forbes_data_tidy_concatenate.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": "true"
   },
   "source": [
    "# Table of Contents\n",
    " <p><div class=\"lev1 toc-item\"><a href=\"#将数据进行初步整理\" data-toc-modified-id=\"将数据进行初步整理-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>将数据进行初步整理</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2007\" data-toc-modified-id=\"Year-2007-11\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Year 2007</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2008\" data-toc-modified-id=\"Year-2008-12\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>Year 2008</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2009\" data-toc-modified-id=\"Year-2009-13\"><span class=\"toc-item-num\">1.3&nbsp;&nbsp;</span>Year 2009</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2010\" data-toc-modified-id=\"Year-2010-14\"><span class=\"toc-item-num\">1.4&nbsp;&nbsp;</span>Year 2010</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2011\" data-toc-modified-id=\"Year-2011-15\"><span class=\"toc-item-num\">1.5&nbsp;&nbsp;</span>Year 2011</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2012\" data-toc-modified-id=\"Year-2012-16\"><span class=\"toc-item-num\">1.6&nbsp;&nbsp;</span>Year 2012</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2013\" data-toc-modified-id=\"Year-2013-17\"><span class=\"toc-item-num\">1.7&nbsp;&nbsp;</span>Year 2013</a></div><div class=\"lev3 toc-item\"><a href=\"#Data-Source-1\" data-toc-modified-id=\"Data-Source-1-171\"><span class=\"toc-item-num\">1.7.1&nbsp;&nbsp;</span>Data Source 1</a></div><div class=\"lev3 toc-item\"><a href=\"#Data-Source-2-补充数据\" data-toc-modified-id=\"Data-Source-2-补充数据-172\"><span class=\"toc-item-num\">1.7.2&nbsp;&nbsp;</span>Data Source 2 补充数据</a></div><div class=\"lev3 toc-item\"><a href=\"#Data-Source-3：-2013年使用excel数据源\" data-toc-modified-id=\"Data-Source-3：-2013年使用excel数据源-173\"><span class=\"toc-item-num\">1.7.3&nbsp;&nbsp;</span>Data Source 3： 2013年使用excel数据源</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2014\" data-toc-modified-id=\"Year-2014-18\"><span class=\"toc-item-num\">1.8&nbsp;&nbsp;</span>Year 2014</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2015\" data-toc-modified-id=\"Year-2015-19\"><span class=\"toc-item-num\">1.9&nbsp;&nbsp;</span>Year 2015</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2016\" data-toc-modified-id=\"Year-2016-110\"><span class=\"toc-item-num\">1.10&nbsp;&nbsp;</span>Year 2016</a></div><div class=\"lev2 toc-item\"><a href=\"#Year-2017\" data-toc-modified-id=\"Year-2017-111\"><span class=\"toc-item-num\">1.11&nbsp;&nbsp;</span>Year 2017</a></div><div class=\"lev1 toc-item\"><a href=\"#数据合并\" data-toc-modified-id=\"数据合并-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>数据合并</a></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# 将数据进行初步整理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2007"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2007年的数据，原始数据的单位为十亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n",
      "年份                    int64\n",
      "排名(Rank)              int64\n",
      "公司名称(Company)        object\n",
      "所在国家或地区(Country)     object\n",
      "所在行业(Industry)       object\n",
      "销售收入(Sales)          object\n",
      "利润(Profits)          object\n",
      "总资产(Assets)          object\n",
      "市值(Market Vaue)     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>排名(Rank)</th>\n",
       "      <th>公司名称(Company)</th>\n",
       "      <th>所在国家或地区(Country)</th>\n",
       "      <th>所在行业(Industry)</th>\n",
       "      <th>销售收入(Sales)</th>\n",
       "      <th>利润(Profits)</th>\n",
       "      <th>总资产(Assets)</th>\n",
       "      <th>市值(Market Vaue)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>Citigroup /花旗集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>146.56</td>\n",
       "      <td>21.54</td>\n",
       "      <td>1,884.32</td>\n",
       "      <td>247.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>Bank of America /美国银行</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>116.57</td>\n",
       "      <td>21.13</td>\n",
       "      <td>1,459.74</td>\n",
       "      <td>226.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>HSBC Holdings/汇丰集团</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>银行</td>\n",
       "      <td>121.51</td>\n",
       "      <td>16.63</td>\n",
       "      <td>1,860.76</td>\n",
       "      <td>202.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份  排名(Rank)          公司名称(Company) 所在国家或地区(Country) 所在行业(Industry)  \\\n",
       "0  2007         1        Citigroup /花旗集团           美国(US)             银行   \n",
       "1  2007         2  Bank of America /美国银行           美国(US)             银行   \n",
       "2  2007         3     HSBC Holdings/汇丰集团           英国(UK)             银行   \n",
       "\n",
       "  销售收入(Sales) 利润(Profits) 总资产(Assets)  市值(Market Vaue)  \n",
       "0      146.56       21.54    1,884.32           247.42  \n",
       "1      116.57       21.13    1,459.74           226.61  \n",
       "2      121.51       16.63    1,860.76           202.29  "
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007 = pd.read_csv('./data/data_forbes_2007.csv', encoding='gbk', thousands=',')\n",
    "print('the shape of DataFrame: ', df_2007.shape)\n",
    "print(df_2007.dtypes)\n",
    "df_2007.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 更新columns的命名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>Citigroup /花旗集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>146.56</td>\n",
       "      <td>21.54</td>\n",
       "      <td>1,884.32</td>\n",
       "      <td>247.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>Bank of America /美国银行</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>116.57</td>\n",
       "      <td>21.13</td>\n",
       "      <td>1,459.74</td>\n",
       "      <td>226.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>HSBC Holdings/汇丰集团</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>银行</td>\n",
       "      <td>121.51</td>\n",
       "      <td>16.63</td>\n",
       "      <td>1,860.76</td>\n",
       "      <td>202.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank          Company_cn_en Country_cn_en Industry_cn   Sales  \\\n",
       "0  2007     1        Citigroup /花旗集团        美国(US)          银行  146.56   \n",
       "1  2007     2  Bank of America /美国银行        美国(US)          银行  116.57   \n",
       "2  2007     3     HSBC Holdings/汇丰集团        英国(UK)          银行  121.51   \n",
       "\n",
       "  Profits    Assets  Market_value  \n",
       "0   21.54  1,884.32        247.42  \n",
       "1   21.13  1,459.74        226.61  \n",
       "2   16.63  1,860.76        202.29  "
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "column_update = ['Year', 'Rank', 'Company_cn_en', 'Country_cn_en', \n",
    "                 'Industry_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2007.columns = column_update\n",
    "df_2007.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **通过前面的分析可看出，只有“Market_value”是数字类型，找出'Sales','Profits'及'Assets'中非数字的内容**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2007</td>\n",
       "      <td>118</td>\n",
       "      <td>Repsol-YPF /瑞普索</td>\n",
       "      <td>西班牙(SP)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>64.20 E</td>\n",
       "      <td>4.12</td>\n",
       "      <td>58.43</td>\n",
       "      <td>38.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>616</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Inpex Holdings</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>6.49 E</td>\n",
       "      <td>1.02 E</td>\n",
       "      <td>10.77 E</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>2007</td>\n",
       "      <td>881</td>\n",
       "      <td>Asahi Breweries/朝日啤酒</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>7.97 E</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.66</td>\n",
       "      <td>7.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Rank         Company_cn_en Country_cn_en Industry_cn    Sales  \\\n",
       "117  2007   118       Repsol-YPF /瑞普索       西班牙(SP)          炼油  64.20 E   \n",
       "616  2007   617        Inpex Holdings        日本(JA)          炼油   6.49 E   \n",
       "880  2007   881  Asahi Breweries/朝日啤酒        日本(JA)    食品、饮料和烟草   7.97 E   \n",
       "\n",
       "    Profits   Assets  Market_value  \n",
       "117    4.12    58.43         38.75  \n",
       "616  1.02 E  10.77 E         19.65  \n",
       "880    0.38    10.66          7.71  "
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007[df_2007['Sales'].str.contains('.*[A-Za-z]', regex=True)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 用replace()方法替换“Sales”列中含有字母的内容"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df_2007['Sales'] = df_2007['Sales'].replace('([A-Za-z])', '', regex=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看替换后的结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2007</td>\n",
       "      <td>118</td>\n",
       "      <td>Repsol-YPF /瑞普索</td>\n",
       "      <td>西班牙(SP)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>64.20</td>\n",
       "      <td>4.12</td>\n",
       "      <td>58.43</td>\n",
       "      <td>38.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>616</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Inpex Holdings</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>6.49</td>\n",
       "      <td>1.02 E</td>\n",
       "      <td>10.77 E</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>2007</td>\n",
       "      <td>881</td>\n",
       "      <td>Asahi Breweries/朝日啤酒</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>7.97</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.66</td>\n",
       "      <td>7.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Rank         Company_cn_en Country_cn_en Industry_cn   Sales  \\\n",
       "117  2007   118       Repsol-YPF /瑞普索       西班牙(SP)          炼油  64.20    \n",
       "616  2007   617        Inpex Holdings        日本(JA)          炼油   6.49    \n",
       "880  2007   881  Asahi Breweries/朝日啤酒        日本(JA)    食品、饮料和烟草   7.97    \n",
       "\n",
       "    Profits   Assets  Market_value  \n",
       "117    4.12    58.43         38.75  \n",
       "616  1.02 E  10.77 E         19.65  \n",
       "880    0.38    10.66          7.71  "
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007.loc[[117,616,880], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **查看“Assets”列中非数字的内容**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>616</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Inpex Holdings</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>6.49</td>\n",
       "      <td>1.02 E</td>\n",
       "      <td>10.77 E</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Rank   Company_cn_en Country_cn_en Industry_cn  Sales Profits  \\\n",
       "616  2007   617  Inpex Holdings        日本(JA)          炼油  6.49   1.02 E   \n",
       "\n",
       "      Assets  Market_value  \n",
       "616  10.77 E         19.65  "
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007[df_2007['Assets'].str.contains('.*[A-Za-z]', regex=True)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 替换非数字的内容，以及替换千分位间隔符号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year                       2007\n",
       "Rank                        617\n",
       "Company_cn_en    Inpex Holdings\n",
       "Country_cn_en            日本(JA)\n",
       "Industry_cn                  炼油\n",
       "Sales                     6.49 \n",
       "Profits                  1.02 E\n",
       "Assets                   10.77 \n",
       "Market_value              19.65\n",
       "Name: 616, dtype: object"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将数字后面的字母进行替换\n",
    "df_2007['Assets'] = df_2007['Assets'].replace('([A-Za-z])', '', regex=True)\n",
    "\n",
    "# 千分位数字的逗号被识别为string了，需要替换\n",
    "df_2007['Assets'] = df_2007['Assets'].replace(',', '', regex=True)\n",
    "df_2007.loc[616, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **发现“Profits”中有NaN值，需要先进行替换**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>2007</td>\n",
