`.`公司名称` \n",
      "FROM `guanzghou_拉钩数据`\n",
      "2021-03-05 20:12:42,151 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,182 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,184 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,190 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,191 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,196 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `hangzhou_拉钩数据`\n",
      "2021-03-05 20:12:42,197 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,206 INFO sqlalchemy.engine.base.Engine SELECT `hangzhou_拉钩数据`.`index`, `hangzhou_拉钩数据`.`职位名称`, `hangzhou_拉钩数据`.`公司地址`, `hangzhou_拉钩数据`.`发布时间`, `hangzhou_拉钩数据`.`薪资待遇`, `hangzhou_拉钩数据`.`岗位要求`, `hangzhou_拉钩数据`.`岗位标签`, `hangzhou_拉钩数据`.`公司福利`, `hangzhou_拉钩数据`.`所属行业`, `hangzhou_拉钩数据`.`公司名称` \n",
      "FROM `hangzhou_拉钩数据`\n",
      "2021-03-05 20:12:42,207 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,236 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,238 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,243 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,244 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,253 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `nanjing_拉钩数据`\n",
      "2021-03-05 20:12:42,255 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,264 INFO sqlalchemy.engine.base.Engine SELECT `nanjing_拉钩数据`.`index`, `nanjing_拉钩数据`.`职位名称`, `nanjing_拉钩数据`.`公司地址`, `nanjing_拉钩数据`.`发布时间`, `nanjing_拉钩数据`.`薪资待遇`, `nanjing_拉钩数据`.`岗位要求`, `nanjing_拉钩数据`.`岗位标签`, `nanjing_拉钩数据`.`公司福利`, `nanjing_拉钩数据`.`所属行业`, `nanjing_拉钩数据`.`公司名称` \n",
      "FROM `nanjing_拉钩数据`\n",
      "2021-03-05 20:12:42,267 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,300 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,303 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,309 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,312 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,318 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `shanghai_拉钩数据`\n",
      "2021-03-05 20:12:42,319 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,328 INFO sqlalchemy.engine.base.Engine SELECT `shanghai_拉钩数据`.`index`, `shanghai_拉钩数据`.`职位名称`, `shanghai_拉钩数据`.`公司地址`, `shanghai_拉钩数据`.`发布时间`, `shanghai_拉钩数据`.`薪资待遇`, `shanghai_拉钩数据`.`岗位要求`, `shanghai_拉钩数据`.`岗位标签`, `shanghai_拉钩数据`.`公司福利`, `shanghai_拉钩数据`.`所属行业`, `shanghai_拉钩数据`.`公司名称` \n",
      "FROM `shanghai_拉钩数据`\n",
      "2021-03-05 20:12:42,331 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,394 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,396 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,401 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,403 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,408 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `shenzhen_拉钩数据`\n",
      "2021-03-05 20:12:42,410 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,421 INFO sqlalchemy.engine.base.Engine SELECT `shenzhen_拉钩数据`.`index`, `shenzhen_拉钩数据`.`职位名称`, `shenzhen_拉钩数据`.`公司地址`, `shenzhen_拉钩数据`.`发布时间`, `shenzhen_拉钩数据`.`薪资待遇`, `shenzhen_拉钩数据`.`岗位要求`, `shenzhen_拉钩数据`.`岗位标签`, `shenzhen_拉钩数据`.`公司福利`, `shenzhen_拉钩数据`.`所属行业`, `shenzhen_拉钩数据`.`公司名称` \n",
      "FROM `shenzhen_拉钩数据`\n",
      "2021-03-05 20:12:42,423 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,458 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,460 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,465 INFO sqlalchemy.engine.base.Engine SHOW FULL TABLES FROM `pandas_mysql`\n",
      "2021-03-05 20:12:42,468 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,475 INFO sqlalchemy.engine.base.Engine SHOW CREATE TABLE `zhengzhou_拉钩数据`\n",
      "2021-03-05 20:12:42,477 INFO sqlalchemy.engine.base.Engine {}\n",
      "2021-03-05 20:12:42,488 INFO sqlalchemy.engine.base.Engine SELECT `zhengzhou_拉钩数据`.`index`, `zhengzhou_拉钩数据`.`职位名称`, `zhengzhou_拉钩数据`.`公司地址`, `zhengzhou_拉钩数据`.`发布时间`, `zhengzhou_拉钩数据`.`薪资待遇`, `zhengzhou_拉钩数据`.`岗位要求`, `zhengzhou_拉钩数据`.`岗位标签`, `zhengzhou_拉钩数据`.`公司福利`, `zhengzhou_拉钩数据`.`所属行业`, `zhengzhou_拉钩数据`.`公司名称` \n",
      "FROM `zhengzhou_拉钩数据`\n",
      "2021-03-05 20:12:42,490 INFO sqlalchemy.engine.base.Engine {}\n"
     ]
    }
   ],
   "source": [
    "list_1 = ['beijin','chongqing','guanzghou','hangzhou','nanjing','shanghai','shenzhen','zhengzhou']\n",
    "filenames = []\n",
    "for i in list_1:\n",
    "    filename = pd.read_sql_table('{}_拉钩数据'.format(i),con=engine,).drop(['index'],axis=1)\n",
    "    filename['城市']=i\n",
    "        \n",
    "    filenames.append(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10k-20k</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10k-15k</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>苏州街</td>\n",
       "      <td>2020-09-04</td>\n",
       "      <td>15k-20k</td>\n",
       "      <td>15k-20k 经验1-3年 / 本科</td>\n",
       "      <td>教育 大数据</td>\n",
       "      <td>“行业龙头，互联**育”</td>\n",
       "      <td>教育 / 未融资 / 15-50人</td>\n",
       "      <td>世纪高教</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>东城区</td>\n",
       "      <td>2020-07-30</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验1-3年 / 本科</td>\n",
       "      <td>电商</td>\n",
       "      <td>“福利待遇好”</td>\n",
       "      <td>金融,移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>中投亚联</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>资深数据分析师-产品技术中心 (MJ006569)</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>2020-12-08</td>\n",
       "      <td>10k-20k</td>\n",
       "      <td>10k-20k 经验不限 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“团队优秀 大牛多”</td>\n",
       "      <td>移动互联网,广告营销 / 上市公司 / 2000人以上</td>\n",
       "      <td>搜狐集团</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>回龙观</td>\n",
       "      <td>2020-12-13</td>\n",
       "      <td>20k-30k</td>\n",
       "      <td>20k-30k 经验3-5年 / 本科</td>\n",
       "      <td>教育 移动互联网 用户增长 用户研究 数据分析</td>\n",
       "      <td>“核心团队，发展空间大”</td>\n",
       "      <td>教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>好未来</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>高级数据分析师</td>\n",
       "      <td>广安门</td>\n",
       "      <td>2020-10-19</td>\n",
       "      <td>18k-25k</td>\n",
       "      <td>18k-25k 经验3-5年 / 本科</td>\n",
       "      <td>Python 数据挖掘 数据建模 业务分析</td>\n",
       "      <td>“五险一金、项目奖金”</td>\n",
       "      <td>数据服务,企业服务 / 上市公司 / 15-50人</td>\n",
       "      <td>博智数源</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>450 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          职位名称 公司地址        发布时间     薪资待遇                 岗位要求  \\\n",
       "0                        数据分析师  将台路     21:00发布  15k-25k  15k-25k 经验3-5年 / 本科   \n",
       "1                        数据分析师   望京     19:09发布  10k-20k  10k-20k 经验1-3年 / 本科   \n",
       "2                       数据分析专员  立水桥     20:37发布  10k-15k  10k-15k 经验1-3年 / 本科   \n",
       "3                        数据分析师  朝阳区     19:21发布   8k-15k     8k-15k 经验不限 / 不限   \n",
       "4                         数据分析  朝阳区     19:16发布  15k-30k  15k-30k 经验3-5年 / 本科   \n",
       "..                         ...  ...         ...      ...                  ...   \n",
       "445                      数据分析师  苏州街  2020-09-04  15k-20k  15k-20k 经验1-3年 / 本科   \n",
       "446                      数据分析师  东城区  2020-07-30  15k-25k  15k-25k 经验1-3年 / 本科   \n",
       "447  资深数据分析师-产品技术中心 (MJ006569)  海淀区  2020-12-08  10k-20k    10k-20k 经验不限 / 本科   \n",
       "448                      数据分析师  回龙观  2020-12-13  20k-30k  20k-30k 经验3-5年 / 本科   \n",
       "449                    高级数据分析师  广安门  2020-10-19  18k-25k  18k-25k 经验3-5年 / 本科   \n",
       "\n",
       "                         岗位标签                      公司福利  \\\n",
       "0         用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1              竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2          SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3    企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                    大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "..                        ...                       ...   \n",
       "445                    教育 大数据              “行业龙头，互联**育”   \n",
       "446                        电商                   “福利待遇好”   \n",
       "447                      数据分析                “团队优秀 大牛多”   \n",
       "448   教育 移动互联网 用户增长 用户研究 数据分析              “核心团队，发展空间大”   \n",
       "449     Python 数据挖掘 数据建模 业务分析               “五险一金、项目奖金”   \n",
       "\n",
       "                             所属行业    公司名称      城市  \n",
       "0    移动互联网,文娱丨内容 / 不需要融资 / 15-50人   百变大侦探  beijin  \n",
       "1       企业服务,数据服务 / C轮 / 150-500人      数美  beijin  \n",
       "2         移动互联网 / 不需要融资 / 50-150人    琥珀创想  beijin  \n",
       "3              金融 / 未融资 / 50-150人  盛业恒泰投资  beijin  \n",
       "4        信息安全 / 不需要融资 / 500-2000人   360os  beijin  \n",
       "..                            ...     ...     ...  \n",
       "445             教育 / 未融资 / 15-50人    世纪高教  beijin  \n",
       "446    金融,移动互联网 / 不需要融资 / 50-150人    中投亚联  beijin  \n",
       "447   移动互联网,广告营销 / 上市公司 / 2000人以上    搜狐集团  beijin  \n",
       "448           教育 / 上市公司 / 2000人以上     好未来  beijin  \n",
       "449     数据服务,企业服务 / 上市公司 / 15-50人    博智数源  beijin  \n",
       "\n",
       "[450 rows x 10 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filenames[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=filenames[0]\n",
    "df2=filenames[1]\n",
    "df3=filenames[2]\n",
    "df4=filenames[3]\n",
    "df5=filenames[4]\n",
    "df6=filenames[5]\n",
    "df7=filenames[6]\n",
    "df8=filenames[7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(filenames[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
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       "      <td>8k-12k</td>\n",
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       "      <td>数据分析 数据运营 SQL</td>\n",
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       "      <td>社交 / 上市公司 / 2000人以上</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>chongqing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析师（金融方向）</td>\n",
       "      <td>渝北区</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验5-10年 / 本科</td>\n",
       "      <td>数据仓库 Spark MySQL</td>\n",
       "      <td>“发展前景、大牛团队、持牌机构”</td>\n",
       "      <td>金融,移动互联网 / 不需要融资 / 2000人以上</td>\n",
       "      <td>马上消费</td>\n",
       "      <td>chongqing</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>短视频运营经理</td>\n",
       "      <td>渝北区</td>\n",
       "      <td>2020-11-02</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>新媒体 MCN 新媒体运营 短视频 运营管理</td>\n",
       "      <td>“六险一金 弹性打卡 周末双休 带薪休假”</td>\n",
       "      <td>社交网络 / 未融资 / 50-150人</td>\n",
       "      <td>橙新橙艺文化传媒</td>\n",
       "      <td>chongqing</td>\n",
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       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>跨境电商资深运营</td>\n",
       "      <td>渝北区</td>\n",
       "      <td>2020-09-11</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
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       "      <th>297</th>\n",
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       "      <td>8k-12k 经验3-5年 / 本科</td>\n",
       "      <td>数仓工程师 Hive MySQL</td>\n",
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       "      <td>沙坪坝区</td>\n",
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       "      <td>8k-12k</td>\n",
       "      <td>8k-12k 经验3-5年 / 本科</td>\n",
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       "      <td>拼说说教育</td>\n",
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       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>课程顾问</td>\n",
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       "      <td>2020-12-01</td>\n",
       "      <td>5k-10k</td>\n",
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       "      <td>数据服务 / 未融资 / 50-150人</td>\n",
       "      <td>菲欧坦数据</td>\n",
       "      <td>chongqing</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>300 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            职位名称  公司地址        发布时间     薪资待遇                  岗位要求  \\\n",
       "0          数据分析师   大竹林     16:01发布   5k-10k    5k-10k 经验1-3年 / 不限   \n",
       "1        数据分析实习生   渝中区     13:39发布    2k-4k    2k-4k 经验在校/应届 / 本科   \n",
       "2         数据分析主管   江北区  2020-12-22  10k-15k   10k-15k 经验3-5年 / 本科   \n",
       "3     数据分析（运营支持）   渝北区  2020-12-15   8k-12k    8k-12k 经验3-5年 / 本科   \n",
       "4    数据分析师（金融方向）   渝北区  2020-12-24  15k-25k  15k-25k 经验5-10年 / 本科   \n",
       "..           ...   ...         ...      ...                   ...   \n",
       "295      短视频运营经理   渝北区  2020-11-02  15k-25k   15k-25k 经验3-5年 / 本科   \n",
       "296     跨境电商资深运营   渝北区  2020-09-11   8k-10k    8k-10k 经验3-5年 / 本科   \n",
       "297      数据开发工程师   弹子石  2020-11-02   8k-12k    8k-12k 经验3-5年 / 本科   \n",
       "298      新媒体运营总监  沙坪坝区  2020-07-30   8k-12k    8k-12k 经验3-5年 / 本科   \n",
       "299         课程顾问   渝北区  2020-12-01   5k-10k      5k-10k 经验不限 / 不限   \n",
       "\n",
       "                        岗位标签                    公司福利  \\\n",
       "0                       数据分析        “七险一金、年度旅游、弹性工作”   \n",
       "1                    数据分析 统计  “五险一金 绩效奖金 弹性工作 补充医疗险”   \n",
       "2            可视化 数据分析 BI SQL   “大品牌好平台，领导nice，弹性工作制”   \n",
       "3              数据分析 数据运营 SQL        “带薪年假；年度旅游；内部晋升”   \n",
       "4           数据仓库 Spark MySQL        “发展前景、大牛团队、持牌机构”   \n",
       "..                       ...                     ...   \n",
       "295   新媒体 MCN 新媒体运营 短视频 运营管理   “六险一金 弹性打卡 周末双休 带薪休假”   \n",
       "296      内容运营 活动策划 用户运营 网站运营              “发展前期未来可期”   \n",
       "297         数仓工程师 Hive MySQL          “团队气氛融洽、发展前景大”   \n",
       "298  教育 移动互联网 运营 SEM SEO SAO                  “高成长性”   \n",
       "299     教育 企业服务 市场拓展 销售 客户代表       “专业团队，亚马逊圈内知名服务商”   \n",
       "\n",
       "                             所属行业      公司名称         城市  \n",
       "0            信息安全 / 天使轮 / 50-150人     梦之想科技  chongqing  \n",
       "1          企业服务 / 不需要融资 / 50-150人        嘉驰  chongqing  \n",
       "2              金融 / 未融资 / 50-150人      永辉金融  chongqing  \n",
       "3             社交 / 上市公司 / 2000人以上        腾讯  chongqing  \n",
       "4      金融,移动互联网 / 不需要融资 / 2000人以上      马上消费  chongqing  \n",
       "..                            ...       ...        ...  \n",
       "295          社交网络 / 未融资 / 50-150人  橙新橙艺文化传媒  chongqing  \n",
       "296         电商 / 不需要融资 / 150-500人    Firmoo  chongqing  \n",
       "297  数据服务,移动互联网 / 不需要融资 / 50-150人      华龙海数  chongqing  \n",
       "298              教育 / 未融资 / 少于15人     拼说说教育  chongqing  \n",
       "299          数据服务 / 未融资 / 50-150人     菲欧坦数据  chongqing  \n",
       "\n",
       "[300 rows x 10 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
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       "      <td>竞品分析 SaaS 企业软件</td>\n",
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       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10k-15k</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
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       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6k-7k</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2563</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2564 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间     薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15k-25k  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10k-20k  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10k-15k  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8k-15k     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15k-30k  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...      ...                  ...   \n",
       "2559          项目经理   高新区  2020-12-15   8k-15k   8k-15k 经验3-5年 / 大专   \n",
       "2560  算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k  15k-30k 经验1-3年 / 本科   \n",
       "2561          市场调研  航空港区  2020-12-04   8k-10k   8k-10k 经验3-5年 / 本科   \n",
       "2562          客户经理    祭城  2020-08-08    6k-7k   6k-7k 经验在校/应届 / 本科   \n",