       "      <td>959</td>\n",
       "      <td>UAL/美国联合航空公司</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>运输</td>\n",
       "      <td>19.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.86</td>\n",
       "      <td>4.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>2007</td>\n",
       "      <td>1441</td>\n",
       "      <td>Owens Corning/欧文斯科宁</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>建筑</td>\n",
       "      <td>6.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.47</td>\n",
       "      <td>4.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1544</th>\n",
       "      <td>2007</td>\n",
       "      <td>1545</td>\n",
       "      <td>Parmalat/帕玛拉特公司</td>\n",
       "      <td>意大利(IT)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>4.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.90</td>\n",
       "      <td>7.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1912</th>\n",
       "      <td>2007</td>\n",
       "      <td>1912</td>\n",
       "      <td>Winn-Dixie Stores</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>食品市场</td>\n",
       "      <td>6.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank        Company_cn_en Country_cn_en Industry_cn  Sales  \\\n",
       "958   2007   959         UAL/美国联合航空公司        美国(US)          运输  19.34   \n",
       "1440  2007  1441  Owens Corning/欧文斯科宁        美国(US)          建筑   6.46   \n",
       "1544  2007  1545      Parmalat/帕玛拉特公司       意大利(IT)    食品、饮料和烟草   4.83   \n",
       "1912  2007  1912    Winn-Dixie Stores        美国(US)        食品市场   6.96   \n",
       "\n",
       "     Profits Assets  Market_value  \n",
       "958      NaN  25.86          4.43  \n",
       "1440     NaN   8.47          4.19  \n",
       "1544     NaN   4.90          7.02  \n",
       "1912     NaN   1.62          1.05  "
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007[pd.isnull(df_2007['Profits'])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 将NaN值填充为 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>2007</td>\n",
       "      <td>959</td>\n",
       "      <td>UAL/美国联合航空公司</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>运输</td>\n",
       "      <td>19.34</td>\n",
       "      <td>0</td>\n",
       "      <td>25.86</td>\n",
       "      <td>4.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>2007</td>\n",
       "      <td>1441</td>\n",
       "      <td>Owens Corning/欧文斯科宁</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>建筑</td>\n",
       "      <td>6.46</td>\n",
       "      <td>0</td>\n",
       "      <td>8.47</td>\n",
       "      <td>4.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1544</th>\n",
       "      <td>2007</td>\n",
       "      <td>1545</td>\n",
       "      <td>Parmalat/帕玛拉特公司</td>\n",
       "      <td>意大利(IT)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>4.83</td>\n",
       "      <td>0</td>\n",
       "      <td>4.90</td>\n",
       "      <td>7.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1912</th>\n",
       "      <td>2007</td>\n",
       "      <td>1912</td>\n",
       "      <td>Winn-Dixie Stores</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>食品市场</td>\n",
       "      <td>6.96</td>\n",
       "      <td>0</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank        Company_cn_en Country_cn_en Industry_cn  Sales  \\\n",
       "958   2007   959         UAL/美国联合航空公司        美国(US)          运输  19.34   \n",
       "1440  2007  1441  Owens Corning/欧文斯科宁        美国(US)          建筑   6.46   \n",
       "1544  2007  1545      Parmalat/帕玛拉特公司       意大利(IT)    食品、饮料和烟草   4.83   \n",
       "1912  2007  1912    Winn-Dixie Stores        美国(US)        食品市场   6.96   \n",
       "\n",
       "     Profits Assets  Market_value  \n",
       "958        0  25.86          4.43  \n",
       "1440       0   8.47          4.19  \n",
       "1544       0   4.90          7.02  \n",
       "1912       0   1.62          1.05  "
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Profits'].fillna(0, inplace=True)\n",
    "df_2007.loc[[958,1440,1544,1912], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 将“Profits”列中非数字的内容进行替换，并查看替换后的结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2007</td>\n",
       "      <td>118</td>\n",
       "      <td>Repsol-YPF /瑞普索</td>\n",
       "      <td>西班牙(SP)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>64.20</td>\n",
       "      <td>4.12</td>\n",
       "      <td>58.43</td>\n",
       "      <td>38.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>616</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Inpex Holdings</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>6.49</td>\n",
       "      <td>1.02</td>\n",
       "      <td>10.77</td>\n",
       "      <td>19.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>2007</td>\n",
       "      <td>881</td>\n",
       "      <td>Asahi Breweries/朝日啤酒</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>7.97</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10.66</td>\n",
       "      <td>7.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Rank         Company_cn_en Country_cn_en Industry_cn   Sales  \\\n",
       "117  2007   118       Repsol-YPF /瑞普索       西班牙(SP)          炼油  64.20    \n",
       "616  2007   617        Inpex Holdings        日本(JA)          炼油   6.49    \n",
       "880  2007   881  Asahi Breweries/朝日啤酒        日本(JA)    食品、饮料和烟草   7.97    \n",
       "\n",
       "    Profits  Assets  Market_value  \n",
       "117    4.12   58.43         38.75  \n",
       "616   1.02   10.77          19.65  \n",
       "880    0.38   10.66          7.71  "
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Profits'] = df_2007['Profits'].replace('([A-Za-z])', '', regex=True)\n",
    "df_2007.loc[[117,616,880], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **将sting类型的数字转换为数据类型，这里使用 pd.to_numeric() 方法**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year               int64\n",
       "Rank               int64\n",
       "Company_cn_en     object\n",
       "Country_cn_en     object\n",
       "Industry_cn       object\n",
       "Sales            float64\n",
       "Profits          float64\n",
       "Assets           float64\n",
       "Market_value     float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Sales'] = pd.to_numeric(df_2007['Sales'])\n",
    "df_2007['Profits'] = pd.to_numeric(df_2007['Profits'])\n",
    "df_2007['Assets'] = pd.to_numeric(df_2007['Assets'])\n",
    "df_2007.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "* **拆分\"Company_cn_en\"列**，新生成两列，分别为公司英文名称和中文名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0           Citigroup \n",
      "1     Bank of America \n",
      "2        HSBC Holdings\n",
      "3    General Electric \n",
      "4      JPMorgan Chase \n",
      "Name: Company_en, dtype: object\n",
      "1995    NaN\n",
      "1996    NaN\n",
      "1997    NaN\n",
      "1998    NaN\n",
      "1999    NaN\n",
      "Name: Company_cn, dtype: object\n"
     ]
    }
   ],
   "source": [
    "df_2007['Company_en'],df_2007['Company_cn'] = df_2007['Company_cn_en'].str.split('/', 1).str\n",
    "print(df_2007['Company_en'][:5])\n",
    "print(df_2007['Company_cn'] [-5:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>2007</td>\n",
       "      <td>1998</td>\n",
       "      <td>CBOT Holdings</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.81</td>\n",
       "      <td>8.54</td>\n",
       "      <td>CBOT Holdings</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>2007</td>\n",
       "      <td>1998</td>\n",
       "      <td>Singapore Petroleum</td>\n",
       "      <td>新加坡(SI)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>5.59</td>\n",
       "      <td>0.19</td>\n",
       "      <td>2.05</td>\n",
       "      <td>1.50</td>\n",
       "      <td>Singapore Petroleum</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>2007</td>\n",
       "      <td>2000</td>\n",
       "      <td>DVB Bank</td>\n",
       "      <td>德国(GE)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.06</td>\n",
       "      <td>12.74</td>\n",
       "      <td>1.26</td>\n",
       "      <td>DVB Bank</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank        Company_cn_en Country_cn_en Industry_cn  Sales  \\\n",
       "1997  2007  1998        CBOT Holdings        美国(US)        综合金融   0.64   \n",
       "1998  2007  1998  Singapore Petroleum       新加坡(SI)          炼油   5.59   \n",
       "1999  2007  2000             DVB Bank        德国(GE)          银行   0.77   \n",
       "\n",
       "      Profits  Assets  Market_value           Company_en Company_cn  \n",
       "1997     0.17    0.81          8.54        CBOT Holdings        NaN  \n",
       "1998     0.19    2.05          1.50  Singapore Petroleum        NaN  \n",
       "1999     0.06   12.74          1.26             DVB Bank        NaN  "
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007.tail(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **拆分\"Country_cn_en\"列**，新生成两列，分别为国家中文名称和英文名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    美国\n",
      "1    美国\n",
      "2    英国\n",
      "3    美国\n",
      "4    美国\n",
      "Name: Country_cn, dtype: object\n",
      "1995    US)\n",
      "1996    US)\n",
      "1997    US)\n",
      "1998    SI)\n",
      "1999    GE)\n",
      "Name: Country_en, dtype: object\n"
     ]
    }
   ],
   "source": [
    "df_2007['Country_cn'],df_2007['Country_en'] = df_2007['Country_cn_en'].str.split('(', 1).str\n",
    "print(df_2007['Country_cn'][:5])\n",
    "print(df_2007['Country_en'][-5:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 由于国家的英文名称中，最后有半个括号，需要去除，用 Series.str.slice()方法\n",
    "* 参数表示选取从开始到倒数第二个，即不要括号\")\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>Citigroup /花旗集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>146.56</td>\n",
       "      <td>21.54</td>\n",
       "      <td>1884.32</td>\n",
       "      <td>247.42</td>\n",
       "      <td>Citigroup</td>\n",
       "      <td>花旗集团</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>Bank of America /美国银行</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>银行</td>\n",
       "      <td>116.57</td>\n",
       "      <td>21.13</td>\n",
       "      <td>1459.74</td>\n",
       "      <td>226.61</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>HSBC Holdings/汇丰集团</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>银行</td>\n",
       "      <td>121.51</td>\n",
       "      <td>16.63</td>\n",
       "      <td>1860.76</td>\n",
       "      <td>202.29</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank          Company_cn_en Country_cn_en Industry_cn   Sales  \\\n",
       "0  2007     1        Citigroup /花旗集团        美国(US)          银行  146.56   \n",
       "1  2007     2  Bank of America /美国银行        美国(US)          银行  116.57   \n",
       "2  2007     3     HSBC Holdings/汇丰集团        英国(UK)          银行  121.51   \n",
       "\n",
       "   Profits   Assets  Market_value        Company_en Company_cn Country_cn  \\\n",
       "0    21.54  1884.32        247.42        Citigroup        花旗集团         美国   \n",
       "1    21.13  1459.74        226.61  Bank of America        美国银行         美国   \n",
       "2    16.63  1860.76        202.29     HSBC Holdings       汇丰集团         英国   \n",
       "\n",
       "  Country_en  \n",
       "0         US  \n",
       "1         US  \n",
       "2         UK  "
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Country_en'] = df_2007['Country_en'].str.slice(0,-1)\n",
    "df_2007.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 考虑的中国的企业有区分为中国大陆，中国香港，中国台湾\n",
    "* 对应的国家英文名称也需要修改下\n",
    "* 中国大陆：CN；中国香港：CN-HK；中国台湾：CN-TA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2007</td>\n",
       "      <td>41</td>\n",
       "      <td>PetroChina /中国石油</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>68.43</td>\n",
       "      <td>16.53</td>\n",
       "      <td>96.42</td>\n",
       "      <td>208.76</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>中国石油</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2007</td>\n",
       "      <td>53</td>\n",
       "      <td>ICBC /中国工商银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>31.98</td>\n",
       "      <td>4.65</td>\n",
       "      <td>800.04</td>\n",
       "      <td>176.03</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2007</td>\n",
       "      <td>69</td>\n",
       "      <td>CCB-China Construction Bank /中国建设银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>23.18</td>\n",
       "      <td>5.84</td>\n",
       "      <td>568.21</td>\n",
       "      <td>126.55</td>\n",
       "      <td>CCB-China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2007</td>\n",
       "      <td>71</td>\n",
       "      <td>Sinopec-China Petroleum /中石化</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>99.03</td>\n",
       "      <td>5.07</td>\n",
       "      <td>65.83</td>\n",
       "      <td>93.57</td>\n",
       "      <td>Sinopec-China Petroleum</td>\n",
       "      <td>中石化</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2007</td>\n",
       "      <td>82</td>\n",
       "      <td>Bank of China /中国银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>23.10</td>\n",
       "      <td>3.41</td>\n",
       "      <td>585.55</td>\n",
       "      <td>143.80</td>\n",
       "      <td>Bank of China</td>\n",
       "      <td>中国银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2007</td>\n",
       "      <td>89</td>\n",
       "      <td>China Mobile /中国移动</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>29.79</td>\n",
       "      <td>6.56</td>\n",
       "      <td>51.35</td>\n",
       "      <td>185.31</td>\n",
       "      <td>China Mobile</td>\n",
       "      <td>中国移动</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>2007</td>\n",
       "      <td>176</td>\n",
       "      <td>Hutchison Whampoa/和记黄埔</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>多元化</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1.85</td>\n",
       "      <td>74.97</td>\n",
       "      <td>40.57</td>\n",
       "      <td>Hutchison Whampoa</td>\n",
       "      <td>和记黄埔</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>2007</td>\n",
       "      <td>181</td>\n",
       "      <td>China Telecom/中国电信</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>20.98</td>\n",
       "      <td>3.46</td>\n",
       "      <td>50.34</td>\n",
       "      <td>37.50</td>\n",
       "      <td>China Telecom</td>\n",
       "      <td>中国电信</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>2007</td>\n",
       "      <td>243</td>\n",
       "      <td>China Life Insurance /中国人寿</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>保险</td>\n",
       "      <td>11.18</td>\n",
       "      <td>1.15</td>\n",
       "      <td>69.30</td>\n",
       "      <td>109.96</td>\n",
       "      <td>China Life Insurance</td>\n",
       "      <td>中国人寿</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>2007</td>\n",
       "      <td>308</td>\n",
       "      <td>Bank of Communications/中国交通银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>6.64</td>\n",
       "      <td>1.15</td>\n",
       "      <td>176.27</td>\n",
       "      <td>46.14</td>\n",
       "      <td>Bank of Communications</td>\n",
       "      <td>中国交通银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>2007</td>\n",
       "      <td>310</td>\n",
       "      <td>Taiwan Semiconductor/台积电</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>半导体</td>\n",
       "      <td>9.74</td>\n",
       "      <td>3.90</td>\n",
       "      <td>18.02</td>\n",
       "      <td>54.32</td>\n",
       "      <td>Taiwan Semiconductor</td>\n",
       "      <td>台积电</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>2007</td>\n",
       "      <td>341</td>\n",
       "      <td>Hon Hai Precision Ind /鸿海精密</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>27.78</td>\n",
       "      <td>1.24</td>\n",
       "      <td>13.99</td>\n",
       "      <td>34.83</td>\n",
       "      <td>Hon Hai Precision Ind</td>\n",
       "      <td>鸿海精密</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>2007</td>\n",
       "      <td>366</td>\n",
       "      <td>Baoshan Iron &amp; Steel /上海宝钢集团</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>15.63</td>\n",
       "      <td>1.57</td>\n",
       "      <td>17.59</td>\n",
       "      <td>21.42</td>\n",
       "      <td>Baoshan Iron &amp; Steel</td>\n",
       "      <td>上海宝钢集团</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>2007</td>\n",
       "      <td>389</td>\n",
       "      <td>Cathay Financial/国泰金融</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>保险</td>\n",
       "      <td>10.09</td>\n",
       "      <td>0.66</td>\n",
       "      <td>93.29</td>\n",
       "      <td>19.87</td>\n",
       "      <td>Cathay Financial</td>\n",
       "      <td>国泰金融</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>2007</td>\n",
       "      <td>395</td>\n",
       "      <td>Cnooc /中海油</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>8.51</td>\n",
       "      <td>3.10</td>\n",
       "      <td>14.22</td>\n",
       "      <td>34.94</td>\n",
       "      <td>Cnooc</td>\n",
       "      <td>中海油</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>2007</td>\n",
       "      <td>401</td>\n",
       "      <td>China Netcom Group /中国网通</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>10.69</td>\n",
       "      <td>1.70</td>\n",
       "      <td>24.70</td>\n",
       "      <td>15.70</td>\n",
       "      <td>China Netcom Group</td>\n",
       "      <td>中国网通</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>2007</td>\n",
       "      <td>423</td>\n",
       "      <td>China Shenhua Energy/中国神华能源股份有限公司</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>6.47</td>\n",
       "      <td>1.94</td>\n",
       "      <td>17.08</td>\n",
       "      <td>45.94</td>\n",
       "      <td>China Shenhua Energy</td>\n",
       "      <td>中国神华能源股份有限公司</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>2007</td>\n",
       "      <td>430</td>\n",
       "      <td>BOC Hong Kong/中银香港</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>4.13</td>\n",
       "      <td>1.74</td>\n",
       "      <td>106.03</td>\n",
       "      <td>25.58</td>\n",
       "      <td>BOC Hong Kong</td>\n",
       "      <td>中银香港</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2007</td>\n",
       "      <td>437</td>\n",
       "      <td>Formosa Petrochemical/台塑石化</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>13.56</td>\n",
       "      <td>1.74</td>\n",
       "      <td>12.35</td>\n",
       "      <td>19.28</td>\n",
       "      <td>Formosa Petrochemical</td>\n",
       "      <td>台塑石化</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2007</td>\n",
       "      <td>440</td>\n",
       "      <td>Ping An Insurance Group/平安保险</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>保险</td>\n",
       "      <td>7.95</td>\n",
       "      <td>0.52</td>\n",
       "      <td>39.62</td>\n",
       "      <td>39.60</td>\n",
       "      <td>Ping An Insurance Group</td>\n",
       "      <td>平安保险</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2007</td>\n",
       "      <td>452</td>\n",
       "      <td>Jardine Matheson/香港怡和集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>食品市场</td>\n",
       "      <td>11.96</td>\n",
       "      <td>1.25</td>\n",
       "      <td>18.34</td>\n",
       "      <td>13.59</td>\n",
       "      <td>Jardine Matheson</td>\n",
       "      <td>香港怡和集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>2007</td>\n",
       "      <td>511</td>\n",
       "      <td>Sun Hung Kai Properties /新鸿基房地产</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>3.30</td>\n",
       "      <td>2.56</td>\n",
       "      <td>29.72</td>\n",
       "      <td>29.49</td>\n",
       "      <td>Sun Hung Kai Properties</td>\n",
       "      <td>新鸿基房地产</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>2007</td>\n",
       "      <td>542</td>\n",
       "      <td>China Unicom /中国联通</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>10.67</td>\n",
       "      <td>0.60</td>\n",
       "      <td>17.63</td>\n",
       "      <td>16.03</td>\n",
       "      <td>China Unicom</td>\n",
       "      <td>中国联通</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>2007</td>\n",
       "      <td>552</td>\n",
       "      <td>CLP Holdings /中电控股</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>公用事业</td>\n",
       "      <td>5.87</td>\n",
       "      <td>1.27</td>\n",
       "      <td>16.42</td>\n",
       "      <td>17.65</td>\n",
       "      <td>CLP Holdings</td>\n",
       "      <td>中电控股</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575</th>\n",
       "      <td>2007</td>\n",
       "      <td>576</td>\n",
       "      <td>Chunghwa Telecom/中华电信</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>5.59</td>\n",
       "      <td>1.45</td>\n",
       "      <td>13.98</td>\n",
       "      <td>18.22</td>\n",
       "      <td>Chunghwa Telecom</td>\n",
       "      <td>中华电信</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>2007</td>\n",
       "      <td>601</td>\n",
       "      <td>China Steel/台湾中钢公司</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>材料</td>\n",
       "      <td>8.66</td>\n",
       "      <td>1.54</td>\n",
       "      <td>10.35</td>\n",
       "      <td>12.24</td>\n",
       "      <td>China Steel</td>\n",
       "      <td>台湾中钢公司</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>2007</td>\n",
       "      <td>604</td>\n",
       "      <td>China Merchants Bank/招商银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>3.53</td>\n",
       "      <td>0.46</td>\n",
       "      <td>90.76</td>\n",
       "      <td>33.19</td>\n",
       "      <td>China Merchants Bank</td>\n",
       "      <td>招商银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Nan Ya Plastic/南亚塑胶工业</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>化学制品</td>\n",
       "      <td>7.64</td>\n",
       "      <td>1.22</td>\n",
       "      <td>11.47</td>\n",
       "      <td>13.37</td>\n",
       "      <td>Nan Ya Plastic</td>\n",
       "      <td>南亚塑胶工业</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>2007</td>\n",
       "      <td>628</td>\n",
       "      <td>Cheung Kong/长江集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1.80</td>\n",
       "      <td>28.01</td>\n",
       "      <td>28.39</td>\n",
       "      <td>Cheung Kong</td>\n",
       "      <td>长江集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>736</th>\n",
       "      <td>2007</td>\n",
       "      <td>737</td>\n",
       "      <td>Swire Pacific /太古集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>多元化</td>\n",
       "      <td>2.44</td>\n",
       "      <td>2.42</td>\n",
       "      <td>16.05</td>\n",
       "      <td>17.32</td>\n",
       "      <td>Swire Pacific</td>\n",
       "      <td>太古集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1636</th>\n",
       "      <td>2007</td>\n",
       "      <td>1637</td>\n",
       "      <td>Champion REIT</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.16</td>\n",
       "      <td>2.95</td>\n",
       "      <td>1.54</td>\n",
       "      <td>Champion REIT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>2007</td>\n",
       "      <td>1642</td>\n",
       "      <td>Noble Group</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>13.75</td>\n",
       "      <td>0.13</td>\n",
       "      <td>3.81</td>\n",
       "      <td>2.14</td>\n",
       "      <td>Noble Group</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>2007</td>\n",
       "      <td>1662</td>\n",
       "      <td>Taiwan Mobile</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>1.81</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3.59</td>\n",
       "      <td>4.84</td>\n",
       "      <td>Taiwan Mobile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1681</th>\n",
       "      <td>2007</td>\n",
       "      <td>1682</td>\n",