       "2563        数据运营专员   金水区  2020-08-24    4k-6k    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2559      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2560                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2561              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2562                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2563  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市  \n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin  \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  \n",
       "...                            ...      ...        ...  \n",
       "2559        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  \n",
       "2560           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  \n",
       "2561      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  \n",
       "2562   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou  \n",
       "2563            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  \n",
       "\n",
       "[2564 rows x 10 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df1,df2,df3,df4,df5,df6,df7,df8],axis=0,ignore_index=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "职位名称    0.00585\n",
       "公司地址    0.00000\n",
       "发布时间    0.00000\n",
       "薪资待遇    0.00000\n",
       "岗位要求    0.00000\n",
       "岗位标签    0.00000\n",
       "公司福利    0.00000\n",
       "所属行业    0.00000\n",
       "公司名称    0.00000\n",
       "城市      0.00000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "渝北区    113\n",
       "南山区    109\n",
       "朝阳区     94\n",
       "西湖区     71\n",
       "海淀区     70\n",
       "      ... \n",
       "回龙观      1\n",
       "万源城      1\n",
       "唐镇       1\n",
       "静安寺      1\n",
       "上城区      1\n",
       "Name: 公司地址, Length: 364, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['公司地址'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>15k高薪聘金融数据分析师 双休 五险</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:25发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>期货 操盘手 外汇 证券</td>\n",
       "      <td>“双休 带薪年假 节日福利 员工旅游”</td>\n",
       "      <td>金融 / 未融资 / 150-500人</td>\n",
       "      <td>储慧国际咨询</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>15k高薪聘金融数据分析师 双休 五险</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:25发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>期货 操盘手 外汇 证券</td>\n",
       "      <td>“双休 带薪年假 节日福利 员工旅游”</td>\n",
       "      <td>金融 / 未融资 / 150-500人</td>\n",
       "      <td>储慧国际咨询</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>资深/数据分析专家【品牌与增长】</td>\n",
       "      <td>昌平区</td>\n",
       "      <td>19:08发布</td>\n",
       "      <td>30k-60k</td>\n",
       "      <td>30k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业 可视化</td>\n",
       "      <td>“六险一金、绩效奖金，股票激励”</td>\n",
       "      <td>教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学-高途课堂</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>资深业务数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:14发布</td>\n",
       "      <td>20k-40k</td>\n",
       "      <td>20k-40k 经验不限 / 不限</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“创新业务，发展空间大”</td>\n",
       "      <td>消费生活 / 上市公司 / 2000人以上</td>\n",
       "      <td>美团</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>资深/数据分析专家【品牌与增长】</td>\n",
       "      <td>昌平区</td>\n",
       "      <td>19:08发布</td>\n",
       "      <td>30k-60k</td>\n",
       "      <td>30k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业 可视化</td>\n",
       "      <td>“六险一金、绩效奖金，股票激励”</td>\n",
       "      <td>教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学-高途课堂</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2561</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6k-7k</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2563</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>476 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     职位名称  公司地址        发布时间     薪资待遇                  岗位要求  \\\n",
       "101   15k高薪聘金融数据分析师 双休 五险   朝阳区     19:25发布   8k-15k      8k-15k 经验不限 / 不限   \n",
       "106   15k高薪聘金融数据分析师 双休 五险   朝阳区     19:25发布   8k-15k      8k-15k 经验不限 / 不限   \n",
       "114      资深/数据分析专家【品牌与增长】   昌平区     19:08发布  30k-60k  30k-60k 经验5-10年 / 本科   \n",
       "116             资深业务数据分析师   朝阳区     19:14发布  20k-40k     20k-40k 经验不限 / 不限   \n",
       "132      资深/数据分析专家【品牌与增长】   昌平区     19:08发布  30k-60k  30k-60k 经验5-10年 / 本科   \n",
       "...                   ...   ...         ...      ...                   ...   \n",
       "2559                 项目经理   高新区  2020-12-15   8k-15k    8k-15k 经验3-5年 / 大专   \n",
       "2560         算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k   15k-30k 经验1-3年 / 本科   \n",
       "2561                 市场调研  航空港区  2020-12-04   8k-10k    8k-10k 经验3-5年 / 本科   \n",
       "2562                 客户经理    祭城  2020-08-08    6k-7k    6k-7k 经验在校/应届 / 本科   \n",
       "2563               数据运营专员   金水区  2020-08-24    4k-6k     4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "101                 期货 操盘手 外汇 证券       “双休 带薪年假 节日福利 员工旅游”   \n",
       "106                 期货 操盘手 外汇 证券       “双休 带薪年假 节日福利 员工旅游”   \n",
       "114             数据分析 数据运营 商业 可视化          “六险一金、绩效奖金，股票激励”   \n",
       "116                         数据分析              “创新业务，发展空间大”   \n",
       "132             数据分析 数据运营 商业 可视化          “六险一金、绩效奖金，股票激励”   \n",
       "...                          ...                       ...   \n",
       "2559      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2560                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2561              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2562                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2563  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                             所属行业      公司名称         城市  \n",
       "101           金融 / 未融资 / 150-500人    储慧国际咨询     beijin  \n",
       "106           金融 / 未融资 / 150-500人    储慧国际咨询     beijin  \n",
       "114           教育 / 上市公司 / 2000人以上  跟谁学-高途课堂     beijin  \n",
       "116         消费生活 / 上市公司 / 2000人以上        美团     beijin  \n",
       "132           教育 / 上市公司 / 2000人以上  跟谁学-高途课堂     beijin  \n",
       "...                           ...       ...        ...  \n",
       "2559       信息安全 / 不需要融资 / 50-150人      崤云安全  zhengzhou  \n",
       "2560          金融 / 上市公司 / 2000人以上      中原银行  zhengzhou  \n",
       "2561     电商,数据服务 / 上市公司 / 2000人以上   富士康科技集团  zhengzhou  \n",
       "2562  教育,移动互联网 / 不需要融资 / 150-500人       校信通  zhengzhou  \n",
       "2563           游戏 / 未融资 / 50-150人      百易科技  zhengzhou  \n",
       "\n",
       "[476 rows x 10 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated(keep=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "职位名称    0.00585\n",
       "公司地址    0.00000\n",
       "发布时间    0.00000\n",
       "薪资待遇    0.00000\n",
       "岗位要求    0.00000\n",
       "岗位标签    0.00000\n",
       "公司福利    0.00000\n",
       "所属行业    0.00000\n",
       "公司名称    0.00000\n",
       "城市      0.00000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#缺失值处理\n",
    "df.isna().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shanghai     450\n",
       "beijin       450\n",
       "nanjing      300\n",
       "shenzhen     300\n",
       "chongqing    300\n",
       "hangzhou     290\n",
       "zhengzhou    258\n",
       "guanzghou    216\n",
       "Name: 城市, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['城市'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['职位名称'].fillna('数据分析师', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "职位名称    0.0\n",
       "公司地址    0.0\n",
       "发布时间    0.0\n",
       "薪资待遇    0.0\n",
       "岗位要求    0.0\n",
       "岗位标签    0.0\n",
       "公司福利    0.0\n",
       "所属行业    0.0\n",
       "公司名称    0.0\n",
       "城市      0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26171829880>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "city_count = df.城市.value_counts()\n",
    "city_count.plot.bar(figsize=(10,6), fontsize=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyecharts\n",
    "from pyecharts.charts import Bar\n",
    "from pyecharts import options as opts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program Files\\anaconda\\lib\\site-packages\\pyecharts\\charts\\chart.py:14: PendingDeprecationWarning: pyecharts 所有图表类型将在 v1.9.0 版本开始强制使用 ChartItem 进行数据项配置 :)\n",
      "  super().__init__(init_opts=init_opts)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"dd32953a9790437c8618f03e452b2280\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_dd32953a9790437c8618f03e452b2280 = echarts.init(\n",
       "                    document.getElementById('dd32953a9790437c8618f03e452b2280'), 'white', {renderer: 'canvas'});\n",
       "                var option_dd32953a9790437c8618f03e452b2280 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5de5\\u4f5c\\u6570\\u91cf\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                450,\n",
       "                450,\n",
       "                300,\n",
       "                300,\n",
       "                300,\n",
       "                290,\n",
       "                258,\n",
       "                216\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5de5\\u4f5c\\u6570\\u91cf\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5de5\\u4f5c\\u6570\\u91cf\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"shanghai\",\n",
       "                \"beijin\",\n",
       "                \"nanjing\",\n",
       "                \"shenzhen\",\n",
       "                \"chongqing\",\n",
       "                \"hangzhou\",\n",
       "                \"zhengzhou\",\n",
       "                \"guanzghou\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u5730\\u533a\\u5206\\u5e03\",\n",
       "            \"left\": \"300\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_dd32953a9790437c8618f03e452b2280.setOption(option_dd32953a9790437c8618f03e452b2280);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x261755a5dc0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = (\n",
    "    Bar() # 创建实例\n",
    "    .add_xaxis(list(city_count.index)) # 添加x轴数据,列表\n",
    "    .add_yaxis('工作数量',list(city_count)) # 添加y轴数据,列表\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"地区分布\",pos_left='300'))\n",
    "    )\n",
    "b.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    " from pyecharts.globals import CurrentConfig, NotebookType\n",
    " CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyecharts.charts import Geo\n",
    "from pyecharts.globals import ChartType, SymbolType"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([('shanghai', 450), ('beijin', 450), ('nanjing', 300), ('shenzhen', 300), ('chongqing', 300), ('hangzhou', 290), ('zhengzhou', 258), ('guanzghou', 216)])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_count.to_dict().items()"
   ]
  },
  {
   "cell_type": "code",
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       "      <td>数据分析师</td>\n",
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       "      <td>数据分析师</td>\n",
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       "      <td>8k-15k</td>\n",
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       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
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       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
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       "      <th>...</th>\n",
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       "      <th>2559</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
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       "    <tr>\n",
       "      <th>2560</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
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       "      <td>2020-11-16</td>\n",
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       "      <td>2020-12-04</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
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       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
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       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
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       "    <tr>\n",
       "      <th>2563</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
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       "              职位名称  公司地址        发布时间     薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15k-25k  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10k-20k  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10k-15k  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8k-15k     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15k-30k  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...      ...                  ...   \n",
       "2559          项目经理   高新区  2020-12-15   8k-15k   8k-15k 经验3-5年 / 大专   \n",
       "2560  算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k  15k-30k 经验1-3年 / 本科   \n",
       "2561          市场调研  航空港区  2020-12-04   8k-10k   8k-10k 经验3-5年 / 本科   \n",
       "2562          客户经理    祭城  2020-08-08    6k-7k   6k-7k 经验在校/应届 / 本科   \n",
       "2563        数据运营专员   金水区  2020-08-24    4k-6k    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2559      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2560                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2561              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2562                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2563  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市  \n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin  \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  \n",
       "...                            ...      ...        ...  \n",
       "2559        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  \n",
       "2560           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  \n",
       "2561      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  \n",
       "2562   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou  \n",
       "2563            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  \n",
       "\n",
       "[2564 rows x 10 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
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    }
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    "df"
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       "      <th>106</th>\n",
       "      <td>15k高薪聘金融数据分析师 双休 五险</td>\n",
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       "      <td>beijin</td>\n",
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       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>资深/数据分析专家【品牌与增长】</td>\n",
       "      <td>昌平区</td>\n",
       "      <td>19:08发布</td>\n",
       "      <td>30k-60k</td>\n",
       "      <td>30k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业 可视化</td>\n",
       "      <td>“六险一金、绩效奖金，股票激励”</td>\n",
       "      <td>教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学-高途课堂</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>资深业务数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:14发布</td>\n",
       "      <td>20k-40k</td>\n",
       "      <td>20k-40k 经验不限 / 不限</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“创新业务，发展空间大”</td>\n",
       "      <td>消费生活 / 上市公司 / 2000人以上</td>\n",
       "      <td>美团</td>\n",
       "      <td>beijin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>资深/数据分析专家【品牌与增长】</td>\n",
       "      <td>昌平区</td>\n",
       "      <td>19:08发布</td>\n",
       "      <td>30k-60k</td>\n",
       "      <td>30k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业 可视化</td>\n",
       "      <td>“六险一金、绩效奖金，股票激励”</td>\n",
       "      <td>教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学-高途课堂</td>\n",
       "      <td>beijin</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>2559</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
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       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
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       "      <th>2560</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
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       "      <td>市场调研</td>\n",
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       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2562</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6k-7k</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2563</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>480 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     职位名称  公司地址        发布时间     薪资待遇                  岗位要求  \\\n",
       "101   15k高薪聘金融数据分析师 双休 五险   朝阳区     19:25发布   8k-15k      8k-15k 经验不限 / 不限   \n",
       "106   15k高薪聘金融数据分析师 双休 五险   朝阳区     19:25发布   8k-15k      8k-15k 经验不限 / 不限   \n",
       "114      资深/数据分析专家【品牌与增长】   昌平区     19:08发布  30k-60k  30k-60k 经验5-10年 / 本科   \n",
       "116             资深业务数据分析师   朝阳区     19:14发布  20k-40k     20k-40k 经验不限 / 不限   \n",
       "132      资深/数据分析专家【品牌与增长】   昌平区     19:08发布  30k-60k  30k-60k 经验5-10年 / 本科   \n",
       "...                   ...   ...         ...      ...                   ...   \n",
       "2559                 项目经理   高新区  2020-12-15   8k-15k    8k-15k 经验3-5年 / 大专   \n",
       "2560         算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k   15k-30k 经验1-3年 / 本科   \n",
       "2561                 市场调研  航空港区  2020-12-04   8k-10k    8k-10k 经验3-5年 / 本科   \n",
       "2562                 客户经理    祭城  2020-08-08    6k-7k    6k-7k 经验在校/应届 / 本科   \n",
       "2563               数据运营专员   金水区  2020-08-24    4k-6k     4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "101                 期货 操盘手 外汇 证券       “双休 带薪年假 节日福利 员工旅游”   \n",
       "106                 期货 操盘手 外汇 证券       “双休 带薪年假 节日福利 员工旅游”   \n",
       "114             数据分析 数据运营 商业 可视化          “六险一金、绩效奖金，股票激励”   \n",
       "116                         数据分析              “创新业务，发展空间大”   \n",
       "132             数据分析 数据运营 商业 可视化          “六险一金、绩效奖金，股票激励”   \n",
       "...                          ...                       ...   \n",
       "2559      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2560                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2561              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2562                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2563  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                             所属行业      公司名称         城市  \n",
       "101           金融 / 未融资 / 150-500人    储慧国际咨询     beijin  \n",
       "106           金融 / 未融资 / 150-500人    储慧国际咨询     beijin  \n",
       "114           教育 / 上市公司 / 2000人以上  跟谁学-高途课堂     beijin  \n",
       "116         消费生活 / 上市公司 / 2000人以上        美团     beijin  \n",
       "132           教育 / 上市公司 / 2000人以上  跟谁学-高途课堂     beijin  \n",
       "...                           ...       ...        ...  \n",
       "2559       信息安全 / 不需要融资 / 50-150人      崤云安全  zhengzhou  \n",
       "2560          金融 / 上市公司 / 2000人以上      中原银行  zhengzhou  \n",
       "2561     电商,数据服务 / 上市公司 / 2000人以上   富士康科技集团  zhengzhou  \n",
       "2562  教育,移动互联网 / 不需要融资 / 150-500人       校信通  zhengzhou  \n",
       "2563           游戏 / 未融资 / 50-150人      百易科技  zhengzhou  \n",
       "\n",
       "[480 rows x 10 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#处理重复值\n",
    "df[df.duplicated(keep=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "      <td>2221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>1042</td>\n",
       "      <td>364</td>\n",
       "      <td>553</td>\n",
       "      <td>154</td>\n",
       "      <td>588</td>\n",
       "      <td>1619</td>\n",
       "      <td>1920</td>\n",
       "      <td>794</td>\n",
       "      <td>1338</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>南山区</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“发展前景”</td>\n",
       "      <td>文娱丨内容 / D轮及以上 / 2000人以上</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>shanghai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>501</td>\n",
       "      <td>109</td>\n",
       "      <td>144</td>\n",
       "      <td>189</td>\n",
       "      <td>100</td>\n",
       "      <td>172</td>\n",
       "      <td>16</td>\n",
       "      <td>74</td>\n",
       "      <td>71</td>\n",
       "      <td>449</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         职位名称  公司地址        发布时间     薪资待遇                 岗位要求  岗位标签    公司福利  \\\n",
       "count    2221  2221        2221     2221                 2221  2221    2221   \n",
       "unique   1042   364         553      154                  588  1619    1920   \n",
       "top     数据分析师   南山区  2020-12-24  15k-25k  15k-25k 经验3-5年 / 本科  数据分析  “发展前景”   \n",
       "freq      501   109         144      189                  100   172      16   \n",
       "\n",
       "                           所属行业  公司名称        城市  \n",
       "count                      2221  2221      2221  \n",
       "unique                      794  1338         8  \n",
       "top     文娱丨内容 / D轮及以上 / 2000人以上  字节跳动  shanghai  \n",
       "freq                         74    71       449  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.drop_duplicates().reset_index(drop=True)\n",
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       15k-25k 经验3-5年 / 本科\n",
       "1       10k-20k 经验1-3年 / 本科\n",
       "2       10k-15k 经验1-3年 / 本科\n",
       "3          8k-15k 经验不限 / 不限\n",
       "4       15k-30k 经验3-5年 / 本科\n",
       "               ...         \n",
       "2216     8k-15k 经验3-5年 / 大专\n",
       "2217    15k-30k 经验1-3年 / 本科\n",
       "2218     8k-10k 经验3-5年 / 本科\n",
       "2219     6k-7k 经验在校/应届 / 本科\n",
       "2220      4k-6k 经验1-3年 / 大专\n",
       "Name: 岗位要求, Length: 2221, dtype: object"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#处理岗位要求\n",
    "df['岗位要求']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "coll = df['岗位要求'].str.split(\n",
    "    r'[ /]+', expand=True).rename(\n",
    "    columns={0:'薪资待遇', 1:'经验要求', 2:'学历'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "collnew=coll.drop([3],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15k-25k</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10k-20k</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10k-15k</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8k-15k</td>\n",
       "      <td>经验不限</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15k-30k</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>8k-15k</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>15k-30k</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>8k-10k</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>6k-7k</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>4k-6k</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2221 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         薪资待遇    经验要求  学历\n",
       "0     15k-25k  经验3-5年  本科\n",
       "1     10k-20k  经验1-3年  本科\n",
       "2     10k-15k  经验1-3年  本科\n",
       "3      8k-15k    经验不限  不限\n",
       "4     15k-30k  经验3-5年  本科\n",
       "...       ...     ...  ..\n",
       "2216   8k-15k  经验3-5年  大专\n",
       "2217  15k-30k  经验1-3年  本科\n",
       "2218   8k-10k  经验3-5年  本科\n",
       "2219    6k-7k    经验在校  应届\n",
       "2220    4k-6k  经验1-3年  大专\n",
       "\n",
       "[2221 rows x 3 columns]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collnew"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat([df,collnew.iloc[:,1:]],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>3</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10k-20k</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10k-15k</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>None</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6k-7k</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>本科</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2221 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间     薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15k-25k  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10k-20k  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10k-15k  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8k-15k     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15k-30k  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...      ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8k-15k   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8k-10k   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6k-7k   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4k-6k    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历     3  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科  None   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科  None   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科  None   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限  None   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科  None   \n",
       "...                            ...      ...        ...     ...  ..   ...   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专  None   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科  None   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科  None   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届    本科   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专  None   \n",
       "\n",
       "        经验要求  学历  \n",
       "0     经验3-5年  本科  \n",
       "1     经验1-3年  本科  \n",
       "2     经验1-3年  本科  \n",
       "3       经验不限  不限  \n",
       "4     经验3-5年  本科  \n",
       "...      ...  ..  \n",
       "2216  经验3-5年  大专  \n",
       "2217  经验1-3年  本科  \n",
       "2218  经验3-5年  本科  \n",
       "2219    经验在校  应届  \n",
       "2220  经验1-3年  大专  \n",
       "\n",
       "[2221 rows x 15 columns]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       移动互联网,文娱丨内容 / 不需要融资 / 15-50人\n",
       "1          企业服务,数据服务 / C轮 / 150-500人\n",
       "2            移动互联网 / 不需要融资 / 50-150人\n",
       "3                 金融 / 未融资 / 50-150人\n",
       "4           信息安全 / 不需要融资 / 500-2000人\n",
       "                    ...             \n",
       "2216          信息安全 / 不需要融资 / 50-150人\n",
       "2217             金融 / 上市公司 / 2000人以上\n",
       "2218        电商,数据服务 / 上市公司 / 2000人以上\n",
       "2219     教育,移动互联网 / 不需要融资 / 150-500人\n",
       "2220              游戏 / 未融资 / 50-150人\n",
       "Name: 所属行业, Length: 2221, dtype: object"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#处理所属行业\n",
    "df['所属行业']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "col2 = df['所属行业'].str.split(\n",
    "    r'[/]+', expand=True).rename(\n",
    "    columns={0:'行业', 1:'融资', 2:'人数'}).apply(\n",
    "    lambda x: x.str.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "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>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2221 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               行业     融资         人数\n",
       "0     移动互联网,文娱丨内容  不需要融资     15-50人\n",
       "1       企业服务,数据服务     C轮   150-500人\n",
       "2           移动互联网  不需要融资    50-150人\n",
       "3              金融    未融资    50-150人\n",
       "4            信息安全  不需要融资  500-2000人\n",
       "...           ...    ...        ...\n",
       "2216         信息安全  不需要融资    50-150人\n",
       "2217           金融   上市公司    2000人以上\n",
       "2218      电商,数据服务   上市公司    2000人以上\n",
       "2219     教育,移动互联网  不需要融资   150-500人\n",
       "2220           游戏    未融资    50-150人\n",
       "\n",
       "[2221 rows x 3 columns]"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat([df, col2], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>3</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15k-25k</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10k-20k</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10k-15k</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>None</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8k-15k</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15k-30k</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8k-10k</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6k-7k</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>本科</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4k-6k</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2221 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间     薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15k-25k  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10k-20k  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10k-15k  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8k-15k     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15k-30k  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...      ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8k-15k   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15k-30k  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8k-10k   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6k-7k   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4k-6k    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历     3  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科  None   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科  None   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科  None   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限  None   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科  None   \n",
       "...                            ...      ...        ...     ...  ..   ...   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专  None   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科  None   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科  None   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届    本科   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专  None   \n",
       "\n",
       "        经验要求  学历           行业     融资         人数  \n",
       "0     经验3-5年  本科  移动互联网,文娱丨内容  不需要融资     15-50人  \n",
       "1     经验1-3年  本科    企业服务,数据服务     C轮   150-500人  \n",
       "2     经验1-3年  本科        移动互联网  不需要融资    50-150人  \n",
       "3       经验不限  不限           金融    未融资    50-150人  \n",
       "4     经验3-5年  本科         信息安全  不需要融资  500-2000人  \n",
       "...      ...  ..          ...    ...        ...  \n",
       "2216  经验3-5年  大专         信息安全  不需要融资    50-150人  \n",
       "2217  经验1-3年  本科           金融   上市公司    2000人以上  \n",
       "2218  经验3-5年  本科      电商,数据服务   上市公司    2000人以上  \n",
       "2219    经验在校  应届     教育,移动互联网  不需要融资   150-500人  \n",
       "2220  经验1-3年  大专           游戏    未融资    50-150人  \n",
       "\n",
       "[2221 rows x 18 columns]"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['15000-25000',\n",
       " '15000-30000',\n",
       " '20000-40000',\n",
       " '10000-20000',\n",
       " '10000-15000',\n",
       " '20000-30000',\n",
       " '8000-15000',\n",
       " '15000-20000',\n",
       " '20000-35000',\n",
       " '25000-50000',\n",
       " '6000-10000',\n",
       " '8000-12000',\n",
       " '12000-20000',\n",
       " '6000-8000',\n",
       " '5000-10000',\n",
       " '8000-10000',\n",
       " '4000-6000',\n",
       " '4000-8000',\n",
       " '25000-35000',\n",
       " '6000-12000',\n",
       " '12000-18000',\n",
       " '12000-24000',\n",
       " '25000-40000',\n",
       " '2000-3000',\n",
       " '8000-16000',\n",
       " '5000-8000',\n",
       " '30000-60000',\n",
       " '3000-6000',\n",
       " '7000-14000',\n",
       " '2000-4000',\n",
       " '10000-18000',\n",
       " '3000-5000',\n",
       " '3000-4000',\n",
       " '25000-45000',\n",
       " '5000-7000',\n",
       " '13000-25000',\n",
       " '7000-12000',\n",
       " '18000-25000',\n",
       " '20000-25000',\n",
       " '8000-13000',\n",
       " '30000-50000',\n",
       " '6000-9000',\n",
       " '18000-30000',\n",
       " '4000-5000',\n",
       " '30000-40000',\n",
       " '18000-35000',\n",
       " '10000-16000',\n",
       " '12000-15000',\n",
       " '7000-9000',\n",
       " '9000-15000',\n",
       " '7000-10000',\n",
       " '11000-20000',\n",
       " '15000-28000',\n",
       " '9000-13000',\n",
       " '10000-12000',\n",
       " '12000-16000',\n",
       " '15000-22000',\n",
       " '18000-36000',\n",
       " '8000-14000',\n",
       " '13000-18000',\n",
       " '14000-20000',\n",
       " '9000-14000',\n",
       " '40000-60000',\n",
       " '6000-11000',\n",
       " '1000-2000',\n",
       " '25000-30000',\n",
       " '6000-7000',\n",
       " '5000-9000',\n",
       " '4000-7000',\n",
       " '40000-80000',\n",