       "      <td>Evergreen Marine</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>运输</td>\n",
       "      <td>4.29</td>\n",
       "      <td>0.37</td>\n",
       "      <td>3.96</td>\n",
       "      <td>1.90</td>\n",
       "      <td>Evergreen Marine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1692</th>\n",
       "      <td>2007</td>\n",
       "      <td>1693</td>\n",
       "      <td>China Southern Airlines</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>4.64</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>8.84</td>\n",
       "      <td>1.97</td>\n",
       "      <td>China Southern Airlines</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1705</th>\n",
       "      <td>2007</td>\n",
       "      <td>1706</td>\n",
       "      <td>Cosco Pacific</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>2.85</td>\n",
       "      <td>5.94</td>\n",
       "      <td>Cosco Pacific</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1710</th>\n",
       "      <td>2007</td>\n",
       "      <td>1711</td>\n",
       "      <td>China Shipping Container</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>3.52</td>\n",
       "      <td>0.44</td>\n",
       "      <td>3.59</td>\n",
       "      <td>2.26</td>\n",
       "      <td>China Shipping Container</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1736</th>\n",
       "      <td>2007</td>\n",
       "      <td>1737</td>\n",
       "      <td>China Resources Power Holdings</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>公用事业</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.37</td>\n",
       "      <td>3.67</td>\n",
       "      <td>5.37</td>\n",
       "      <td>China Resources Power Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1739</th>\n",
       "      <td>2007</td>\n",
       "      <td>1740</td>\n",
       "      <td>Citic Securities</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.52</td>\n",
       "      <td>14.29</td>\n",
       "      <td>Citic Securities</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1780</th>\n",
       "      <td>2007</td>\n",
       "      <td>1781</td>\n",
       "      <td>Far EasTone Telecom</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>2.19</td>\n",
       "      <td>0.45</td>\n",
       "      <td>3.01</td>\n",
       "      <td>4.45</td>\n",
       "      <td>Far EasTone Telecom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1786</th>\n",
       "      <td>2007</td>\n",
       "      <td>1787</td>\n",
       "      <td>E.Sun Financial</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.14</td>\n",
       "      <td>19.36</td>\n",
       "      <td>2.19</td>\n",
       "      <td>E.Sun Financial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2007</td>\n",
       "      <td>1825</td>\n",
       "      <td>Minmetals Development</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>贸易公司</td>\n",
       "      <td>8.25</td>\n",
       "      <td>0.04</td>\n",
       "      <td>3.46</td>\n",
       "      <td>1.50</td>\n",
       "      <td>Minmetals Development</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1840</th>\n",
       "      <td>2007</td>\n",
       "      <td>1841</td>\n",
       "      <td>Shanghai Automotive</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>耐用消费品</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.81</td>\n",
       "      <td>11.10</td>\n",
       "      <td>Shanghai Automotive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1846</th>\n",
       "      <td>2007</td>\n",
       "      <td>1847</td>\n",
       "      <td>HK Exchanges &amp; Clearing</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.17</td>\n",
       "      <td>2.96</td>\n",
       "      <td>10.97</td>\n",
       "      <td>HK Exchanges &amp; Clearing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1852</th>\n",
       "      <td>2007</td>\n",
       "      <td>1853</td>\n",
       "      <td>Link REIT</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.27</td>\n",
       "      <td>5.24</td>\n",
       "      <td>5.00</td>\n",
       "      <td>Link REIT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1860</th>\n",
       "      <td>2007</td>\n",
       "      <td>1861</td>\n",
       "      <td>Kweichow Moutai</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10.69</td>\n",
       "      <td>Kweichow Moutai</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>2007</td>\n",
       "      <td>1892</td>\n",
       "      <td>Yanzhou Coal Mining</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>1.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>2.63</td>\n",
       "      <td>4.52</td>\n",
       "      <td>Yanzhou Coal Mining</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1908</th>\n",
       "      <td>2007</td>\n",
       "      <td>1909</td>\n",
       "      <td>China Shipping Develop</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.66</td>\n",
       "      <td>4.61</td>\n",
       "      <td>China Shipping Develop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1920</th>\n",
       "      <td>2007</td>\n",
       "      <td>1920</td>\n",
       "      <td>Wing Lung Bank</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.21</td>\n",
       "      <td>10.92</td>\n",
       "      <td>2.43</td>\n",
       "      <td>Wing Lung Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1922</th>\n",
       "      <td>2007</td>\n",
       "      <td>1923</td>\n",
       "      <td>Delta Electronics</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>2.46</td>\n",
       "      <td>0.23</td>\n",
       "      <td>2.49</td>\n",
       "      <td>6.40</td>\n",
       "      <td>Delta Electronics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945</th>\n",
       "      <td>2007</td>\n",
       "      <td>1946</td>\n",
       "      <td>China Airlines</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>运输</td>\n",
       "      <td>3.61</td>\n",
       "      <td>0.02</td>\n",
       "      <td>7.63</td>\n",
       "      <td>1.85</td>\n",
       "      <td>China Airlines</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948</th>\n",
       "      <td>2007</td>\n",
       "      <td>1949</td>\n",
       "      <td>Wing Hang Bank</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.17</td>\n",
       "      <td>13.45</td>\n",
       "      <td>3.33</td>\n",
       "      <td>Wing Hang Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959</th>\n",
       "      <td>2007</td>\n",
       "      <td>1959</td>\n",
       "      <td>PCCW</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>2.90</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6.87</td>\n",
       "      <td>3.98</td>\n",
       "      <td>PCCW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1960</th>\n",
       "      <td>2007</td>\n",
       "      <td>1961</td>\n",
       "      <td>Benq</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>5.39</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>5.04</td>\n",
       "      <td>1.27</td>\n",
       "      <td>Benq</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>2007</td>\n",
       "      <td>1964</td>\n",
       "      <td>TCL Corp</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>6.40</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1.39</td>\n",
       "      <td>TCL Corp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>2007</td>\n",
       "      <td>1971</td>\n",
       "      <td>Wuliangye Yibin</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.19</td>\n",
       "      <td>8.81</td>\n",
       "      <td>Wuliangye Yibin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>2007</td>\n",
       "      <td>1974</td>\n",
       "      <td>CNPC (Hong Kong)</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.47</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.30</td>\n",
       "      <td>CNPC (Hong Kong)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>2007</td>\n",
       "      <td>1976</td>\n",
       "      <td>K Wah International</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.47</td>\n",
       "      <td>1.29</td>\n",
       "      <td>0.98</td>\n",
       "      <td>K Wah International</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>2007</td>\n",
       "      <td>1987</td>\n",
       "      <td>China Overseas Land &amp; Inv</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.20</td>\n",
       "      <td>3.24</td>\n",
       "      <td>7.05</td>\n",
       "      <td>China Overseas Land &amp; Inv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>2007</td>\n",
       "      <td>1989</td>\n",
       "      <td>Nine Dragons Paper Holdings</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.86</td>\n",
       "      <td>8.61</td>\n",
       "      <td>Nine Dragons Paper Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>HK)/中国大陆(CN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank                        Company_cn_en      Country_cn_en  \\\n",
       "40    2007    41                     PetroChina /中国石油           中国大陆(CN)   \n",
       "52    2007    53                         ICBC /中国工商银行           中国大陆(CN)   \n",
       "68    2007    69  CCB-China Construction Bank /中国建设银行           中国大陆(CN)   \n",
       "70    2007    71         Sinopec-China Petroleum /中石化           中国大陆(CN)   \n",
       "81    2007    82                  Bank of China /中国银行           中国大陆(CN)   \n",
       "88    2007    89                   China Mobile /中国移动  中国香港(HK)/中国大陆(CN)   \n",
       "175   2007   176               Hutchison Whampoa/和记黄埔  中国香港(HK)/中国大陆(CN)   \n",
       "180   2007   181                   China Telecom/中国电信           中国大陆(CN)   \n",
       "242   2007   243           China Life Insurance /中国人寿           中国大陆(CN)   \n",
       "307   2007   308        Bank of Communications/中国交通银行           中国大陆(CN)   \n",
       "309   2007   310             Taiwan Semiconductor/台积电           中国台湾(TA)   \n",
       "340   2007   341          Hon Hai Precision Ind /鸿海精密           中国台湾(TA)   \n",
       "365   2007   366         Baoshan Iron & Steel /上海宝钢集团           中国大陆(CN)   \n",
       "388   2007   389                Cathay Financial/国泰金融           中国台湾(TA)   \n",
       "394   2007   395                           Cnooc /中海油  中国香港(HK)/中国大陆(CN)   \n",
       "400   2007   401             China Netcom Group /中国网通  中国香港(HK)/中国大陆(CN)   \n",
       "422   2007   423    China Shenhua Energy/中国神华能源股份有限公司           中国大陆(CN)   \n",
       "429   2007   430                   BOC Hong Kong/中银香港  中国香港(HK)/中国大陆(CN)   \n",
       "436   2007   437           Formosa Petrochemical/台塑石化           中国台湾(TA)   \n",
       "439   2007   440         Ping An Insurance Group/平安保险           中国大陆(CN)   \n",
       "451   2007   452              Jardine Matheson/香港怡和集团  中国香港(HK)/中国大陆(CN)   \n",
       "510   2007   511      Sun Hung Kai Properties /新鸿基房地产  中国香港(HK)/中国大陆(CN)   \n",
       "541   2007   542                   China Unicom /中国联通  中国香港(HK)/中国大陆(CN)   \n",
       "551   2007   552                   CLP Holdings /中电控股  中国香港(HK)/中国大陆(CN)   \n",
       "575   2007   576                Chunghwa Telecom/中华电信           中国台湾(TA)   \n",
       "600   2007   601                   China Steel/台湾中钢公司           中国台湾(TA)   \n",
       "603   2007   604            China Merchants Bank/招商银行           中国大陆(CN)   \n",
       "617   2007   617                Nan Ya Plastic/南亚塑胶工业           中国台湾(TA)   \n",
       "627   2007   628                     Cheung Kong/长江集团  中国香港(HK)/中国大陆(CN)   \n",
       "736   2007   737                  Swire Pacific /太古集团  中国香港(HK)/中国大陆(CN)   \n",
       "...    ...   ...                                  ...                ...   \n",
       "1636  2007  1637                        Champion REIT  中国香港(HK)/中国大陆(CN)   \n",
       "1641  2007  1642                          Noble Group  中国香港(HK)/中国大陆(CN)   \n",
       "1661  2007  1662                        Taiwan Mobile           中国台湾(TA)   \n",
       "1681  2007  1682                     Evergreen Marine           中国台湾(TA)   \n",