       " '9000-18000',\n",
       " '13000-26000',\n",
       " '35000-45000',\n",
       " '30000-45000',\n",
       " '18000-28000',\n",
       " '11000-22000',\n",
       " '7000-13000',\n",
       " '11000-18000',\n",
       " '16000-25000',\n",
       " '17000-25000',\n",
       " '22000-35000',\n",
       " '5000-6000',\n",
       " '9000-11000',\n",
       " '10000-13000',\n",
       " '9000-16000',\n",
       " '13000-20000',\n",
       " '8000-9000',\n",
       " '17000-30000',\n",
       " '9000-12000',\n",
       " '16000-20000',\n",
       " '14000-18000',\n",
       " '14000-28000',\n",
       " '35000-55000',\n",
       " '35000-50000',\n",
       " '16000-32000',\n",
       " '13000-23000',\n",
       " '35000-70000',\n",
       " '17000-32000',\n",
       " '50000-100000',\n",
       " '22000-30000',\n",
       " '16000-30000',\n",
       " '13000-16000',\n",
       " '35000-60000',\n",
       " '10000-17000',\n",
       " '15000-23000',\n",
       " '18000-22000',\n",
       " '40000-70000',\n",
       " '7000-8000',\n",
       " '11000-15000',\n",
       " '14000-25000',\n",
       " '8000-11000',\n",
       " '13000-15000',\n",
       " '28000-46000',\n",
       " '18000-32000',\n",
       " '27000-40000',\n",
       " '20000-27000',\n",
       " '28000-50000',\n",
       " '13000-24000',\n",
       " '18000-34000',\n",
       " '45000-90000',\n",
       " '20000-28000',\n",
       " '23000-40000',\n",
       " '15000-18000',\n",
       " '14000-24000',\n",
       " '11000-16000',\n",
       " '23000-35000',\n",
       " '10000-14000',\n",
       " '15000-24000',\n",
       " '3000以上',\n",
       " '27000-37000',\n",
       " '15000-26000',\n",
       " '10000-11000',\n",
       " '28000-48000',\n",
       " '14000-22000',\n",
       " '60000-90000',\n",
       " '17000-24000',\n",
       " '23000-45000',\n",
       " '30000-33000',\n",
       " '18000-20000',\n",
       " '30000-36000',\n",
       " '7000-11000',\n",
       " '18000-24000',\n",
       " '25000-33000',\n",
       " '13000-19000',\n",
       " '17000-23000',\n",
       " '16000-18000',\n",
       " '14000-21000',\n",
       " '17000-27000',\n",
       " '22000-42000',\n",
       " '16000-22000',\n",
       " '20000-36000',\n",
       " '22000-44000',\n",
       " '16000-28000',\n",
       " '20000-32000']"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#处理薪资，描述薪资\n",
    "df['薪资待遇'].str.replace('k', '000', case=False).value_counts().index.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['薪资待遇'] = df['薪资待遇'].str.replace('k', '000', case=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df[-df.薪资待遇.isin(['3000以上'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat([df,df['薪资待遇'].str.split('-', expand=True).rename(columns={0:'最低薪资',1:'最高薪资'}).astype(int)], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>3</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10000-15000</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>None</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8000-10000</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>None</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>8000</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6000-7000</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>本科</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>6000</td>\n",
       "      <td>7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4000-6000</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>None</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>4000</td>\n",
       "      <td>6000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间         薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15000-25000  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10000-20000  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10000-15000  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8000-15000     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15000-30000  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...          ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8000-15000   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15000-30000  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8000-10000   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6000-7000   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4000-6000    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历     3  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科  None   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科  None   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科  None   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限  None   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科  None   \n",
       "...                            ...      ...        ...     ...  ..   ...   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专  None   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科  None   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科  None   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届    本科   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专  None   \n",
       "\n",
       "        经验要求  学历           行业     融资         人数   最低薪资   最高薪资  \n",
       "0     经验3-5年  本科  移动互联网,文娱丨内容  不需要融资     15-50人  15000  25000  \n",
       "1     经验1-3年  本科    企业服务,数据服务     C轮   150-500人  10000  20000  \n",
       "2     经验1-3年  本科        移动互联网  不需要融资    50-150人  10000  15000  \n",
       "3       经验不限  不限           金融    未融资    50-150人   8000  15000  \n",
       "4     经验3-5年  本科         信息安全  不需要融资  500-2000人  15000  30000  \n",
       "...      ...  ..          ...    ...        ...    ...    ...  \n",
       "2216  经验3-5年  大专         信息安全  不需要融资    50-150人   8000  15000  \n",
       "2217  经验1-3年  本科           金融   上市公司    2000人以上  15000  30000  \n",
       "2218  经验3-5年  本科      电商,数据服务   上市公司    2000人以上   8000  10000  \n",
       "2219    经验在校  应届     教育,移动互联网  不需要融资   150-500人   6000   7000  \n",
       "2220  经验1-3年  大专           游戏    未融资    50-150人   4000   6000  \n",
       "\n",
       "[2220 rows x 20 columns]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "#生成平均薪资列\n",
    "df['平均薪资'] = df[['最低薪资', '最高薪资']].mean(1)\n",
    "df=df.drop([3],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10000-15000</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>15000</td>\n",
       "      <td>12500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8000-10000</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>8000</td>\n",
       "      <td>10000</td>\n",
       "      <td>9000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6000-7000</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>6000</td>\n",
       "      <td>7000</td>\n",
       "      <td>6500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4000-6000</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>4000</td>\n",
       "      <td>6000</td>\n",
       "      <td>5000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间         薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15000-25000  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10000-20000  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10000-15000  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8000-15000     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15000-30000  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...          ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8000-15000   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15000-30000  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8000-10000   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6000-7000   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4000-6000    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科   \n",
       "...                            ...      ...        ...     ...  ..   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专   \n",
       "\n",
       "               行业     融资         人数   最低薪资   最高薪资     平均薪资  \n",
       "0     移动互联网,文娱丨内容  不需要融资     15-50人  15000  25000  20000.0  \n",
       "1       企业服务,数据服务     C轮   150-500人  10000  20000  15000.0  \n",
       "2           移动互联网  不需要融资    50-150人  10000  15000  12500.0  \n",
       "3              金融    未融资    50-150人   8000  15000  11500.0  \n",
       "4            信息安全  不需要融资  500-2000人  15000  30000  22500.0  \n",
       "...           ...    ...        ...    ...    ...      ...  \n",
       "2216         信息安全  不需要融资    50-150人   8000  15000  11500.0  \n",
       "2217           金融   上市公司    2000人以上  15000  30000  22500.0  \n",
       "2218      电商,数据服务   上市公司    2000人以上   8000  10000   9000.0  \n",
       "2219     教育,移动互联网  不需要融资   150-500人   6000   7000   6500.0  \n",
       "2220           游戏    未融资    50-150人   4000   6000   5000.0  \n",
       "\n",
       "[2220 rows x 18 columns]"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "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>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2220.000000</td>\n",
       "      <td>2220.000000</td>\n",
       "      <td>2220.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>13212.612613</td>\n",
       "      <td>22663.963964</td>\n",
       "      <td>17938.288288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7274.246858</td>\n",
       "      <td>13181.017205</td>\n",
       "      <td>10123.283446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.1%</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8000.000000</td>\n",
       "      <td>12000.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>12000.000000</td>\n",
       "      <td>20000.000000</td>\n",
       "      <td>16000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>17250.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>22500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99.9%</th>\n",
       "      <td>48905.000000</td>\n",
       "      <td>90000.000000</td>\n",
       "      <td>73357.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>60000.000000</td>\n",
       "      <td>100000.000000</td>\n",
       "      <td>75000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               最低薪资           最高薪资          平均薪资\n",
       "count   2220.000000    2220.000000   2220.000000\n",
       "mean   13212.612613   22663.963964  17938.288288\n",
       "std     7274.246858   13181.017205  10123.283446\n",
       "min     1000.000000    2000.000000   1500.000000\n",
       "0.1%    1000.000000    2000.000000   1500.000000\n",
       "25%     8000.000000   12000.000000  10000.000000\n",
       "50%    12000.000000   20000.000000  16000.000000\n",
       "75%    17250.000000   30000.000000  22500.000000\n",
       "99.9%  48905.000000   90000.000000  73357.500000\n",
       "max    60000.000000  100000.000000  75000.000000"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#薪资描述性分析\n",
    "df.describe(percentiles=[0.001,0.25,0.5,0.75,0.999])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(0,80000,3000)\n",
    "df.平均薪资.plot(kind='density',grid=True,figsize=(14,6),xlim=(-1000,80000),xticks=x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "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>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>城市</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>beijin</th>\n",
       "      <td>16136.465324</td>\n",
       "      <td>27865.771812</td>\n",
       "      <td>22001.118568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hangzhou</th>\n",
       "      <td>14993.865031</td>\n",
       "      <td>26055.214724</td>\n",
       "      <td>20524.539877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shenzhen</th>\n",
       "      <td>15053.511706</td>\n",
       "      <td>25903.010033</td>\n",
       "      <td>20478.260870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shanghai</th>\n",
       "      <td>14930.957684</td>\n",
       "      <td>25806.236080</td>\n",
       "      <td>20368.596882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>guanzghou</th>\n",
       "      <td>12447.619048</td>\n",
       "      <td>21019.047619</td>\n",
       "      <td>16733.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nanjing</th>\n",
       "      <td>10183.333333</td>\n",
       "      <td>17243.333333</td>\n",
       "      <td>13713.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chongqing</th>\n",
       "      <td>8716.216216</td>\n",
       "      <td>14567.567568</td>\n",
       "      <td>11641.891892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zhengzhou</th>\n",
       "      <td>7406.862745</td>\n",
       "      <td>12431.372549</td>\n",
       "      <td>9919.117647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   最低薪资          最高薪资          平均薪资\n",
       "城市                                                 \n",
       "beijin     16136.465324  27865.771812  22001.118568\n",
       "hangzhou   14993.865031  26055.214724  20524.539877\n",
       "shenzhen   15053.511706  25903.010033  20478.260870\n",
       "shanghai   14930.957684  25806.236080  20368.596882\n",
       "guanzghou  12447.619048  21019.047619  16733.333333\n",
       "nanjing    10183.333333  17243.333333  13713.333333\n",
       "chongqing   8716.216216  14567.567568  11641.891892\n",
       "zhengzhou   7406.862745  12431.372549   9919.117647"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(by='城市').mean().sort_values('平均薪资',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['城市','平均薪资']].boxplot(by='城市',rot=45, fontsize=15, figsize=(8,12))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "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>经验要求</th>\n",
       "      <th>经验要求</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>经验3-5年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>经验1-3年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>经验1-3年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>经验不限</td>\n",
       "      <td>经验不限</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>经验3-5年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>经验3-5年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>经验1-3年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>经验3-5年</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>经验在校</td>\n",
       "      <td>经验在校</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>经验1-3年</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        经验要求    经验要求\n",
       "0     经验3-5年  经验3-5年\n",
       "1     经验1-3年  经验1-3年\n",
       "2     经验1-3年  经验1-3年\n",
       "3       经验不限    经验不限\n",
       "4     经验3-5年  经验3-5年\n",
       "...      ...     ...\n",
       "2216  经验3-5年  经验3-5年\n",
       "2217  经验1-3年  经验1-3年\n",
       "2218  经验3-5年  经验3-5年\n",
       "2219    经验在校    经验在校\n",
       "2220  经验1-3年  经验1-3年\n",
       "\n",
       "[2220 rows x 2 columns]"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['经验要求']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.T.drop_duplicates().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
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       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10000-15000</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>15000</td>\n",
       "      <td>12500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8000-10000</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>8000</td>\n",
       "      <td>10000</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6000-7000</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>6000</td>\n",
       "      <td>7000</td>\n",
       "      <td>6500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4000-6000</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>4000</td>\n",
       "      <td>6000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间         薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15000-25000  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10000-20000  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10000-15000  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8000-15000     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15000-30000  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...          ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8000-15000   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15000-30000  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8000-10000   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6000-7000   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4000-6000    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科   \n",
       "...                            ...      ...        ...     ...  ..   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专   \n",
       "\n",
       "               行业     融资         人数   最低薪资   最高薪资   平均薪资  \n",
       "0     移动互联网,文娱丨内容  不需要融资     15-50人  15000  25000  20000  \n",
       "1       企业服务,数据服务     C轮   150-500人  10000  20000  15000  \n",
       "2           移动互联网  不需要融资    50-150人  10000  15000  12500  \n",
       "3              金融    未融资    50-150人   8000  15000  11500  \n",
       "4            信息安全  不需要融资  500-2000人  15000  30000  22500  \n",
       "...           ...    ...        ...    ...    ...    ...  \n",
       "2216         信息安全  不需要融资    50-150人   8000  15000  11500  \n",
       "2217           金融   上市公司    2000人以上  15000  30000  22500  \n",
       "2218      电商,数据服务   上市公司    2000人以上   8000  10000   9000  \n",
       "2219     教育,移动互联网  不需要融资   150-500人   6000   7000   6500  \n",
       "2220           游戏    未融资    50-150人   4000   6000   5000  \n",
       "\n",
       "[2220 rows x 18 columns]"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['学历']=df['学历'].replace('None','本科')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>将台路</td>\n",
       "      <td>21:00发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>用户研究 需求分析 数据分析 用户增长</td>\n",
       "      <td>“五险一金 免费工作餐 定期体检”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 15-50人</td>\n",
       "      <td>百变大侦探</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>15-50人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>望京</td>\n",
       "      <td>19:09发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>竞品分析 SaaS 企业软件</td>\n",
       "      <td>“风控独角兽、飞速发展、待遇给力”</td>\n",
       "      <td>企业服务,数据服务 / C轮 / 150-500人</td>\n",
       "      <td>数美</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>数据分析专员</td>\n",
       "      <td>立水桥</td>\n",
       "      <td>20:37发布</td>\n",
       "      <td>10000-15000</td>\n",
       "      <td>10k-15k 经验1-3年 / 本科</td>\n",
       "      <td>SQL python Linux系统</td>\n",
       "      <td>“午晚餐；六险一金；高效协作的团队；信息共享；”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 50-150人</td>\n",
       "      <td>琥珀创想</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>15000</td>\n",
       "      <td>12500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:21发布</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验不限 / 不限</td>\n",
       "      <td>企业服务 信息安全 需求分析 竞品分析 数据分析</td>\n",
       "      <td>“五险一金 双休 每年两次国内外游 弹性工作”</td>\n",
       "      <td>金融 / 未融资 / 50-150人</td>\n",
       "      <td>盛业恒泰投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>不限</td>\n",
       "      <td>金融</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>数据分析</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>19:16发布</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验3-5年 / 本科</td>\n",
       "      <td>大数据 数据挖掘</td>\n",
       "      <td>“大平台,核心部门,领导好”</td>\n",
       "      <td>信息安全 / 不需要融资 / 500-2000人</td>\n",
       "      <td>360os</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2216</th>\n",
       "      <td>项目经理</td>\n",
       "      <td>高新区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>8000-15000</td>\n",
       "      <td>8k-15k 经验3-5年 / 大专</td>\n",
       "      <td>信息安全 政务 项目管理 过程管理 需求分析</td>\n",
       "      <td>“政府主导、自研项目、六险一金、提供食宿”</td>\n",
       "      <td>信息安全 / 不需要融资 / 50-150人</td>\n",
       "      <td>崤云安全</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>大专</td>\n",
       "      <td>信息安全</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>8000</td>\n",
       "      <td>15000</td>\n",
       "      <td>11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>算法工程师（中级、高级）</td>\n",
       "      <td>郑东新区</td>\n",
       "      <td>2020-11-16</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>算法工程师</td>\n",
       "      <td>“五险一金 住房餐贴 带薪年假 交通补助”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>中原银行</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>市场调研</td>\n",
       "      <td>航空港区</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>8000-10000</td>\n",
       "      <td>8k-10k 经验3-5年 / 本科</td>\n",
       "      <td>信息收集 数据分析 竞品调研</td>\n",
       "      <td>“工作弹性 管理正规”</td>\n",
       "      <td>电商,数据服务 / 上市公司 / 2000人以上</td>\n",
       "      <td>富士康科技集团</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>电商,数据服务</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>8000</td>\n",
       "      <td>10000</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2219</th>\n",
       "      <td>客户经理</td>\n",
       "      <td>祭城</td>\n",
       "      <td>2020-08-08</td>\n",
       "      <td>6000-7000</td>\n",
       "      <td>6k-7k 经验在校/应届 / 本科</td>\n",
       "      <td>教育 移动互联网</td>\n",
       "      <td>“五险一金、工作餐、图书馆、健身房等等”</td>\n",
       "      <td>教育,移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>校信通</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>教育,移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>6000</td>\n",
       "      <td>7000</td>\n",
       "      <td>6500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>数据运营专员</td>\n",
       "      <td>金水区</td>\n",
       "      <td>2020-08-24</td>\n",
       "      <td>4000-6000</td>\n",
       "      <td>4k-6k 经验1-3年 / 大专</td>\n",
       "      <td>移动互联网 活动运营 游戏运营 APP运营 数据分析</td>\n",
       "      <td>“五险一金 免费午餐 体检 节假日福利 年终奖”</td>\n",
       "      <td>游戏 / 未融资 / 50-150人</td>\n",
       "      <td>百易科技</td>\n",
       "      <td>zhengzhou</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>大专</td>\n",
       "      <td>游戏</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>4000</td>\n",
       "      <td>6000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              职位名称  公司地址        发布时间         薪资待遇                 岗位要求  \\\n",
       "0            数据分析师   将台路     21:00发布  15000-25000  15k-25k 经验3-5年 / 本科   \n",
       "1            数据分析师    望京     19:09发布  10000-20000  10k-20k 经验1-3年 / 本科   \n",
       "2           数据分析专员   立水桥     20:37发布  10000-15000  10k-15k 经验1-3年 / 本科   \n",
       "3            数据分析师   朝阳区     19:21发布   8000-15000     8k-15k 经验不限 / 不限   \n",
       "4             数据分析   朝阳区     19:16发布  15000-30000  15k-30k 经验3-5年 / 本科   \n",
       "...            ...   ...         ...          ...                  ...   \n",
       "2216          项目经理   高新区  2020-12-15   8000-15000   8k-15k 经验3-5年 / 大专   \n",
       "2217  算法工程师（中级、高级）  郑东新区  2020-11-16  15000-30000  15k-30k 经验1-3年 / 本科   \n",
       "2218          市场调研  航空港区  2020-12-04   8000-10000   8k-10k 经验3-5年 / 本科   \n",
       "2219          客户经理    祭城  2020-08-08    6000-7000   6k-7k 经验在校/应届 / 本科   \n",
       "2220        数据运营专员   金水区  2020-08-24    4000-6000    4k-6k 经验1-3年 / 大专   \n",
       "\n",
       "                            岗位标签                      公司福利  \\\n",
       "0            用户研究 需求分析 数据分析 用户增长         “五险一金 免费工作餐 定期体检”   \n",
       "1                 竞品分析 SaaS 企业软件         “风控独角兽、飞速发展、待遇给力”   \n",
       "2             SQL python Linux系统  “午晚餐；六险一金；高效协作的团队；信息共享；”   \n",
       "3       企业服务 信息安全 需求分析 竞品分析 数据分析   “五险一金 双休 每年两次国内外游 弹性工作”   \n",
       "4                       大数据 数据挖掘            “大平台,核心部门,领导好”   \n",
       "...                          ...                       ...   \n",
       "2216      信息安全 政务 项目管理 过程管理 需求分析     “政府主导、自研项目、六险一金、提供食宿”   \n",
       "2217                       算法工程师     “五险一金 住房餐贴 带薪年假 交通补助”   \n",
       "2218              信息收集 数据分析 竞品调研               “工作弹性 管理正规”   \n",
       "2219                    教育 移动互联网      “五险一金、工作餐、图书馆、健身房等等”   \n",
       "2220  移动互联网 活动运营 游戏运营 APP运营 数据分析  “五险一金 免费午餐 体检 节假日福利 年终奖”   \n",
       "\n",
       "                              所属行业     公司名称         城市    经验要求  学历  \\\n",
       "0     移动互联网,文娱丨内容 / 不需要融资 / 15-50人    百变大侦探     beijin  经验3-5年  本科   \n",
       "1        企业服务,数据服务 / C轮 / 150-500人       数美     beijin  经验1-3年  本科   \n",
       "2          移动互联网 / 不需要融资 / 50-150人     琥珀创想     beijin  经验1-3年  本科   \n",
       "3               金融 / 未融资 / 50-150人   盛业恒泰投资     beijin    经验不限  不限   \n",
       "4         信息安全 / 不需要融资 / 500-2000人    360os     beijin  经验3-5年  本科   \n",
       "...                            ...      ...        ...     ...  ..   \n",
       "2216        信息安全 / 不需要融资 / 50-150人     崤云安全  zhengzhou  经验3-5年  大专   \n",
       "2217           金融 / 上市公司 / 2000人以上     中原银行  zhengzhou  经验1-3年  本科   \n",
       "2218      电商,数据服务 / 上市公司 / 2000人以上  富士康科技集团  zhengzhou  经验3-5年  本科   \n",
       "2219   教育,移动互联网 / 不需要融资 / 150-500人      校信通  zhengzhou    经验在校  应届   \n",
       "2220            游戏 / 未融资 / 50-150人     百易科技  zhengzhou  经验1-3年  大专   \n",
       "\n",
       "               行业     融资         人数   最低薪资   最高薪资   平均薪资  \n",
       "0     移动互联网,文娱丨内容  不需要融资     15-50人  15000  25000  20000  \n",
       "1       企业服务,数据服务     C轮   150-500人  10000  20000  15000  \n",
       "2           移动互联网  不需要融资    50-150人  10000  15000  12500  \n",
       "3              金融    未融资    50-150人   8000  15000  11500  \n",
       "4            信息安全  不需要融资  500-2000人  15000  30000  22500  \n",
       "...           ...    ...        ...    ...    ...    ...  \n",
       "2216         信息安全  不需要融资    50-150人   8000  15000  11500  \n",
       "2217           金融   上市公司    2000人以上  15000  30000  22500  \n",
       "2218      电商,数据服务   上市公司    2000人以上   8000  10000   9000  \n",
       "2219     教育,移动互联网  不需要融资   150-500人   6000   7000   6500  \n",
       "2220           游戏    未融资    50-150人   4000   6000   5000  \n",
       "\n",
       "[2220 rows x 18 columns]"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th colspan=\"2\" halign=\"left\">发布时间</th>\n",
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       "      <th>...</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>学历</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>不限</th>\n",
       "      <td>94</td>\n",
       "      <td>71</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>15</td>\n",
       "      <td>94</td>\n",
       "      <td>57</td>\n",
       "      <td>金水区</td>\n",
       "      <td>8</td>\n",
       "      <td>94</td>\n",
       "      <td>67</td>\n",
       "      <td>...</td>\n",
       "      <td>8000</td>\n",
       "      <td>17</td>\n",
       "      <td>94</td>\n",
       "      <td>22</td>\n",
       "      <td>15000</td>\n",
       "      <td>12</td>\n",
       "      <td>94.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>11500.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大专</th>\n",
       "      <td>196</td>\n",
       "      <td>144</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>18</td>\n",
       "      <td>196</td>\n",
       "      <td>80</td>\n",
       "      <td>金水区</td>\n",
       "      <td>14</td>\n",
       "      <td>196</td>\n",
       "      <td>120</td>\n",
       "      <td>...</td>\n",
       "      <td>4000</td>\n",
       "      <td>35</td>\n",
       "      <td>196</td>\n",
       "      <td>21</td>\n",
       "      <td>8000</td>\n",
       "      <td>33</td>\n",
       "      <td>196.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>应届</th>\n",
       "      <td>190</td>\n",
       "      <td>113</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>29</td>\n",
       "      <td>190</td>\n",
       "      <td>105</td>\n",
       "      <td>天河区</td>\n",
       "      <td>8</td>\n",
       "      <td>190</td>\n",
       "      <td>109</td>\n",
       "      <td>...</td>\n",
       "      <td>2000</td>\n",
       "      <td>37</td>\n",
       "      <td>190</td>\n",
       "      <td>24</td>\n",
       "      <td>4000</td>\n",
       "      <td>30</td>\n",
       "      <td>190.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>本科</th>\n",
       "      <td>1671</td>\n",
       "      <td>764</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>427</td>\n",
       "      <td>1671</td>\n",
       "      <td>317</td>\n",
       "      <td>南山区</td>\n",
       "      <td>101</td>\n",
       "      <td>1671</td>\n",
       "      <td>485</td>\n",
       "      <td>...</td>\n",
       "      <td>15000</td>\n",
       "      <td>397</td>\n",
       "      <td>1671</td>\n",
       "      <td>46</td>\n",
       "      <td>30000</td>\n",
       "      <td>241</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>硕士</th>\n",
       "      <td>69</td>\n",
       "      <td>44</td>\n",
       "      <td>数据分析师</td>\n",
       "      <td>12</td>\n",
       "      <td>69</td>\n",
       "      <td>42</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>8</td>\n",
       "      <td>69</td>\n",
       "      <td>48</td>\n",
       "      <td>...</td>\n",
       "      <td>15000</td>\n",
       "      <td>18</td>\n",
       "      <td>69</td>\n",
       "      <td>21</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>69.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>22500.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 68 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    职位名称                     公司地址                   发布时间         ...   最低薪资  \\\n",
       "   count unique    top freq count unique  top freq count unique  ...    top   \n",
       "学历                                                               ...          \n",
       "不限    94     71  数据分析师   15    94     57  金水区    8    94     67  ...   8000   \n",
       "大专   196    144  数据分析师   18   196     80  金水区   14   196    120  ...   4000   \n",
       "应届   190    113  数据分析师   29   190    105  天河区    8   190    109  ...   2000   \n",
       "本科  1671    764  数据分析师  427  1671    317  南山区  101  1671    485  ...  15000   \n",
       "硕士    69     44  数据分析师   12    69     42  海淀区    8    69     48  ...  15000   \n",
       "\n",
       "         最高薪资                       平均薪资                         \n",
       "   freq count unique    top freq   count unique      top   freq  \n",
       "学历                                                               \n",
       "不限   17    94     22  15000   12    94.0   31.0  11500.0    8.0  \n",
       "大专   35   196     21   8000   33   196.0   35.0   6000.0   20.0  \n",
       "应届   37   190     24   4000   30   190.0   34.0   4500.0   22.0  \n",
       "本科  397  1671     46  30000  241  1671.0   73.0  20000.0  175.0  \n",
       "硕士   18    69     21  30000   14    69.0   29.0  22500.0   12.0  \n",
       "\n",
       "[5 rows x 68 columns]"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(by='学历').describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [],
   "source": [
    "#根据薪资查找异常值\n",
    "def bool_out_scope(x, times=3):\n",
    "    x = pd.Series(x)\n",
    "    lb, ub = x.mean() + pd.Series([-1,1]) * times * x.std()\n",
    "    return (x> ub) | (x<lb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>高级数据分析专家</td>\n",
       "      <td>西北旺</td>\n",
       "      <td>17:53发布</td>\n",
       "      <td>45000-90000</td>\n",
       "      <td>45k-90k 经验5-10年 / 本科</td>\n",
       "      <td>BI分析 数据分析 商业分析</td>\n",
       "      <td>“发展空间大，不加班”</td>\n",
       "      <td>硬件,数据服务 / 不需要融资 / 150-500人</td>\n",
       "      <td>圣达龙翔</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件,数据服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>45000</td>\n",
       "      <td>90000</td>\n",
       "      <td>67500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>数据科学家（资深：数据分析、建模）</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>14:53发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>Python 数据分析 数据建模</td>\n",
       "      <td>“大牛带队、硅谷风格、双休”</td>\n",
       "      <td>工具 / B轮 / 150-500人</td>\n",
       "      <td>石墨文档</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>工具</td>\n",
       "      <td>B轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>高级数据分析经理（HR领域）</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>10:42发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>教育 互联网 数据分析 ROI 驾驶舱 数字化</td>\n",
       "      <td>“在线教育赛道，头部企业，空间，可配股”</td>\n",