       "1692  2007  1693              China Southern Airlines           中国大陆(CN)   \n",
       "1705  2007  1706                        Cosco Pacific  中国香港(HK)/中国大陆(CN)   \n",
       "1710  2007  1711             China Shipping Container           中国大陆(CN)   \n",
       "1736  2007  1737       China Resources Power Holdings  中国香港(HK)/中国大陆(CN)   \n",
       "1739  2007  1740                     Citic Securities           中国大陆(CN)   \n",
       "1780  2007  1781                  Far EasTone Telecom           中国台湾(TA)   \n",
       "1786  2007  1787                      E.Sun Financial           中国台湾(TA)   \n",
       "1824  2007  1825                Minmetals Development           中国大陆(CN)   \n",
       "1840  2007  1841                  Shanghai Automotive           中国大陆(CN)   \n",
       "1846  2007  1847              HK Exchanges & Clearing  中国香港(HK)/中国大陆(CN)   \n",
       "1852  2007  1853                            Link REIT  中国香港(HK)/中国大陆(CN)   \n",
       "1860  2007  1861                      Kweichow Moutai           中国大陆(CN)   \n",
       "1892  2007  1892                  Yanzhou Coal Mining           中国大陆(CN)   \n",
       "1908  2007  1909               China Shipping Develop           中国大陆(CN)   \n",
       "1920  2007  1920                       Wing Lung Bank  中国香港(HK)/中国大陆(CN)   \n",
       "1922  2007  1923                    Delta Electronics           中国台湾(TA)   \n",
       "1945  2007  1946                       China Airlines           中国台湾(TA)   \n",
       "1948  2007  1949                       Wing Hang Bank  中国香港(HK)/中国大陆(CN)   \n",
       "1959  2007  1959                                 PCCW  中国香港(HK)/中国大陆(CN)   \n",
       "1960  2007  1961                                 Benq           中国台湾(TA)   \n",
       "1963  2007  1964                             TCL Corp           中国大陆(CN)   \n",
       "1970  2007  1971                      Wuliangye Yibin           中国大陆(CN)   \n",
       "1973  2007  1974                     CNPC (Hong Kong)  中国香港(HK)/中国大陆(CN)   \n",
       "1975  2007  1976                  K Wah International  中国香港(HK)/中国大陆(CN)   \n",
       "1986  2007  1987            China Overseas Land & Inv  中国香港(HK)/中国大陆(CN)   \n",
       "1989  2007  1989          Nine Dragons Paper Holdings  中国香港(HK)/中国大陆(CN)   \n",
       "\n",
       "     Industry_cn  Sales  Profits  Assets  Market_value  \\\n",
       "40            炼油  68.43    16.53   96.42        208.76   \n",
       "52            银行  31.98     4.65  800.04        176.03   \n",
       "68            银行  23.18     5.84  568.21        126.55   \n",
       "70            炼油  99.03     5.07   65.83         93.57   \n",
       "81            银行  23.10     3.41  585.55        143.80   \n",
       "88         电信运营商  29.79     6.56   51.35        185.31   \n",
       "175          多元化  23.55     1.85   74.97         40.57   \n",
       "180        电信运营商  20.98     3.46   50.34         37.50   \n",
       "242           保险  11.18     1.15   69.30        109.96   \n",
       "307           银行   6.64     1.15  176.27         46.14   \n",
       "309          半导体   9.74     3.90   18.02         54.32   \n",
       "340      技术硬件和装备  27.78     1.24   13.99         34.83   \n",
       "365           材料  15.63     1.57   17.59         21.42   \n",
       "388           保险  10.09     0.66   93.29         19.87   \n",
       "394           炼油   8.51     3.10   14.22         34.94   \n",
       "400        电信运营商  10.69     1.70   24.70         15.70   \n",
       "422           材料   6.47     1.94   17.08         45.94   \n",
       "429           银行   4.13     1.74  106.03         25.58   \n",
       "436           炼油  13.56     1.74   12.35         19.28   \n",
       "439           保险   7.95     0.52   39.62         39.60   \n",
       "451         食品市场  11.96     1.25   18.34         13.59   \n",
       "510         综合金融   3.30     2.56   29.72         29.49   \n",
       "541        电信运营商  10.67     0.60   17.63         16.03   \n",
       "551         公用事业   5.87     1.27   16.42         17.65   \n",
       "575        电信运营商   5.59     1.45   13.98         18.22   \n",
       "600           材料   8.66     1.54   10.35         12.24   \n",
       "603           银行   3.53     0.46   90.76         33.19   \n",
       "617         化学制品   7.64     1.22   11.47         13.37   \n",
       "627         综合金融   0.80     1.80   28.01         28.39   \n",
       "736          多元化   2.44     2.42   16.05         17.32   \n",
       "...          ...    ...      ...     ...           ...   \n",
       "1636        综合金融   0.05     1.16    2.95          1.54   \n",
       "1641          运输  13.75     0.13    3.81          2.14   \n",
       "1661       电信运营商   1.81     0.50    3.59          4.84   \n",
       "1681          运输   4.29     0.37    3.96          1.90   \n",
       "1692          运输   4.64    -0.23    8.84          1.97   \n",
       "1705          运输   0.30     0.34    2.85          5.94   \n",
       "1710          运输   3.52     0.44    3.59          2.26   \n",
       "1736        公用事业   0.76     0.37    3.67          5.37   \n",
       "1739        综合金融   0.14     0.04    2.52         14.29   \n",
       "1780       电信运营商   2.19     0.45    3.01          4.45   \n",
       "1786          银行   0.73     0.14   19.36          2.19   \n",
       "1824        贸易公司   8.25     0.04    3.46          1.50   \n",
       "1840       耐用消费品   0.79     0.14    1.81         11.10   \n",
       "1846        综合金融   0.35     0.17    2.96         10.97   \n",
       "1852        综合金融   0.43     0.27    5.24          5.00   \n",
       "1860    食品、饮料和烟草   0.43     0.14    1.00         10.69   \n",
       "1892          材料   1.43     0.36    2.63          4.52   \n",
       "1908          运输   1.06     0.33    1.66          4.61   \n",
       "1920          银行   0.66     0.21   10.92          2.43   \n",
       "1922     技术硬件和装备   2.46     0.23    2.49          6.40   \n",
       "1945          运输   3.61     0.02    7.63          1.85   \n",
       "1948          银行   0.66     0.17   13.45          3.33   \n",
       "1959       电信运营商   2.90     0.21    6.87          3.98   \n",
       "1960     技术硬件和装备   5.39    -0.16    5.04          1.27   \n",
       "1963     技术硬件和装备   6.40    -0.04    3.77          1.39   \n",
       "1970    食品、饮料和烟草   0.70     0.10    1.19          8.81   \n",
       "1973          炼油   0.44     0.47    2.07          2.30   \n",
       "1975        综合金融   0.04     0.47    1.29          0.98   \n",
       "1986        综合金融   0.90     0.20    3.24          7.05   \n",
       "1989          材料   0.99     0.17    1.86          8.61   \n",
       "\n",
       "                          Company_en    Company_cn Country_cn   Country_en  \n",
       "40                       PetroChina           中国石油       中国大陆           CN  \n",
       "52                             ICBC         中国工商银行       中国大陆           CN  \n",
       "68      CCB-China Construction Bank         中国建设银行       中国大陆           CN  \n",
       "70          Sinopec-China Petroleum            中石化       中国大陆           CN  \n",
       "81                    Bank of China           中国银行       中国大陆           CN  \n",
       "88                     China Mobile           中国移动       中国香港  HK)/中国大陆(CN  \n",
       "175                Hutchison Whampoa          和记黄埔       中国香港  HK)/中国大陆(CN  \n",
       "180                    China Telecom          中国电信       中国大陆           CN  \n",
       "242            China Life Insurance           中国人寿       中国大陆           CN  \n",
       "307           Bank of Communications        中国交通银行       中国大陆           CN  \n",
       "309             Taiwan Semiconductor           台积电       中国台湾           TA  \n",
       "340           Hon Hai Precision Ind           鸿海精密       中国台湾           TA  \n",
       "365            Baoshan Iron & Steel         上海宝钢集团       中国大陆           CN  \n",
       "388                 Cathay Financial          国泰金融       中国台湾           TA  \n",
       "394                           Cnooc            中海油       中国香港  HK)/中国大陆(CN  \n",
       "400              China Netcom Group           中国网通       中国香港  HK)/中国大陆(CN  \n",
       "422             China Shenhua Energy  中国神华能源股份有限公司       中国大陆           CN  \n",
       "429                    BOC Hong Kong          中银香港       中国香港  HK)/中国大陆(CN  \n",
       "436            Formosa Petrochemical          台塑石化       中国台湾           TA  \n",
       "439          Ping An Insurance Group          平安保险       中国大陆           CN  \n",
       "451                 Jardine Matheson        香港怡和集团       中国香港  HK)/中国大陆(CN  \n",
       "510         Sun Hung Kai Properties         新鸿基房地产       中国香港  HK)/中国大陆(CN  \n",
       "541                    China Unicom           中国联通       中国香港  HK)/中国大陆(CN  \n",
       "551                    CLP Holdings           中电控股       中国香港  HK)/中国大陆(CN  \n",
       "575                 Chunghwa Telecom          中华电信       中国台湾           TA  \n",
       "600                      China Steel        台湾中钢公司       中国台湾           TA  \n",
       "603             China Merchants Bank          招商银行       中国大陆           CN  \n",
       "617                   Nan Ya Plastic        南亚塑胶工业       中国台湾           TA  \n",
       "627                      Cheung Kong          长江集团       中国香港  HK)/中国大陆(CN  \n",
       "736                   Swire Pacific           太古集团       中国香港  HK)/中国大陆(CN  \n",
       "...                              ...           ...        ...          ...  \n",
       "1636                   Champion REIT           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1641                     Noble Group           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1661                   Taiwan Mobile           NaN       中国台湾           TA  \n",
       "1681                Evergreen Marine           NaN       中国台湾           TA  \n",
       "1692         China Southern Airlines           NaN       中国大陆           CN  \n",
       "1705                   Cosco Pacific           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1710        China Shipping Container           NaN       中国大陆           CN  \n",
       "1736  China Resources Power Holdings           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1739                Citic Securities           NaN       中国大陆           CN  \n",
       "1780             Far EasTone Telecom           NaN       中国台湾           TA  \n",
       "1786                 E.Sun Financial           NaN       中国台湾           TA  \n",
       "1824           Minmetals Development           NaN       中国大陆           CN  \n",
       "1840             Shanghai Automotive           NaN       中国大陆           CN  \n",
       "1846         HK Exchanges & Clearing           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1852                       Link REIT           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1860                 Kweichow Moutai           NaN       中国大陆           CN  \n",
       "1892             Yanzhou Coal Mining           NaN       中国大陆           CN  \n",
       "1908          China Shipping Develop           NaN       中国大陆           CN  \n",
       "1920                  Wing Lung Bank           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1922               Delta Electronics           NaN       中国台湾           TA  \n",
       "1945                  China Airlines           NaN       中国台湾           TA  \n",
       "1948                  Wing Hang Bank           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1959                            PCCW           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1960                            Benq           NaN       中国台湾           TA  \n",
       "1963                        TCL Corp           NaN       中国大陆           CN  \n",
       "1970                 Wuliangye Yibin           NaN       中国大陆           CN  \n",
       "1973                CNPC (Hong Kong)           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1975             K Wah International           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1986       China Overseas Land & Inv           NaN       中国香港  HK)/中国大陆(CN  \n",
       "1989     Nine Dragons Paper Holdings           NaN       中国香港  HK)/中国大陆(CN  \n",
       "\n",
       "[131 rows x 13 columns]"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007[df_2007['Country_cn'].str.contains('中国',regex=True)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2007</td>\n",
       "      <td>41</td>\n",
       "      <td>PetroChina /中国石油</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>68.43</td>\n",
       "      <td>16.53</td>\n",
       "      <td>96.42</td>\n",
       "      <td>208.76</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>中国石油</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2007</td>\n",
       "      <td>53</td>\n",
       "      <td>ICBC /中国工商银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>31.98</td>\n",
       "      <td>4.65</td>\n",
       "      <td>800.04</td>\n",
       "      <td>176.03</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2007</td>\n",
       "      <td>69</td>\n",
       "      <td>CCB-China Construction Bank /中国建设银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>23.18</td>\n",
       "      <td>5.84</td>\n",
       "      <td>568.21</td>\n",
       "      <td>126.55</td>\n",
       "      <td>CCB-China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2007</td>\n",
       "      <td>71</td>\n",
       "      <td>Sinopec-China Petroleum /中石化</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>99.03</td>\n",
       "      <td>5.07</td>\n",
       "      <td>65.83</td>\n",
       "      <td>93.57</td>\n",
       "      <td>Sinopec-China Petroleum</td>\n",
       "      <td>中石化</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2007</td>\n",
       "      <td>82</td>\n",
       "      <td>Bank of China /中国银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>23.10</td>\n",
       "      <td>3.41</td>\n",
       "      <td>585.55</td>\n",
       "      <td>143.80</td>\n",
       "      <td>Bank of China</td>\n",
       "      <td>中国银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2007</td>\n",
       "      <td>89</td>\n",
       "      <td>China Mobile /中国移动</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>29.79</td>\n",
       "      <td>6.56</td>\n",
       "      <td>51.35</td>\n",
       "      <td>185.31</td>\n",
       "      <td>China Mobile</td>\n",
       "      <td>中国移动</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>2007</td>\n",
       "      <td>176</td>\n",
       "      <td>Hutchison Whampoa/和记黄埔</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>多元化</td>\n",
       "      <td>23.55</td>\n",
       "      <td>1.85</td>\n",
       "      <td>74.97</td>\n",
       "      <td>40.57</td>\n",
       "      <td>Hutchison Whampoa</td>\n",
       "      <td>和记黄埔</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>2007</td>\n",
       "      <td>181</td>\n",
       "      <td>China Telecom/中国电信</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>20.98</td>\n",
       "      <td>3.46</td>\n",
       "      <td>50.34</td>\n",
       "      <td>37.50</td>\n",
       "      <td>China Telecom</td>\n",
       "      <td>中国电信</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>2007</td>\n",
       "      <td>243</td>\n",
       "      <td>China Life Insurance /中国人寿</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>保险</td>\n",
       "      <td>11.18</td>\n",
       "      <td>1.15</td>\n",
       "      <td>69.30</td>\n",
       "      <td>109.96</td>\n",
       "      <td>China Life Insurance</td>\n",
       "      <td>中国人寿</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>2007</td>\n",
       "      <td>308</td>\n",
       "      <td>Bank of Communications/中国交通银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>6.64</td>\n",
       "      <td>1.15</td>\n",
       "      <td>176.27</td>\n",
       "      <td>46.14</td>\n",
       "      <td>Bank of Communications</td>\n",
       "      <td>中国交通银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>2007</td>\n",
       "      <td>310</td>\n",
       "      <td>Taiwan Semiconductor/台积电</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>半导体</td>\n",
       "      <td>9.74</td>\n",
       "      <td>3.90</td>\n",
       "      <td>18.02</td>\n",
       "      <td>54.32</td>\n",
       "      <td>Taiwan Semiconductor</td>\n",
       "      <td>台积电</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>2007</td>\n",
       "      <td>341</td>\n",
       "      <td>Hon Hai Precision Ind /鸿海精密</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>27.78</td>\n",
       "      <td>1.24</td>\n",
       "      <td>13.99</td>\n",
       "      <td>34.83</td>\n",
       "      <td>Hon Hai Precision Ind</td>\n",
       "      <td>鸿海精密</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>2007</td>\n",
       "      <td>366</td>\n",
       "      <td>Baoshan Iron &amp; Steel /上海宝钢集团</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>15.63</td>\n",
       "      <td>1.57</td>\n",
       "      <td>17.59</td>\n",
       "      <td>21.42</td>\n",
       "      <td>Baoshan Iron &amp; Steel</td>\n",
       "      <td>上海宝钢集团</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>2007</td>\n",
       "      <td>389</td>\n",
       "      <td>Cathay Financial/国泰金融</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>保险</td>\n",
       "      <td>10.09</td>\n",
       "      <td>0.66</td>\n",
       "      <td>93.29</td>\n",
       "      <td>19.87</td>\n",
       "      <td>Cathay Financial</td>\n",
       "      <td>国泰金融</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>2007</td>\n",
       "      <td>395</td>\n",
       "      <td>Cnooc /中海油</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>8.51</td>\n",
       "      <td>3.10</td>\n",
       "      <td>14.22</td>\n",
       "      <td>34.94</td>\n",
       "      <td>Cnooc</td>\n",
       "      <td>中海油</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>2007</td>\n",
       "      <td>401</td>\n",
       "      <td>China Netcom Group /中国网通</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>10.69</td>\n",
       "      <td>1.70</td>\n",
       "      <td>24.70</td>\n",
       "      <td>15.70</td>\n",
       "      <td>China Netcom Group</td>\n",
       "      <td>中国网通</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>2007</td>\n",
       "      <td>423</td>\n",
       "      <td>China Shenhua Energy/中国神华能源股份有限公司</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>6.47</td>\n",
       "      <td>1.94</td>\n",
       "      <td>17.08</td>\n",
       "      <td>45.94</td>\n",
       "      <td>China Shenhua Energy</td>\n",
       "      <td>中国神华能源股份有限公司</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>2007</td>\n",
       "      <td>430</td>\n",
       "      <td>BOC Hong Kong/中银香港</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>4.13</td>\n",
       "      <td>1.74</td>\n",
       "      <td>106.03</td>\n",
       "      <td>25.58</td>\n",
       "      <td>BOC Hong Kong</td>\n",
       "      <td>中银香港</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2007</td>\n",
       "      <td>437</td>\n",
       "      <td>Formosa Petrochemical/台塑石化</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>13.56</td>\n",
       "      <td>1.74</td>\n",
       "      <td>12.35</td>\n",
       "      <td>19.28</td>\n",
       "      <td>Formosa Petrochemical</td>\n",
       "      <td>台塑石化</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2007</td>\n",
       "      <td>440</td>\n",
       "      <td>Ping An Insurance Group/平安保险</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>保险</td>\n",
       "      <td>7.95</td>\n",
       "      <td>0.52</td>\n",
       "      <td>39.62</td>\n",
       "      <td>39.60</td>\n",
       "      <td>Ping An Insurance Group</td>\n",
       "      <td>平安保险</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2007</td>\n",
       "      <td>452</td>\n",
       "      <td>Jardine Matheson/香港怡和集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>食品市场</td>\n",
       "      <td>11.96</td>\n",
       "      <td>1.25</td>\n",
       "      <td>18.34</td>\n",
       "      <td>13.59</td>\n",
       "      <td>Jardine Matheson</td>\n",
       "      <td>香港怡和集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>2007</td>\n",
       "      <td>511</td>\n",
       "      <td>Sun Hung Kai Properties /新鸿基房地产</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>3.30</td>\n",
       "      <td>2.56</td>\n",
       "      <td>29.72</td>\n",
       "      <td>29.49</td>\n",
       "      <td>Sun Hung Kai Properties</td>\n",
       "      <td>新鸿基房地产</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>2007</td>\n",
       "      <td>542</td>\n",
       "      <td>China Unicom /中国联通</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>10.67</td>\n",
       "      <td>0.60</td>\n",
       "      <td>17.63</td>\n",
       "      <td>16.03</td>\n",
       "      <td>China Unicom</td>\n",
       "      <td>中国联通</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>2007</td>\n",
       "      <td>552</td>\n",
       "      <td>CLP Holdings /中电控股</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>公用事业</td>\n",
       "      <td>5.87</td>\n",
       "      <td>1.27</td>\n",
       "      <td>16.42</td>\n",
       "      <td>17.65</td>\n",
       "      <td>CLP Holdings</td>\n",
       "      <td>中电控股</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575</th>\n",
       "      <td>2007</td>\n",
       "      <td>576</td>\n",
       "      <td>Chunghwa Telecom/中华电信</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>5.59</td>\n",
       "      <td>1.45</td>\n",
       "      <td>13.98</td>\n",
       "      <td>18.22</td>\n",
       "      <td>Chunghwa Telecom</td>\n",
       "      <td>中华电信</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>2007</td>\n",
       "      <td>601</td>\n",
       "      <td>China Steel/台湾中钢公司</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>材料</td>\n",
       "      <td>8.66</td>\n",
       "      <td>1.54</td>\n",
       "      <td>10.35</td>\n",
       "      <td>12.24</td>\n",
       "      <td>China Steel</td>\n",
       "      <td>台湾中钢公司</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>2007</td>\n",
       "      <td>604</td>\n",
       "      <td>China Merchants Bank/招商银行</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>3.53</td>\n",
       "      <td>0.46</td>\n",
       "      <td>90.76</td>\n",
       "      <td>33.19</td>\n",
       "      <td>China Merchants Bank</td>\n",
       "      <td>招商银行</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>2007</td>\n",
       "      <td>617</td>\n",
       "      <td>Nan Ya Plastic/南亚塑胶工业</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>化学制品</td>\n",
       "      <td>7.64</td>\n",
       "      <td>1.22</td>\n",
       "      <td>11.47</td>\n",
       "      <td>13.37</td>\n",
       "      <td>Nan Ya Plastic</td>\n",
       "      <td>南亚塑胶工业</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>2007</td>\n",
       "      <td>628</td>\n",
       "      <td>Cheung Kong/长江集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1.80</td>\n",
       "      <td>28.01</td>\n",
       "      <td>28.39</td>\n",
       "      <td>Cheung Kong</td>\n",
       "      <td>长江集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>736</th>\n",
       "      <td>2007</td>\n",
       "      <td>737</td>\n",
       "      <td>Swire Pacific /太古集团</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>多元化</td>\n",
       "      <td>2.44</td>\n",
       "      <td>2.42</td>\n",
       "      <td>16.05</td>\n",
       "      <td>17.32</td>\n",
       "      <td>Swire Pacific</td>\n",
       "      <td>太古集团</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1636</th>\n",
       "      <td>2007</td>\n",
       "      <td>1637</td>\n",
       "      <td>Champion REIT</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.16</td>\n",
       "      <td>2.95</td>\n",
       "      <td>1.54</td>\n",
       "      <td>Champion REIT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>2007</td>\n",
       "      <td>1642</td>\n",