       "      <td>移动互联网,教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,教育</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>高级数据分析师</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-70000</td>\n",
       "      <td>40k-70k 经验3-5年 / 本科</td>\n",
       "      <td>数据仓库 数仓建模</td>\n",
       "      <td>“待遇详谈”</td>\n",
       "      <td>金融,软件开发 / 未融资 / 500-2000人</td>\n",
       "      <td>兆扬投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,软件开发</td>\n",
       "      <td>未融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>40000</td>\n",
       "      <td>70000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>西北旺</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业</td>\n",
       "      <td>“行业大牛，完善的福利，晋升空间”</td>\n",
       "      <td>金融 / 不需要融资 / 2000人以上</td>\n",
       "      <td>火币网</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>35000-70000</td>\n",
       "      <td>35k-70k 经验5-10年 / 本科</td>\n",
       "      <td>移动互联网 教育 商业分析 行业研究 用户增长</td>\n",
       "      <td>“有上升空间”</td>\n",
       "      <td>企业服务 / 未融资 / 150-500人</td>\n",
       "      <td>睿展（上海）人力资源有限公司</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务</td>\n",
       "      <td>未融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>35000</td>\n",
       "      <td>70000</td>\n",
       "      <td>52500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>太平桥</td>\n",
       "      <td>2020-12-17</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验3-5年 / 本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>“发展空间大，福利好”</td>\n",
       "      <td>金融,区块链 / 不需要融资 / 150-500人</td>\n",
       "      <td>中国人民银行金融科技研究院</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,区块链</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>数据分析负责人</td>\n",
       "      <td>新港</td>\n",
       "      <td>2020-12-16</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>电商 大数据 数仓建模 Hive Flink MySQL</td>\n",
       "      <td>“弹性工作时间 员工子女补充医疗”</td>\n",
       "      <td>汽车丨出行 / 未融资 / 150-500人</td>\n",
       "      <td>如祺出行</td>\n",
       "      <td>guanzghou</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>汽车丨出行</td>\n",
       "      <td>未融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777</th>\n",
       "      <td>商业数据分析师</td>\n",
       "      <td>荔湾区</td>\n",
       "      <td>2020-12-22</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验3-5年 / 本科</td>\n",
       "      <td>SQL 数据分析 商业 数据库</td>\n",
       "      <td>“发展空间大 领导nice”</td>\n",
       "      <td>企业服务 / 未融资 / 15-50人</td>\n",
       "      <td>优礼科技</td>\n",
       "      <td>guanzghou</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务</td>\n",
       "      <td>未融资</td>\n",
       "      <td>15-50人</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>软件产品及数据分析服务销售总监</td>\n",
       "      <td>长河</td>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验10年以上 / 本科</td>\n",
       "      <td>大数据 广告营销 销售 BD 市场拓展 电话销售</td>\n",
       "      <td>“就业+创业，原始股，弹性工作”</td>\n",
       "      <td>移动互联网,数据服务 / 未融资 / 150-500人</td>\n",
       "      <td>银基安全</td>\n",
       "      <td>hangzhou</td>\n",
       "      <td>经验10年以上</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,数据服务</td>\n",
       "      <td>未融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>数据分析产品研发负责人-To B</td>\n",
       "      <td>鼓楼区</td>\n",
       "      <td>04:24发布</td>\n",
       "      <td>50000-100000</td>\n",
       "      <td>50k-100k 经验不限 / 本科</td>\n",
       "      <td>数据挖掘</td>\n",
       "      <td>“下午茶,健身瑜伽,股票期权,团队氛围好”</td>\n",
       "      <td>文娱丨内容 / D轮及以上 / 2000人以上</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>nanjing</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>本科</td>\n",
       "      <td>文娱丨内容</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>50000</td>\n",
       "      <td>100000</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1616</th>\n",
       "      <td>高级数据分析经理</td>\n",
       "      <td>中山公园</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>50000-100000</td>\n",
       "      <td>50k-100k 经验10年以上 / 本科</td>\n",
       "      <td>电商 互联网 高科技 SQL Data Warehouse</td>\n",
       "      <td>“团队管理，全球视野，大平台，海量数据”</td>\n",
       "      <td>移动互联网,电商 / 上市公司 / 2000人以上</td>\n",
       "      <td>亚马逊（中国）</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验10年以上</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,电商</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>50000</td>\n",
       "      <td>100000</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>资深大数据分析师</td>\n",
       "      <td>洋泾</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“平台大，福利好，年终奖”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>平安金服</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1805</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>南山区</td>\n",
       "      <td>04:08发布</td>\n",
       "      <td>35000-70000</td>\n",
       "      <td>35k-70k 经验不限 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“扁平管理，过亿用户，职业大牛”</td>\n",
       "      <td>文娱丨内容 / D轮及以上 / 2000人以上</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>本科</td>\n",
       "      <td>文娱丨内容</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>35000</td>\n",
       "      <td>70000</td>\n",
       "      <td>52500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>后海</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验5-10年 / 本科</td>\n",
       "      <td>BI SQL 商业 增长黑客</td>\n",
       "      <td>“团队简单高效，上升空间大”</td>\n",
       "      <td>硬件 / 不需要融资 / 2000人以上</td>\n",
       "      <td>OPPO</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>福田区</td>\n",
       "      <td>2020-12-17</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验3-5年 / 本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>“发展空间大，福利好”</td>\n",
       "      <td>金融,区块链 / 不需要融资 / 150-500人</td>\n",
       "      <td>中国人民银行金融科技研究院</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,区块链</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1923</th>\n",
       "      <td>SJZ-大数据分析专家</td>\n",
       "      <td>大冲</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验5-10年 / 硕士</td>\n",
       "      <td>MySQL</td>\n",
       "      <td>“急招”</td>\n",
       "      <td>软件开发,数据服务 / 不需要融资 / 2000人以上</td>\n",
       "      <td>顺丰科技有限公司</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>硕士</td>\n",
       "      <td>软件开发,数据服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>产品数据分析师(007758)</td>\n",
       "      <td>福田区</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>40000-70000</td>\n",
       "      <td>40k-70k 经验5-10年 / 本科</td>\n",
       "      <td>大数据 产品运营</td>\n",
       "      <td>“绩效奖金”</td>\n",
       "      <td>硬件 / 不需要融资 / 2000人以上</td>\n",
       "      <td>vivo</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>70000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>数据分析总监</td>\n",
       "      <td>大冲</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>60000-90000</td>\n",
       "      <td>60k-90k 经验5-10年 / 本科</td>\n",
       "      <td>云计算 大数据 Hadoop Python R语言 机器学习</td>\n",
       "      <td>“股票期权、扁平化管理、平台大”</td>\n",
       "      <td>移动互联网,企业服务 / 不需要融资 / 500-2000人</td>\n",
       "      <td>慧择信息集团</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,企业服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>60000</td>\n",
       "      <td>90000</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   职位名称  公司地址        发布时间          薪资待遇  \\\n",
       "138            高级数据分析专家   西北旺     17:53发布   45000-90000   \n",
       "163   数据科学家（资深：数据分析、建模）   朝阳区     14:53发布   40000-60000   \n",
       "201      高级数据分析经理（HR领域）   海淀区     10:42发布   40000-60000   \n",
       "273             高级数据分析师   海淀区       3天前发布   40000-70000   \n",
       "317              数据分析专家   西北旺  2020-12-14   40000-60000   \n",
       "377              数据分析专家   海淀区  2020-12-15   35000-70000   \n",
       "388               数据分析师   太平桥  2020-12-17   40000-80000   \n",
       "758             数据分析负责人    新港  2020-12-16   40000-60000   \n",
       "777             商业数据分析师   荔湾区  2020-12-22   40000-60000   \n",
       "947     软件产品及数据分析服务销售总监    长河  2020-12-04   40000-80000   \n",
       "982    数据分析产品研发负责人-To B   鼓楼区     04:24发布  50000-100000   \n",
       "1616           高级数据分析经理  中山公园  2020-11-26  50000-100000   \n",
       "1685           资深大数据分析师    洋泾       3天前发布   40000-60000   \n",
       "1805             数据分析专家   南山区     04:08发布   35000-70000   \n",
       "1861              数据分析师    后海       3天前发布   40000-80000   \n",
       "1909              数据分析师   福田区  2020-12-17   40000-80000   \n",
       "1923        SJZ-大数据分析专家    大冲  2020-12-23   40000-80000   \n",
       "1969    产品数据分析师(007758)   福田区  2020-12-14   40000-70000   \n",
       "1994             数据分析总监    大冲  2020-12-21   60000-90000   \n",
       "\n",
       "                       岗位要求                            岗位标签  \\\n",
       "138    45k-90k 经验5-10年 / 本科                  BI分析 数据分析 商业分析   \n",
       "163    40k-60k 经验5-10年 / 本科                Python 数据分析 数据建模   \n",
       "201    40k-60k 经验5-10年 / 本科         教育 互联网 数据分析 ROI 驾驶舱 数字化   \n",
       "273     40k-70k 经验3-5年 / 本科                       数据仓库 数仓建模   \n",
       "317    40k-60k 经验5-10年 / 本科                    数据分析 数据运营 商业   \n",
       "377    35k-70k 经验5-10年 / 本科         移动互联网 教育 商业分析 行业研究 用户增长   \n",
       "388     40k-80k 经验3-5年 / 本科                              金融   \n",
       "758    40k-60k 经验5-10年 / 本科    电商 大数据 数仓建模 Hive Flink MySQL   \n",
       "777     40k-60k 经验3-5年 / 本科                 SQL 数据分析 商业 数据库   \n",
       "947    40k-80k 经验10年以上 / 本科        大数据 广告营销 销售 BD 市场拓展 电话销售   \n",
       "982      50k-100k 经验不限 / 本科                            数据挖掘   \n",
       "1616  50k-100k 经验10年以上 / 本科   电商 互联网 高科技 SQL Data Warehouse   \n",
       "1685   40k-60k 经验5-10年 / 本科                            数据分析   \n",
       "1805      35k-70k 经验不限 / 本科                            数据分析   \n",
       "1861   40k-80k 经验5-10年 / 本科                  BI SQL 商业 增长黑客   \n",
       "1909    40k-80k 经验3-5年 / 本科                              金融   \n",
       "1923   40k-80k 经验5-10年 / 硕士                           MySQL   \n",
       "1969   40k-70k 经验5-10年 / 本科                        大数据 产品运营   \n",
       "1994   60k-90k 经验5-10年 / 本科  云计算 大数据 Hadoop Python R语言 机器学习   \n",
       "\n",
       "                       公司福利                            所属行业            公司名称  \\\n",
       "138             “发展空间大，不加班”      硬件,数据服务 / 不需要融资 / 150-500人            圣达龙翔   \n",
       "163          “大牛带队、硅谷风格、双休”              工具 / B轮 / 150-500人            石墨文档   \n",
       "201    “在线教育赛道，头部企业，空间，可配股”       移动互联网,教育 / 上市公司 / 2000人以上             跟谁学   \n",
       "273                  “待遇详谈”       金融,软件开发 / 未融资 / 500-2000人            兆扬投资   \n",
       "317       “行业大牛，完善的福利，晋升空间”            金融 / 不需要融资 / 2000人以上             火币网   \n",
       "377                 “有上升空间”           企业服务 / 未融资 / 150-500人  睿展（上海）人力资源有限公司   \n",
       "388             “发展空间大，福利好”       金融,区块链 / 不需要融资 / 150-500人   中国人民银行金融科技研究院   \n",
       "758       “弹性工作时间 员工子女补充医疗”          汽车丨出行 / 未融资 / 150-500人            如祺出行   \n",
       "777          “发展空间大 领导nice”             企业服务 / 未融资 / 15-50人            优礼科技   \n",
       "947        “就业+创业，原始股，弹性工作”     移动互联网,数据服务 / 未融资 / 150-500人            银基安全   \n",
       "982   “下午茶,健身瑜伽,股票期权,团队氛围好”         文娱丨内容 / D轮及以上 / 2000人以上            字节跳动   \n",
       "1616   “团队管理，全球视野，大平台，海量数据”       移动互联网,电商 / 上市公司 / 2000人以上         亚马逊（中国）   \n",
       "1685          “平台大，福利好，年终奖”             金融 / 上市公司 / 2000人以上            平安金服   \n",
       "1805       “扁平管理，过亿用户，职业大牛”         文娱丨内容 / D轮及以上 / 2000人以上            字节跳动   \n",
       "1861         “团队简单高效，上升空间大”            硬件 / 不需要融资 / 2000人以上            OPPO   \n",
       "1909            “发展空间大，福利好”       金融,区块链 / 不需要融资 / 150-500人   中国人民银行金融科技研究院   \n",
       "1923                   “急招”     软件开发,数据服务 / 不需要融资 / 2000人以上        顺丰科技有限公司   \n",
       "1969                 “绩效奖金”            硬件 / 不需要融资 / 2000人以上            vivo   \n",
       "1994       “股票期权、扁平化管理、平台大”  移动互联网,企业服务 / 不需要融资 / 500-2000人          慧择信息集团   \n",
       "\n",
       "             城市     经验要求  学历          行业     融资         人数   最低薪资    最高薪资  \\\n",
       "138      beijin  经验5-10年  本科     硬件,数据服务  不需要融资   150-500人  45000   90000   \n",
       "163      beijin  经验5-10年  本科          工具     B轮   150-500人  40000   60000   \n",
       "201      beijin  经验5-10年  本科    移动互联网,教育   上市公司    2000人以上  40000   60000   \n",
       "273      beijin   经验3-5年  本科     金融,软件开发    未融资  500-2000人  40000   70000   \n",
       "317      beijin  经验5-10年  本科          金融  不需要融资    2000人以上  40000   60000   \n",
       "377      beijin  经验5-10年  本科        企业服务    未融资   150-500人  35000   70000   \n",
       "388      beijin   经验3-5年  本科      金融,区块链  不需要融资   150-500人  40000   80000   \n",
       "758   guanzghou  经验5-10年  本科       汽车丨出行    未融资   150-500人  40000   60000   \n",
       "777   guanzghou   经验3-5年  本科        企业服务    未融资     15-50人  40000   60000   \n",
       "947    hangzhou  经验10年以上  本科  移动互联网,数据服务    未融资   150-500人  40000   80000   \n",
       "982     nanjing     经验不限  本科       文娱丨内容  D轮及以上    2000人以上  50000  100000   \n",
       "1616   shanghai  经验10年以上  本科    移动互联网,电商   上市公司    2000人以上  50000  100000   \n",
       "1685   shanghai  经验5-10年  本科          金融   上市公司    2000人以上  40000   60000   \n",
       "1805   shenzhen     经验不限  本科       文娱丨内容  D轮及以上    2000人以上  35000   70000   \n",
       "1861   shenzhen  经验5-10年  本科          硬件  不需要融资    2000人以上  40000   80000   \n",
       "1909   shenzhen   经验3-5年  本科      金融,区块链  不需要融资   150-500人  40000   80000   \n",
       "1923   shenzhen  经验5-10年  硕士   软件开发,数据服务  不需要融资    2000人以上  40000   80000   \n",
       "1969   shenzhen  经验5-10年  本科          硬件  不需要融资    2000人以上  40000   70000   \n",
       "1994   shenzhen  经验5-10年  本科  移动互联网,企业服务  不需要融资  500-2000人  60000   90000   \n",
       "\n",
       "       平均薪资  \n",
       "138   67500  \n",
       "163   50000  \n",
       "201   50000  \n",
       "273   55000  \n",
       "317   50000  \n",
       "377   52500  \n",
       "388   60000  \n",
       "758   50000  \n",
       "777   50000  \n",
       "947   60000  \n",
       "982   75000  \n",
       "1616  75000  \n",
       "1685  50000  \n",
       "1805  52500  \n",
       "1861  60000  \n",
       "1909  60000  \n",
       "1923  60000  \n",
       "1969  55000  \n",
       "1994  75000  "
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[bool_out_scope(df.平均薪资)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>高级数据分析专家</td>\n",
       "      <td>西北旺</td>\n",
       "      <td>17:53发布</td>\n",
       "      <td>45000-90000</td>\n",
       "      <td>45k-90k 经验5-10年 / 本科</td>\n",
       "      <td>BI分析 数据分析 商业分析</td>\n",
       "      <td>“发展空间大，不加班”</td>\n",
       "      <td>硬件,数据服务 / 不需要融资 / 150-500人</td>\n",
       "      <td>圣达龙翔</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件,数据服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>45000</td>\n",
       "      <td>90000</td>\n",
       "      <td>67500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>数据科学家（资深：数据分析、建模）</td>\n",
       "      <td>朝阳区</td>\n",
       "      <td>14:53发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>Python 数据分析 数据建模</td>\n",
       "      <td>“大牛带队、硅谷风格、双休”</td>\n",
       "      <td>工具 / B轮 / 150-500人</td>\n",
       "      <td>石墨文档</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>工具</td>\n",
       "      <td>B轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>高级数据分析经理（HR领域）</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>10:42发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>教育 互联网 数据分析 ROI 驾驶舱 数字化</td>\n",
       "      <td>“在线教育赛道，头部企业，空间，可配股”</td>\n",
       "      <td>移动互联网,教育 / 上市公司 / 2000人以上</td>\n",
       "      <td>跟谁学</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,教育</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>高级数据分析师</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-70000</td>\n",
       "      <td>40k-70k 经验3-5年 / 本科</td>\n",
       "      <td>数据仓库 数仓建模</td>\n",
       "      <td>“待遇详谈”</td>\n",
       "      <td>金融,软件开发 / 未融资 / 500-2000人</td>\n",
       "      <td>兆扬投资</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,软件开发</td>\n",
       "      <td>未融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>40000</td>\n",