       "      <td>Noble Group</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>13.75</td>\n",
       "      <td>0.13</td>\n",
       "      <td>3.81</td>\n",
       "      <td>2.14</td>\n",
       "      <td>Noble Group</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>2007</td>\n",
       "      <td>1662</td>\n",
       "      <td>Taiwan Mobile</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>1.81</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3.59</td>\n",
       "      <td>4.84</td>\n",
       "      <td>Taiwan Mobile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1681</th>\n",
       "      <td>2007</td>\n",
       "      <td>1682</td>\n",
       "      <td>Evergreen Marine</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>运输</td>\n",
       "      <td>4.29</td>\n",
       "      <td>0.37</td>\n",
       "      <td>3.96</td>\n",
       "      <td>1.90</td>\n",
       "      <td>Evergreen Marine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1692</th>\n",
       "      <td>2007</td>\n",
       "      <td>1693</td>\n",
       "      <td>China Southern Airlines</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>4.64</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>8.84</td>\n",
       "      <td>1.97</td>\n",
       "      <td>China Southern Airlines</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1705</th>\n",
       "      <td>2007</td>\n",
       "      <td>1706</td>\n",
       "      <td>Cosco Pacific</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.34</td>\n",
       "      <td>2.85</td>\n",
       "      <td>5.94</td>\n",
       "      <td>Cosco Pacific</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1710</th>\n",
       "      <td>2007</td>\n",
       "      <td>1711</td>\n",
       "      <td>China Shipping Container</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>3.52</td>\n",
       "      <td>0.44</td>\n",
       "      <td>3.59</td>\n",
       "      <td>2.26</td>\n",
       "      <td>China Shipping Container</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1736</th>\n",
       "      <td>2007</td>\n",
       "      <td>1737</td>\n",
       "      <td>China Resources Power Holdings</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>公用事业</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.37</td>\n",
       "      <td>3.67</td>\n",
       "      <td>5.37</td>\n",
       "      <td>China Resources Power Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1739</th>\n",
       "      <td>2007</td>\n",
       "      <td>1740</td>\n",
       "      <td>Citic Securities</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.52</td>\n",
       "      <td>14.29</td>\n",
       "      <td>Citic Securities</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1780</th>\n",
       "      <td>2007</td>\n",
       "      <td>1781</td>\n",
       "      <td>Far EasTone Telecom</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>2.19</td>\n",
       "      <td>0.45</td>\n",
       "      <td>3.01</td>\n",
       "      <td>4.45</td>\n",
       "      <td>Far EasTone Telecom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1786</th>\n",
       "      <td>2007</td>\n",
       "      <td>1787</td>\n",
       "      <td>E.Sun Financial</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.14</td>\n",
       "      <td>19.36</td>\n",
       "      <td>2.19</td>\n",
       "      <td>E.Sun Financial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2007</td>\n",
       "      <td>1825</td>\n",
       "      <td>Minmetals Development</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>贸易公司</td>\n",
       "      <td>8.25</td>\n",
       "      <td>0.04</td>\n",
       "      <td>3.46</td>\n",
       "      <td>1.50</td>\n",
       "      <td>Minmetals Development</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1840</th>\n",
       "      <td>2007</td>\n",
       "      <td>1841</td>\n",
       "      <td>Shanghai Automotive</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>耐用消费品</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.81</td>\n",
       "      <td>11.10</td>\n",
       "      <td>Shanghai Automotive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1846</th>\n",
       "      <td>2007</td>\n",
       "      <td>1847</td>\n",
       "      <td>HK Exchanges &amp; Clearing</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.17</td>\n",
       "      <td>2.96</td>\n",
       "      <td>10.97</td>\n",
       "      <td>HK Exchanges &amp; Clearing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1852</th>\n",
       "      <td>2007</td>\n",
       "      <td>1853</td>\n",
       "      <td>Link REIT</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.27</td>\n",
       "      <td>5.24</td>\n",
       "      <td>5.00</td>\n",
       "      <td>Link REIT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1860</th>\n",
       "      <td>2007</td>\n",
       "      <td>1861</td>\n",
       "      <td>Kweichow Moutai</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10.69</td>\n",
       "      <td>Kweichow Moutai</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>2007</td>\n",
       "      <td>1892</td>\n",
       "      <td>Yanzhou Coal Mining</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>1.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>2.63</td>\n",
       "      <td>4.52</td>\n",
       "      <td>Yanzhou Coal Mining</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1908</th>\n",
       "      <td>2007</td>\n",
       "      <td>1909</td>\n",
       "      <td>China Shipping Develop</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>运输</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.66</td>\n",
       "      <td>4.61</td>\n",
       "      <td>China Shipping Develop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1920</th>\n",
       "      <td>2007</td>\n",
       "      <td>1920</td>\n",
       "      <td>Wing Lung Bank</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.21</td>\n",
       "      <td>10.92</td>\n",
       "      <td>2.43</td>\n",
       "      <td>Wing Lung Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1922</th>\n",
       "      <td>2007</td>\n",
       "      <td>1923</td>\n",
       "      <td>Delta Electronics</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>2.46</td>\n",
       "      <td>0.23</td>\n",
       "      <td>2.49</td>\n",
       "      <td>6.40</td>\n",
       "      <td>Delta Electronics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945</th>\n",
       "      <td>2007</td>\n",
       "      <td>1946</td>\n",
       "      <td>China Airlines</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>运输</td>\n",
       "      <td>3.61</td>\n",
       "      <td>0.02</td>\n",
       "      <td>7.63</td>\n",
       "      <td>1.85</td>\n",
       "      <td>China Airlines</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948</th>\n",
       "      <td>2007</td>\n",
       "      <td>1949</td>\n",
       "      <td>Wing Hang Bank</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.17</td>\n",
       "      <td>13.45</td>\n",
       "      <td>3.33</td>\n",
       "      <td>Wing Hang Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959</th>\n",
       "      <td>2007</td>\n",
       "      <td>1959</td>\n",
       "      <td>PCCW</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td>2.90</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6.87</td>\n",
       "      <td>3.98</td>\n",
       "      <td>PCCW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1960</th>\n",
       "      <td>2007</td>\n",
       "      <td>1961</td>\n",
       "      <td>Benq</td>\n",
       "      <td>中国台湾(TA)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>5.39</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>5.04</td>\n",
       "      <td>1.27</td>\n",
       "      <td>Benq</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>CN-TA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>2007</td>\n",
       "      <td>1964</td>\n",
       "      <td>TCL Corp</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>技术硬件和装备</td>\n",
       "      <td>6.40</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1.39</td>\n",
       "      <td>TCL Corp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>2007</td>\n",
       "      <td>1971</td>\n",
       "      <td>Wuliangye Yibin</td>\n",
       "      <td>中国大陆(CN)</td>\n",
       "      <td>食品、饮料和烟草</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.19</td>\n",
       "      <td>8.81</td>\n",
       "      <td>Wuliangye Yibin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>CN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>2007</td>\n",
       "      <td>1974</td>\n",
       "      <td>CNPC (Hong Kong)</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.47</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.30</td>\n",
       "      <td>CNPC (Hong Kong)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>2007</td>\n",
       "      <td>1976</td>\n",
       "      <td>K Wah International</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.47</td>\n",
       "      <td>1.29</td>\n",
       "      <td>0.98</td>\n",
       "      <td>K Wah International</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>2007</td>\n",
       "      <td>1987</td>\n",
       "      <td>China Overseas Land &amp; Inv</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.20</td>\n",
       "      <td>3.24</td>\n",
       "      <td>7.05</td>\n",
       "      <td>China Overseas Land &amp; Inv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>2007</td>\n",
       "      <td>1989</td>\n",
       "      <td>Nine Dragons Paper Holdings</td>\n",
       "      <td>中国香港(HK)/中国大陆(CN)</td>\n",
       "      <td>材料</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.86</td>\n",
       "      <td>8.61</td>\n",
       "      <td>Nine Dragons Paper Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>CN-HK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank                        Company_cn_en      Country_cn_en  \\\n",
       "40    2007    41                     PetroChina /中国石油           中国大陆(CN)   \n",
       "52    2007    53                         ICBC /中国工商银行           中国大陆(CN)   \n",
       "68    2007    69  CCB-China Construction Bank /中国建设银行           中国大陆(CN)   \n",
       "70    2007    71         Sinopec-China Petroleum /中石化           中国大陆(CN)   \n",
       "81    2007    82                  Bank of China /中国银行           中国大陆(CN)   \n",
       "88    2007    89                   China Mobile /中国移动  中国香港(HK)/中国大陆(CN)   \n",
       "175   2007   176               Hutchison Whampoa/和记黄埔  中国香港(HK)/中国大陆(CN)   \n",
       "180   2007   181                   China Telecom/中国电信           中国大陆(CN)   \n",
       "242   2007   243           China Life Insurance /中国人寿           中国大陆(CN)   \n",
       "307   2007   308        Bank of Communications/中国交通银行           中国大陆(CN)   \n",
       "309   2007   310             Taiwan Semiconductor/台积电           中国台湾(TA)   \n",
       "340   2007   341          Hon Hai Precision Ind /鸿海精密           中国台湾(TA)   \n",
       "365   2007   366         Baoshan Iron & Steel /上海宝钢集团           中国大陆(CN)   \n",
       "388   2007   389                Cathay Financial/国泰金融           中国台湾(TA)   \n",
       "394   2007   395                           Cnooc /中海油  中国香港(HK)/中国大陆(CN)   \n",
       "400   2007   401             China Netcom Group /中国网通  中国香港(HK)/中国大陆(CN)   \n",
       "422   2007   423    China Shenhua Energy/中国神华能源股份有限公司           中国大陆(CN)   \n",
       "429   2007   430                   BOC Hong Kong/中银香港  中国香港(HK)/中国大陆(CN)   \n",
       "436   2007   437           Formosa Petrochemical/台塑石化           中国台湾(TA)   \n",
       "439   2007   440         Ping An Insurance Group/平安保险           中国大陆(CN)   \n",
       "451   2007   452              Jardine Matheson/香港怡和集团  中国香港(HK)/中国大陆(CN)   \n",
       "510   2007   511      Sun Hung Kai Properties /新鸿基房地产  中国香港(HK)/中国大陆(CN)   \n",
       "541   2007   542                   China Unicom /中国联通  中国香港(HK)/中国大陆(CN)   \n",