       "      <td>70000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>西北旺</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 数据运营 商业</td>\n",
       "      <td>“行业大牛，完善的福利，晋升空间”</td>\n",
       "      <td>金融 / 不需要融资 / 2000人以上</td>\n",
       "      <td>火币网</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>海淀区</td>\n",
       "      <td>2020-12-15</td>\n",
       "      <td>35000-70000</td>\n",
       "      <td>35k-70k 经验5-10年 / 本科</td>\n",
       "      <td>移动互联网 教育 商业分析 行业研究 用户增长</td>\n",
       "      <td>“有上升空间”</td>\n",
       "      <td>企业服务 / 未融资 / 150-500人</td>\n",
       "      <td>睿展（上海）人力资源有限公司</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务</td>\n",
       "      <td>未融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>35000</td>\n",
       "      <td>70000</td>\n",
       "      <td>52500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>太平桥</td>\n",
       "      <td>2020-12-17</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验3-5年 / 本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>“发展空间大，福利好”</td>\n",
       "      <td>金融,区块链 / 不需要融资 / 150-500人</td>\n",
       "      <td>中国人民银行金融科技研究院</td>\n",
       "      <td>beijin</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,区块链</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1616</th>\n",
       "      <td>高级数据分析经理</td>\n",
       "      <td>中山公园</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>50000-100000</td>\n",
       "      <td>50k-100k 经验10年以上 / 本科</td>\n",
       "      <td>电商 互联网 高科技 SQL Data Warehouse</td>\n",
       "      <td>“团队管理，全球视野，大平台，海量数据”</td>\n",
       "      <td>移动互联网,电商 / 上市公司 / 2000人以上</td>\n",
       "      <td>亚马逊（中国）</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验10年以上</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,电商</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>50000</td>\n",
       "      <td>100000</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>资深大数据分析师</td>\n",
       "      <td>洋泾</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-60000</td>\n",
       "      <td>40k-60k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“平台大，福利好，年终奖”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>平安金服</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>60000</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1805</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>南山区</td>\n",
       "      <td>04:08发布</td>\n",
       "      <td>35000-70000</td>\n",
       "      <td>35k-70k 经验不限 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“扁平管理，过亿用户，职业大牛”</td>\n",
       "      <td>文娱丨内容 / D轮及以上 / 2000人以上</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>本科</td>\n",
       "      <td>文娱丨内容</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>35000</td>\n",
       "      <td>70000</td>\n",
       "      <td>52500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>后海</td>\n",
       "      <td>3天前发布</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验5-10年 / 本科</td>\n",
       "      <td>BI SQL 商业 增长黑客</td>\n",
       "      <td>“团队简单高效，上升空间大”</td>\n",
       "      <td>硬件 / 不需要融资 / 2000人以上</td>\n",
       "      <td>OPPO</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>福田区</td>\n",
       "      <td>2020-12-17</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验3-5年 / 本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>“发展空间大，福利好”</td>\n",
       "      <td>金融,区块链 / 不需要融资 / 150-500人</td>\n",
       "      <td>中国人民银行金融科技研究院</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融,区块链</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1923</th>\n",
       "      <td>SJZ-大数据分析专家</td>\n",
       "      <td>大冲</td>\n",
       "      <td>2020-12-23</td>\n",
       "      <td>40000-80000</td>\n",
       "      <td>40k-80k 经验5-10年 / 硕士</td>\n",
       "      <td>MySQL</td>\n",
       "      <td>“急招”</td>\n",
       "      <td>软件开发,数据服务 / 不需要融资 / 2000人以上</td>\n",
       "      <td>顺丰科技有限公司</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>硕士</td>\n",
       "      <td>软件开发,数据服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>80000</td>\n",
       "      <td>60000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>产品数据分析师(007758)</td>\n",
       "      <td>福田区</td>\n",
       "      <td>2020-12-14</td>\n",
       "      <td>40000-70000</td>\n",
       "      <td>40k-70k 经验5-10年 / 本科</td>\n",
       "      <td>大数据 产品运营</td>\n",
       "      <td>“绩效奖金”</td>\n",
       "      <td>硬件 / 不需要融资 / 2000人以上</td>\n",
       "      <td>vivo</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>硬件</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>40000</td>\n",
       "      <td>70000</td>\n",
       "      <td>55000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>数据分析总监</td>\n",
       "      <td>大冲</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>60000-90000</td>\n",
       "      <td>60k-90k 经验5-10年 / 本科</td>\n",
       "      <td>云计算 大数据 Hadoop Python R语言 机器学习</td>\n",
       "      <td>“股票期权、扁平化管理、平台大”</td>\n",
       "      <td>移动互联网,企业服务 / 不需要融资 / 500-2000人</td>\n",
       "      <td>慧择信息集团</td>\n",
       "      <td>shenzhen</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,企业服务</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>60000</td>\n",
       "      <td>90000</td>\n",
       "      <td>75000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   职位名称  公司地址        发布时间          薪资待遇  \\\n",
       "138            高级数据分析专家   西北旺     17:53发布   45000-90000   \n",
       "163   数据科学家（资深：数据分析、建模）   朝阳区     14:53发布   40000-60000   \n",
       "201      高级数据分析经理（HR领域）   海淀区     10:42发布   40000-60000   \n",
       "273             高级数据分析师   海淀区       3天前发布   40000-70000   \n",
       "317              数据分析专家   西北旺  2020-12-14   40000-60000   \n",
       "377              数据分析专家   海淀区  2020-12-15   35000-70000   \n",
       "388               数据分析师   太平桥  2020-12-17   40000-80000   \n",
       "1616           高级数据分析经理  中山公园  2020-11-26  50000-100000   \n",
       "1685           资深大数据分析师    洋泾       3天前发布   40000-60000   \n",
       "1805             数据分析专家   南山区     04:08发布   35000-70000   \n",
       "1861              数据分析师    后海       3天前发布   40000-80000   \n",
       "1909              数据分析师   福田区  2020-12-17   40000-80000   \n",
       "1923        SJZ-大数据分析专家    大冲  2020-12-23   40000-80000   \n",
       "1969    产品数据分析师(007758)   福田区  2020-12-14   40000-70000   \n",
       "1994             数据分析总监    大冲  2020-12-21   60000-90000   \n",
       "\n",
       "                       岗位要求                            岗位标签  \\\n",
       "138    45k-90k 经验5-10年 / 本科                  BI分析 数据分析 商业分析   \n",
       "163    40k-60k 经验5-10年 / 本科                Python 数据分析 数据建模   \n",
       "201    40k-60k 经验5-10年 / 本科         教育 互联网 数据分析 ROI 驾驶舱 数字化   \n",
       "273     40k-70k 经验3-5年 / 本科                       数据仓库 数仓建模   \n",
       "317    40k-60k 经验5-10年 / 本科                    数据分析 数据运营 商业   \n",
       "377    35k-70k 经验5-10年 / 本科         移动互联网 教育 商业分析 行业研究 用户增长   \n",
       "388     40k-80k 经验3-5年 / 本科                              金融   \n",
       "1616  50k-100k 经验10年以上 / 本科   电商 互联网 高科技 SQL Data Warehouse   \n",
       "1685   40k-60k 经验5-10年 / 本科                            数据分析   \n",
       "1805      35k-70k 经验不限 / 本科                            数据分析   \n",
       "1861   40k-80k 经验5-10年 / 本科                  BI SQL 商业 增长黑客   \n",
       "1909    40k-80k 经验3-5年 / 本科                              金融   \n",
       "1923   40k-80k 经验5-10年 / 硕士                           MySQL   \n",
       "1969   40k-70k 经验5-10年 / 本科                        大数据 产品运营   \n",
       "1994   60k-90k 经验5-10年 / 本科  云计算 大数据 Hadoop Python R语言 机器学习   \n",
       "\n",
       "                      公司福利                            所属行业            公司名称  \\\n",
       "138            “发展空间大，不加班”      硬件,数据服务 / 不需要融资 / 150-500人            圣达龙翔   \n",
       "163         “大牛带队、硅谷风格、双休”              工具 / B轮 / 150-500人            石墨文档   \n",
       "201   “在线教育赛道，头部企业，空间，可配股”       移动互联网,教育 / 上市公司 / 2000人以上             跟谁学   \n",
       "273                 “待遇详谈”       金融,软件开发 / 未融资 / 500-2000人            兆扬投资   \n",
       "317      “行业大牛，完善的福利，晋升空间”            金融 / 不需要融资 / 2000人以上             火币网   \n",
       "377                “有上升空间”           企业服务 / 未融资 / 150-500人  睿展（上海）人力资源有限公司   \n",
       "388            “发展空间大，福利好”       金融,区块链 / 不需要融资 / 150-500人   中国人民银行金融科技研究院   \n",
       "1616  “团队管理，全球视野，大平台，海量数据”       移动互联网,电商 / 上市公司 / 2000人以上         亚马逊（中国）   \n",
       "1685         “平台大，福利好，年终奖”             金融 / 上市公司 / 2000人以上            平安金服   \n",
       "1805      “扁平管理，过亿用户，职业大牛”         文娱丨内容 / D轮及以上 / 2000人以上            字节跳动   \n",
       "1861        “团队简单高效，上升空间大”            硬件 / 不需要融资 / 2000人以上            OPPO   \n",
       "1909           “发展空间大，福利好”       金融,区块链 / 不需要融资 / 150-500人   中国人民银行金融科技研究院   \n",
       "1923                  “急招”     软件开发,数据服务 / 不需要融资 / 2000人以上        顺丰科技有限公司   \n",
       "1969                “绩效奖金”            硬件 / 不需要融资 / 2000人以上            vivo   \n",
       "1994      “股票期权、扁平化管理、平台大”  移动互联网,企业服务 / 不需要融资 / 500-2000人          慧择信息集团   \n",
       "\n",
       "            城市     经验要求  学历          行业     融资         人数   最低薪资    最高薪资  \\\n",
       "138     beijin  经验5-10年  本科     硬件,数据服务  不需要融资   150-500人  45000   90000   \n",
       "163     beijin  经验5-10年  本科          工具     B轮   150-500人  40000   60000   \n",
       "201     beijin  经验5-10年  本科    移动互联网,教育   上市公司    2000人以上  40000   60000   \n",
       "273     beijin   经验3-5年  本科     金融,软件开发    未融资  500-2000人  40000   70000   \n",
       "317     beijin  经验5-10年  本科          金融  不需要融资    2000人以上  40000   60000   \n",
       "377     beijin  经验5-10年  本科        企业服务    未融资   150-500人  35000   70000   \n",
       "388     beijin   经验3-5年  本科      金融,区块链  不需要融资   150-500人  40000   80000   \n",
       "1616  shanghai  经验10年以上  本科    移动互联网,电商   上市公司    2000人以上  50000  100000   \n",
       "1685  shanghai  经验5-10年  本科          金融   上市公司    2000人以上  40000   60000   \n",
       "1805  shenzhen     经验不限  本科       文娱丨内容  D轮及以上    2000人以上  35000   70000   \n",
       "1861  shenzhen  经验5-10年  本科          硬件  不需要融资    2000人以上  40000   80000   \n",
       "1909  shenzhen   经验3-5年  本科      金融,区块链  不需要融资   150-500人  40000   80000   \n",
       "1923  shenzhen  经验5-10年  硕士   软件开发,数据服务  不需要融资    2000人以上  40000   80000   \n",
       "1969  shenzhen  经验5-10年  本科          硬件  不需要融资    2000人以上  40000   70000   \n",
       "1994  shenzhen  经验5-10年  本科  移动互联网,企业服务  不需要融资  500-2000人  60000   90000   \n",
       "\n",
       "       平均薪资  \n",
       "138   67500  \n",
       "163   50000  \n",
       "201   50000  \n",
       "273   55000  \n",
       "317   50000  \n",
       "377   52500  \n",
       "388   60000  \n",
       "1616  75000  \n",
       "1685  50000  \n",
       "1805  52500  \n",
       "1861  60000  \n",
       "1909  60000  \n",
       "1923  60000  \n",
       "1969  55000  \n",
       "1994  75000  "
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[bool_out_scope(df.平均薪资) & df.城市.isin(['beijin','shanghai','shenzhen'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>北蔡</td>\n",
       "      <td>19:56发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>金融 数据分析</td>\n",
       "      <td>“氛围好,商业医疗险”</td>\n",
       "      <td>金融 / C轮 / 150-500人</td>\n",
       "      <td>萨摩耶数科</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1270</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>华漕</td>\n",
       "      <td>17:02发布</td>\n",
       "      <td>12000-18000</td>\n",
       "      <td>12k-18k 经验3-5年 / 本科</td>\n",
       "      <td>教育 企业服务 数据库 BI SQL 数据分析</td>\n",
       "      <td>“上市公司、创新氛围强、团队凝聚力、发展空间大”</td>\n",
       "      <td>教育 / 不需要融资 / 500-2000人</td>\n",
       "      <td>行动教育</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>教育</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>12000</td>\n",
       "      <td>18000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1271</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>徐家汇</td>\n",
       "      <td>17:41发布</td>\n",
       "      <td>12000-20000</td>\n",
       "      <td>12k-20k 经验不限 / 本科</td>\n",
       "      <td>大数据 新零售</td>\n",
       "      <td>“福利待遇优厚，发展空间大，团队氛围好”</td>\n",
       "      <td>企业服务,数据服务 / 未融资 / 50-150人</td>\n",
       "      <td>久谦咨询</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>未融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>12000</td>\n",
       "      <td>20000</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>17:01发布</td>\n",
       "      <td>10000-18000</td>\n",
       "      <td>10k-18k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“交通便利 待遇良好 晋升机会 技术大牛”</td>\n",
       "      <td>移动互联网 / A轮 / 50-150人</td>\n",
       "      <td>上海众调科技</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>A轮</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>18000</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1273</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>六里</td>\n",
       "      <td>18:02发布</td>\n",
       "      <td>10000-16000</td>\n",
       "      <td>10k-16k 经验1-3年 / 本科</td>\n",
       "      <td>电商 数据分析</td>\n",
       "      <td>“发展前景好 团队氛围佳 注重个人成长”</td>\n",
       "      <td>软件开发 / 未融资 / 150-500人</td>\n",
       "      <td>杉欣集团</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>软件开发</td>\n",
       "      <td>未融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>16000</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1713</th>\n",
       "      <td>【21届校招】质量数据分析专员/上海(J13720)</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>15000-20000</td>\n",
       "      <td>15k-20k 经验在校/应届 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“0-12个月年终奖，一线互联网公司”</td>\n",
       "      <td>移动互联网,硬件 / D轮及以上 / 2000人以上</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>移动互联网,硬件</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>20000</td>\n",
       "      <td>17500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>EI8467-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>13000-26000</td>\n",
       "      <td>13k-26k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析 业务理解</td>\n",
       "      <td>“发展前景,晋升机会,能力发挥”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>13000</td>\n",
       "      <td>26000</td>\n",
       "      <td>19500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>游戏数据分析师</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验1-3年 / 本科</td>\n",
       "      <td>数据分析 SQL/Hive 数据挖掘 算法</td>\n",
       "      <td>“福利待遇好，晋升空间大”</td>\n",
       "      <td>游戏 / 不需要融资 / 500-2000人</td>\n",
       "      <td>沐瞳游戏</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>游戏</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>500-2000人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>数据分析专家</td>\n",
       "      <td>漕河泾</td>\n",
       "      <td>2020-07-25</td>\n",
       "      <td>20000-40000</td>\n",
       "      <td>20k-40k 经验3-5年 / 本科</td>\n",
       "      <td>企业服务 机器学习 创业 数据挖掘</td>\n",
       "      <td>“数据科学，产品创新孵化”</td>\n",
       "      <td>企业服务,数据服务 / B轮 / 150-500人</td>\n",
       "      <td>GrowingIO</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>企业服务,数据服务</td>\n",
       "      <td>B轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>20000</td>\n",
       "      <td>40000</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>JA5738-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>互联网</td>\n",
       "      <td>“上市公司,五险一金”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>449 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            职位名称 公司地址        发布时间         薪资待遇  \\\n",
       "1269                       数据分析师   北蔡     19:56发布  10000-20000   \n",
       "1270                       数据分析师   华漕     17:02发布  12000-18000   \n",
       "1271                       数据分析师  徐家汇     17:41发布  12000-20000   \n",
       "1272                       数据分析师  杨浦区     17:01发布  10000-18000   \n",
       "1273                       数据分析师   六里     18:02发布  10000-16000   \n",
       "...                          ...  ...         ...          ...   \n",
       "1713  【21届校招】质量数据分析专员/上海(J13720)  闵行区  2020-12-21  15000-20000   \n",
       "1714              EI8467-资深数据分析师  杨浦区  2020-12-09  13000-26000   \n",
       "1715                     游戏数据分析师  闵行区  2020-12-18  15000-25000   \n",
       "1716                      数据分析专家  漕河泾  2020-07-25  20000-40000   \n",
       "1717              JA5738-资深数据分析师  杨浦区  2020-12-18  15000-30000   \n",
       "\n",
       "                      岗位要求                     岗位标签                      公司福利  \\\n",
       "1269   10k-20k 经验1-3年 / 本科                  金融 数据分析               “氛围好,商业医疗险”   \n",
       "1270   12k-18k 经验3-5年 / 本科  教育 企业服务 数据库 BI SQL 数据分析  “上市公司、创新氛围强、团队凝聚力、发展空间大”   \n",
       "1271     12k-20k 经验不限 / 本科                  大数据 新零售      “福利待遇优厚，发展空间大，团队氛围好”   \n",
       "1272   10k-18k 经验3-5年 / 本科                     数据分析     “交通便利 待遇良好 晋升机会 技术大牛”   \n",
       "1273   10k-16k 经验1-3年 / 本科                  电商 数据分析      “发展前景好 团队氛围佳 注重个人成长”   \n",
       "...                    ...                      ...                       ...   \n",
       "1713  15k-20k 经验在校/应届 / 本科                     数据分析       “0-12个月年终奖，一线互联网公司”   \n",
       "1714   13k-26k 经验3-5年 / 本科                数据分析 业务理解          “发展前景,晋升机会,能力发挥”   \n",
       "1715   15k-25k 经验1-3年 / 本科    数据分析 SQL/Hive 数据挖掘 算法             “福利待遇好，晋升空间大”   \n",
       "1716   20k-40k 经验3-5年 / 本科        企业服务 机器学习 创业 数据挖掘             “数据科学，产品创新孵化”   \n",
       "1717   15k-30k 经验1-3年 / 本科                      互联网               “上市公司,五险一金”   \n",
       "\n",
       "                              所属行业       公司名称        城市    经验要求  学历  \\\n",
       "1269            金融 / C轮 / 150-500人      萨摩耶数科  shanghai  经验1-3年  本科   \n",
       "1270        教育 / 不需要融资 / 500-2000人       行动教育  shanghai  经验3-5年  本科   \n",
       "1271     企业服务,数据服务 / 未融资 / 50-150人       久谦咨询  shanghai    经验不限  本科   \n",
       "1272          移动互联网 / A轮 / 50-150人     上海众调科技  shanghai  经验3-5年  本科   \n",
       "1273         软件开发 / 未融资 / 150-500人       杉欣集团  shanghai  经验1-3年  本科   \n",
       "...                            ...        ...       ...     ...  ..   \n",
       "1713    移动互联网,硬件 / D轮及以上 / 2000人以上       哈啰出行  shanghai    经验在校  应届   \n",
       "1714  移动互联网,文娱丨内容 / 上市公司 / 2000人以上       哔哩哔哩  shanghai  经验3-5年  本科   \n",
       "1715        游戏 / 不需要融资 / 500-2000人       沐瞳游戏  shanghai  经验1-3年  本科   \n",
       "1716     企业服务,数据服务 / B轮 / 150-500人  GrowingIO  shanghai  经验3-5年  本科   \n",
       "1717  移动互联网,文娱丨内容 / 上市公司 / 2000人以上       哔哩哔哩  shanghai  经验1-3年  本科   \n",
       "\n",
       "               行业     融资         人数   最低薪资   最高薪资   平均薪资  \n",
       "1269           金融     C轮   150-500人  10000  20000  15000  \n",
       "1270           教育  不需要融资  500-2000人  12000  18000  15000  \n",
       "1271    企业服务,数据服务    未融资    50-150人  12000  20000  16000  \n",
       "1272        移动互联网     A轮    50-150人  10000  18000  14000  \n",
       "1273         软件开发    未融资   150-500人  10000  16000  13000  \n",
       "...           ...    ...        ...    ...    ...    ...  \n",
       "1713     移动互联网,硬件  D轮及以上    2000人以上  15000  20000  17500  \n",
       "1714  移动互联网,文娱丨内容   上市公司    2000人以上  13000  26000  19500  \n",
       "1715           游戏  不需要融资  500-2000人  15000  25000  20000  \n",
       "1716    企业服务,数据服务     B轮   150-500人  20000  40000  30000  \n",
       "1717  移动互联网,文娱丨内容   上市公司    2000人以上  15000  30000  22500  \n",
       "\n",
       "[449 rows x 18 columns]"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sh = df[df.城市 == 'shanghai'].copy()\n",
    "df_sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_sh.公司地址.value_counts(ascending=True).plot(kind='barh',\n",
    "                                             fontsize=15, figsize=(10,20))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_sh.行业.value_counts(ascending=True).plot(kind='barh',\n",
    "                                           fontsize=15, figsize=(10,20)) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "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>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>北蔡</td>\n",
       "      <td>19:56发布</td>\n",
       "      <td>10000-20000</td>\n",
       "      <td>10k-20k 经验1-3年 / 本科</td>\n",
       "      <td>金融 数据分析</td>\n",
       "      <td>“氛围好,商业医疗险”</td>\n",
       "      <td>金融 / C轮 / 150-500人</td>\n",
       "      <td>萨摩耶数科</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>C轮</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>10000</td>\n",
       "      <td>20000</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>17:01发布</td>\n",
       "      <td>10000-18000</td>\n",
       "      <td>10k-18k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“交通便利 待遇良好 晋升机会 技术大牛”</td>\n",
       "      <td>移动互联网 / A轮 / 50-150人</td>\n",
       "      <td>上海众调科技</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>A轮</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>10000</td>\n",
       "      <td>18000</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>金桥</td>\n",
       "      <td>15:43发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验5-10年 / 本科</td>\n",
       "      <td>数据分析 SQL 数据建模</td>\n",
       "      <td>“年终奖 带薪年假 交通补助 通讯津贴等”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 不需要融资 / 2000人以上</td>\n",
       "      <td>咪咕</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>16:04发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验1-3年 / 本科</td>\n",
       "      <td>社交 移动互联网 数据分析 SQL</td>\n",
       "      <td>“行业前景好,人性化管理,福利好”</td>\n",
       "      <td>移动互联网,社交 / 不需要融资 / 50-150人</td>\n",
       "      <td>么么直播</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,社交</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>50-150人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>张江</td>\n",
       "      <td>16:31发布</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验1-3年 / 本科</td>\n",
       "      <td>电商 竞品分析 数据分析</td>\n",
       "      <td>“年终奖金，五险一金，领导好，薪酬福利好”</td>\n",
       "      <td>移动互联网 / 不需要融资 / 150-500人</td>\n",
       "      <td>包图网</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网</td>\n",
       "      <td>不需要融资</td>\n",
       "      <td>150-500人</td>\n",
       "      <td>15000</td>\n",
       "      <td>25000</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1711</th>\n",
       "      <td>数据产品-数据分析师（财务方向）(J12418)</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>30000-40000</td>\n",
       "      <td>30k-40k 经验5-10年 / 不限</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“发展前景”</td>\n",
       "      <td>移动互联网,硬件 / D轮及以上 / 2000人以上</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验5-10年</td>\n",
       "      <td>不限</td>\n",
       "      <td>移动互联网,硬件</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>30000</td>\n",
       "      <td>40000</td>\n",
       "      <td>35000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1712</th>\n",
       "      <td>DJ3024-资深数据分析师(漫画)</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>20000-35000</td>\n",
       "      <td>20k-35k 经验3-5年 / 本科</td>\n",
       "      <td>互联网</td>\n",
       "      <td>“上市公司,五险一金”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>20000</td>\n",
       "      <td>35000</td>\n",
       "      <td>27500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1713</th>\n",
       "      <td>【21届校招】质量数据分析专员/上海(J13720)</td>\n",
       "      <td>闵行区</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>15000-20000</td>\n",
       "      <td>15k-20k 经验在校/应届 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“0-12个月年终奖，一线互联网公司”</td>\n",
       "      <td>移动互联网,硬件 / D轮及以上 / 2000人以上</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验在校</td>\n",
       "      <td>应届</td>\n",
       "      <td>移动互联网,硬件</td>\n",
       "      <td>D轮及以上</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>20000</td>\n",
       "      <td>17500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>EI8467-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-09</td>\n",
       "      <td>13000-26000</td>\n",
       "      <td>13k-26k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析 业务理解</td>\n",
       "      <td>“发展前景,晋升机会,能力发挥”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>13000</td>\n",
       "      <td>26000</td>\n",
       "      <td>19500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>JA5738-资深数据分析师</td>\n",
       "      <td>杨浦区</td>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>15000-30000</td>\n",
       "      <td>15k-30k 经验1-3年 / 本科</td>\n",
       "      <td>互联网</td>\n",
       "      <td>“上市公司,五险一金”</td>\n",
       "      <td>移动互联网,文娱丨内容 / 上市公司 / 2000人以上</td>\n",
       "      <td>哔哩哔哩</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验1-3年</td>\n",
       "      <td>本科</td>\n",
       "      <td>移动互联网,文娱丨内容</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>22500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>219 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            职位名称 公司地址        发布时间         薪资待遇  \\\n",
       "1269                       数据分析师   北蔡     19:56发布  10000-20000   \n",
       "1272                       数据分析师  杨浦区     17:01发布  10000-18000   \n",
       "1279                       数据分析师   金桥     15:43发布  15000-25000   \n",
       "1280                       数据分析师  闵行区     16:04发布  15000-25000   \n",
       "1282                       数据分析师   张江     16:31发布  15000-25000   \n",
       "...                          ...  ...         ...          ...   \n",
       "1711    数据产品-数据分析师（财务方向）(J12418)  闵行区  2020-12-21  30000-40000   \n",
       "1712          DJ3024-资深数据分析师(漫画)  杨浦区  2020-12-21  20000-35000   \n",
       "1713  【21届校招】质量数据分析专员/上海(J13720)  闵行区  2020-12-21  15000-20000   \n",
       "1714              EI8467-资深数据分析师  杨浦区  2020-12-09  13000-26000   \n",
       "1717              JA5738-资深数据分析师  杨浦区  2020-12-18  15000-30000   \n",
       "\n",
       "                      岗位要求               岗位标签                   公司福利  \\\n",
       "1269   10k-20k 经验1-3年 / 本科            金融 数据分析            “氛围好,商业医疗险”   \n",
       "1272   10k-18k 经验3-5年 / 本科               数据分析  “交通便利 待遇良好 晋升机会 技术大牛”   \n",
       "1279  15k-25k 经验5-10年 / 本科      数据分析 SQL 数据建模  “年终奖 带薪年假 交通补助 通讯津贴等”   \n",
       "1280   15k-25k 经验1-3年 / 本科  社交 移动互联网 数据分析 SQL      “行业前景好,人性化管理,福利好”   \n",
       "1282   15k-25k 经验1-3年 / 本科       电商 竞品分析 数据分析  “年终奖金，五险一金，领导好，薪酬福利好”   \n",
       "...                    ...                ...                    ...   \n",
       "1711  30k-40k 经验5-10年 / 不限               数据分析                 “发展前景”   \n",
       "1712   20k-35k 经验3-5年 / 本科                互联网            “上市公司,五险一金”   \n",
       "1713  15k-20k 经验在校/应届 / 本科               数据分析    “0-12个月年终奖，一线互联网公司”   \n",
       "1714   13k-26k 经验3-5年 / 本科          数据分析 业务理解       “发展前景,晋升机会,能力发挥”   \n",
       "1717   15k-30k 经验1-3年 / 本科                互联网            “上市公司,五险一金”   \n",
       "\n",
       "                               所属行业    公司名称        城市     经验要求  学历  \\\n",
       "1269             金融 / C轮 / 150-500人   萨摩耶数科  shanghai   经验1-3年  本科   \n",
       "1272           移动互联网 / A轮 / 50-150人  上海众调科技  shanghai   经验3-5年  本科   \n",
       "1279  移动互联网,文娱丨内容 / 不需要融资 / 2000人以上      咪咕  shanghai  经验5-10年  本科   \n",
       "1280     移动互联网,社交 / 不需要融资 / 50-150人    么么直播  shanghai   经验1-3年  本科   \n",
       "1282       移动互联网 / 不需要融资 / 150-500人     包图网  shanghai   经验1-3年  本科   \n",
       "...                             ...     ...       ...      ...  ..   \n",
       "1711     移动互联网,硬件 / D轮及以上 / 2000人以上    哈啰出行  shanghai  经验5-10年  不限   \n",
       "1712   移动互联网,文娱丨内容 / 上市公司 / 2000人以上    哔哩哔哩  shanghai   经验3-5年  本科   \n",
       "1713     移动互联网,硬件 / D轮及以上 / 2000人以上    哈啰出行  shanghai     经验在校  应届   \n",
       "1714   移动互联网,文娱丨内容 / 上市公司 / 2000人以上    哔哩哔哩  shanghai   经验3-5年  本科   \n",
       "1717   移动互联网,文娱丨内容 / 上市公司 / 2000人以上    哔哩哔哩  shanghai   经验1-3年  本科   \n",
       "\n",
       "               行业     融资        人数   最低薪资   最高薪资   平均薪资  \n",
       "1269           金融     C轮  150-500人  10000  20000  15000  \n",
       "1272        移动互联网     A轮   50-150人  10000  18000  14000  \n",
       "1279  移动互联网,文娱丨内容  不需要融资   2000人以上  15000  25000  20000  \n",
       "1280     移动互联网,社交  不需要融资   50-150人  15000  25000  20000  \n",
       "1282        移动互联网  不需要融资  150-500人  15000  25000  20000  \n",
       "...           ...    ...       ...    ...    ...    ...  \n",
       "1711     移动互联网,硬件  D轮及以上   2000人以上  30000  40000  35000  \n",
       "1712  移动互联网,文娱丨内容   上市公司   2000人以上  20000  35000  27500  \n",
       "1713     移动互联网,硬件  D轮及以上   2000人以上  15000  20000  17500  \n",
       "1714  移动互联网,文娱丨内容   上市公司   2000人以上  13000  26000  19500  \n",
       "1717  移动互联网,文娱丨内容   上市公司   2000人以上  15000  30000  22500  \n",
       "\n",
       "[219 rows x 18 columns]"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sh_net = df_sh[df_sh.行业.str.contains('互联网|金融')]\n",
    "df_sh_net"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>职位名称</th>\n",
       "      <th>公司地址</th>\n",
       "      <th>发布时间</th>\n",
       "      <th>薪资待遇</th>\n",
       "      <th>岗位要求</th>\n",
       "      <th>岗位标签</th>\n",
       "      <th>公司福利</th>\n",
       "      <th>所属行业</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>城市</th>\n",
       "      <th>经验要求</th>\n",
       "      <th>学历</th>\n",
       "      <th>行业</th>\n",
       "      <th>融资</th>\n",
       "      <th>人数</th>\n",
       "      <th>最低薪资</th>\n",
       "      <th>最高薪资</th>\n",
       "      <th>平均薪资</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219</td>\n",
       "      <td>219.0</td>\n",
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       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>119</td>\n",
       "      <td>55</td>\n",
       "      <td>99</td>\n",
       "      <td>66</td>\n",
       "      <td>118</td>\n",
       "      <td>177</td>\n",
       "      <td>195</td>\n",
       "      <td>98</td>\n",
       "      <td>130</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>数据分析师</td>\n",
       "      <td>浦东新区</td>\n",
       "      <td>2020-12-24</td>\n",
       "      <td>15000-25000</td>\n",
       "      <td>15k-25k 经验3-5年 / 本科</td>\n",
       "      <td>数据分析</td>\n",
       "      <td>“上市公司,五险一金”</td>\n",
       "      <td>金融 / 上市公司 / 2000人以上</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>shanghai</td>\n",
       "      <td>经验3-5年</td>\n",
       "      <td>本科</td>\n",
       "      <td>金融</td>\n",
       "      <td>上市公司</td>\n",
       "      <td>2000人以上</td>\n",
       "      <td>15000</td>\n",
       "      <td>30000</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>62</td>\n",
       "      <td>47</td>\n",
       "      <td>19</td>\n",
       "      <td>28</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "      <td>4</td>\n",
       "      <td>26</td>\n",
       "      <td>12</td>\n",
       "      <td>219</td>\n",
       "      <td>84</td>\n",
       "      <td>174</td>\n",
       "      <td>54</td>\n",
       "      <td>70</td>\n",
       "      <td>75</td>\n",
       "      <td>55</td>\n",
       "      <td>36</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         职位名称  公司地址        发布时间         薪资待遇                 岗位要求  岗位标签  \\\n",
       "count     219   219         219          219                  219   219   \n",
       "unique    119    55          99           66                  118   177   \n",
       "top     数据分析师  浦东新区  2020-12-24  15000-25000  15k-25k 经验3-5年 / 本科  数据分析   \n",
       "freq       62    47          19           28                   15    21   \n",
       "\n",
       "               公司福利                 所属行业  公司名称        城市    经验要求   学历   行业  \\\n",
       "count           219                  219   219       219     219  219  219   \n",
       "unique          195                   98   130         1       7    5   26   \n",
       "top     “上市公司,五险一金”  金融 / 上市公司 / 2000人以上  哈啰出行  shanghai  经验3-5年   本科   金融   \n",
       "freq              4                   26    12       219      84  174   54   \n",
       "\n",
       "          融资       人数   最低薪资   最高薪资     平均薪资  \n",
       "count    219      219    219    219    219.0  \n",
       "unique     8        6     24     30     49.0  \n",
       "top     上市公司  2000人以上  15000  30000  20000.0  \n",
       "freq      70       75     55     36     29.0  "
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sh_net.describe(percentiles=[0.001,0.25,0.5,0.75,0.999])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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