       "551   2007   552                   CLP Holdings /中电控股  中国香港(HK)/中国大陆(CN)   \n",
       "575   2007   576                Chunghwa Telecom/中华电信           中国台湾(TA)   \n",
       "600   2007   601                   China Steel/台湾中钢公司           中国台湾(TA)   \n",
       "603   2007   604            China Merchants Bank/招商银行           中国大陆(CN)   \n",
       "617   2007   617                Nan Ya Plastic/南亚塑胶工业           中国台湾(TA)   \n",
       "627   2007   628                     Cheung Kong/长江集团  中国香港(HK)/中国大陆(CN)   \n",
       "736   2007   737                  Swire Pacific /太古集团  中国香港(HK)/中国大陆(CN)   \n",
       "...    ...   ...                                  ...                ...   \n",
       "1636  2007  1637                        Champion REIT  中国香港(HK)/中国大陆(CN)   \n",
       "1641  2007  1642                          Noble Group  中国香港(HK)/中国大陆(CN)   \n",
       "1661  2007  1662                        Taiwan Mobile           中国台湾(TA)   \n",
       "1681  2007  1682                     Evergreen Marine           中国台湾(TA)   \n",
       "1692  2007  1693              China Southern Airlines           中国大陆(CN)   \n",
       "1705  2007  1706                        Cosco Pacific  中国香港(HK)/中国大陆(CN)   \n",
       "1710  2007  1711             China Shipping Container           中国大陆(CN)   \n",
       "1736  2007  1737       China Resources Power Holdings  中国香港(HK)/中国大陆(CN)   \n",
       "1739  2007  1740                     Citic Securities           中国大陆(CN)   \n",
       "1780  2007  1781                  Far EasTone Telecom           中国台湾(TA)   \n",
       "1786  2007  1787                      E.Sun Financial           中国台湾(TA)   \n",
       "1824  2007  1825                Minmetals Development           中国大陆(CN)   \n",
       "1840  2007  1841                  Shanghai Automotive           中国大陆(CN)   \n",
       "1846  2007  1847              HK Exchanges & Clearing  中国香港(HK)/中国大陆(CN)   \n",
       "1852  2007  1853                            Link REIT  中国香港(HK)/中国大陆(CN)   \n",
       "1860  2007  1861                      Kweichow Moutai           中国大陆(CN)   \n",
       "1892  2007  1892                  Yanzhou Coal Mining           中国大陆(CN)   \n",
       "1908  2007  1909               China Shipping Develop           中国大陆(CN)   \n",
       "1920  2007  1920                       Wing Lung Bank  中国香港(HK)/中国大陆(CN)   \n",
       "1922  2007  1923                    Delta Electronics           中国台湾(TA)   \n",
       "1945  2007  1946                       China Airlines           中国台湾(TA)   \n",
       "1948  2007  1949                       Wing Hang Bank  中国香港(HK)/中国大陆(CN)   \n",
       "1959  2007  1959                                 PCCW  中国香港(HK)/中国大陆(CN)   \n",
       "1960  2007  1961                                 Benq           中国台湾(TA)   \n",
       "1963  2007  1964                             TCL Corp           中国大陆(CN)   \n",
       "1970  2007  1971                      Wuliangye Yibin           中国大陆(CN)   \n",
       "1973  2007  1974                     CNPC (Hong Kong)  中国香港(HK)/中国大陆(CN)   \n",
       "1975  2007  1976                  K Wah International  中国香港(HK)/中国大陆(CN)   \n",
       "1986  2007  1987            China Overseas Land & Inv  中国香港(HK)/中国大陆(CN)   \n",
       "1989  2007  1989          Nine Dragons Paper Holdings  中国香港(HK)/中国大陆(CN)   \n",
       "\n",
       "     Industry_cn  Sales  Profits  Assets  Market_value  \\\n",
       "40            炼油  68.43    16.53   96.42        208.76   \n",
       "52            银行  31.98     4.65  800.04        176.03   \n",
       "68            银行  23.18     5.84  568.21        126.55   \n",
       "70            炼油  99.03     5.07   65.83         93.57   \n",
       "81            银行  23.10     3.41  585.55        143.80   \n",
       "88         电信运营商  29.79     6.56   51.35        185.31   \n",
       "175          多元化  23.55     1.85   74.97         40.57   \n",
       "180        电信运营商  20.98     3.46   50.34         37.50   \n",
       "242           保险  11.18     1.15   69.30        109.96   \n",
       "307           银行   6.64     1.15  176.27         46.14   \n",
       "309          半导体   9.74     3.90   18.02         54.32   \n",
       "340      技术硬件和装备  27.78     1.24   13.99         34.83   \n",
       "365           材料  15.63     1.57   17.59         21.42   \n",
       "388           保险  10.09     0.66   93.29         19.87   \n",
       "394           炼油   8.51     3.10   14.22         34.94   \n",
       "400        电信运营商  10.69     1.70   24.70         15.70   \n",
       "422           材料   6.47     1.94   17.08         45.94   \n",
       "429           银行   4.13     1.74  106.03         25.58   \n",
       "436           炼油  13.56     1.74   12.35         19.28   \n",
       "439           保险   7.95     0.52   39.62         39.60   \n",
       "451         食品市场  11.96     1.25   18.34         13.59   \n",
       "510         综合金融   3.30     2.56   29.72         29.49   \n",
       "541        电信运营商  10.67     0.60   17.63         16.03   \n",
       "551         公用事业   5.87     1.27   16.42         17.65   \n",
       "575        电信运营商   5.59     1.45   13.98         18.22   \n",
       "600           材料   8.66     1.54   10.35         12.24   \n",
       "603           银行   3.53     0.46   90.76         33.19   \n",
       "617         化学制品   7.64     1.22   11.47         13.37   \n",
       "627         综合金融   0.80     1.80   28.01         28.39   \n",
       "736          多元化   2.44     2.42   16.05         17.32   \n",
       "...          ...    ...      ...     ...           ...   \n",
       "1636        综合金融   0.05     1.16    2.95          1.54   \n",
       "1641          运输  13.75     0.13    3.81          2.14   \n",
       "1661       电信运营商   1.81     0.50    3.59          4.84   \n",
       "1681          运输   4.29     0.37    3.96          1.90   \n",
       "1692          运输   4.64    -0.23    8.84          1.97   \n",
       "1705          运输   0.30     0.34    2.85          5.94   \n",
       "1710          运输   3.52     0.44    3.59          2.26   \n",
       "1736        公用事业   0.76     0.37    3.67          5.37   \n",
       "1739        综合金融   0.14     0.04    2.52         14.29   \n",
       "1780       电信运营商   2.19     0.45    3.01          4.45   \n",
       "1786          银行   0.73     0.14   19.36          2.19   \n",
       "1824        贸易公司   8.25     0.04    3.46          1.50   \n",
       "1840       耐用消费品   0.79     0.14    1.81         11.10   \n",
       "1846        综合金融   0.35     0.17    2.96         10.97   \n",
       "1852        综合金融   0.43     0.27    5.24          5.00   \n",
       "1860    食品、饮料和烟草   0.43     0.14    1.00         10.69   \n",
       "1892          材料   1.43     0.36    2.63          4.52   \n",
       "1908          运输   1.06     0.33    1.66          4.61   \n",
       "1920          银行   0.66     0.21   10.92          2.43   \n",
       "1922     技术硬件和装备   2.46     0.23    2.49          6.40   \n",
       "1945          运输   3.61     0.02    7.63          1.85   \n",
       "1948          银行   0.66     0.17   13.45          3.33   \n",
       "1959       电信运营商   2.90     0.21    6.87          3.98   \n",
       "1960     技术硬件和装备   5.39    -0.16    5.04          1.27   \n",
       "1963     技术硬件和装备   6.40    -0.04    3.77          1.39   \n",
       "1970    食品、饮料和烟草   0.70     0.10    1.19          8.81   \n",
       "1973          炼油   0.44     0.47    2.07          2.30   \n",
       "1975        综合金融   0.04     0.47    1.29          0.98   \n",
       "1986        综合金融   0.90     0.20    3.24          7.05   \n",
       "1989          材料   0.99     0.17    1.86          8.61   \n",
       "\n",
       "                          Company_en    Company_cn Country_cn Country_en  \n",
       "40                       PetroChina           中国石油       中国大陆         CN  \n",
       "52                             ICBC         中国工商银行       中国大陆         CN  \n",
       "68      CCB-China Construction Bank         中国建设银行       中国大陆         CN  \n",
       "70          Sinopec-China Petroleum            中石化       中国大陆         CN  \n",
       "81                    Bank of China           中国银行       中国大陆         CN  \n",
       "88                     China Mobile           中国移动       中国香港      CN-HK  \n",
       "175                Hutchison Whampoa          和记黄埔       中国香港      CN-HK  \n",
       "180                    China Telecom          中国电信       中国大陆         CN  \n",
       "242            China Life Insurance           中国人寿       中国大陆         CN  \n",
       "307           Bank of Communications        中国交通银行       中国大陆         CN  \n",
       "309             Taiwan Semiconductor           台积电       中国台湾      CN-TA  \n",
       "340           Hon Hai Precision Ind           鸿海精密       中国台湾      CN-TA  \n",
       "365            Baoshan Iron & Steel         上海宝钢集团       中国大陆         CN  \n",
       "388                 Cathay Financial          国泰金融       中国台湾      CN-TA  \n",
       "394                           Cnooc            中海油       中国香港      CN-HK  \n",
       "400              China Netcom Group           中国网通       中国香港      CN-HK  \n",
       "422             China Shenhua Energy  中国神华能源股份有限公司       中国大陆         CN  \n",
       "429                    BOC Hong Kong          中银香港       中国香港      CN-HK  \n",
       "436            Formosa Petrochemical          台塑石化       中国台湾      CN-TA  \n",
       "439          Ping An Insurance Group          平安保险       中国大陆         CN  \n",
       "451                 Jardine Matheson        香港怡和集团       中国香港      CN-HK  \n",
       "510         Sun Hung Kai Properties         新鸿基房地产       中国香港      CN-HK  \n",
       "541                    China Unicom           中国联通       中国香港      CN-HK  \n",
       "551                    CLP Holdings           中电控股       中国香港      CN-HK  \n",
       "575                 Chunghwa Telecom          中华电信       中国台湾      CN-TA  \n",
       "600                      China Steel        台湾中钢公司       中国台湾      CN-TA  \n",
       "603             China Merchants Bank          招商银行       中国大陆         CN  \n",
       "617                   Nan Ya Plastic        南亚塑胶工业       中国台湾      CN-TA  \n",
       "627                      Cheung Kong          长江集团       中国香港      CN-HK  \n",
       "736                   Swire Pacific           太古集团       中国香港      CN-HK  \n",
       "...                              ...           ...        ...        ...  \n",
       "1636                   Champion REIT           NaN       中国香港      CN-HK  \n",
       "1641                     Noble Group           NaN       中国香港      CN-HK  \n",
       "1661                   Taiwan Mobile           NaN       中国台湾      CN-TA  \n",
       "1681                Evergreen Marine           NaN       中国台湾      CN-TA  \n",
       "1692         China Southern Airlines           NaN       中国大陆         CN  \n",
       "1705                   Cosco Pacific           NaN       中国香港      CN-HK  \n",
       "1710        China Shipping Container           NaN       中国大陆         CN  \n",
       "1736  China Resources Power Holdings           NaN       中国香港      CN-HK  \n",
       "1739                Citic Securities           NaN       中国大陆         CN  \n",
       "1780             Far EasTone Telecom           NaN       中国台湾      CN-TA  \n",
       "1786                 E.Sun Financial           NaN       中国台湾      CN-TA  \n",
       "1824           Minmetals Development           NaN       中国大陆         CN  \n",
       "1840             Shanghai Automotive           NaN       中国大陆         CN  \n",
       "1846         HK Exchanges & Clearing           NaN       中国香港      CN-HK  \n",
       "1852                       Link REIT           NaN       中国香港      CN-HK  \n",
       "1860                 Kweichow Moutai           NaN       中国大陆         CN  \n",
       "1892             Yanzhou Coal Mining           NaN       中国大陆         CN  \n",
       "1908          China Shipping Develop           NaN       中国大陆         CN  \n",
       "1920                  Wing Lung Bank           NaN       中国香港      CN-HK  \n",
       "1922               Delta Electronics           NaN       中国台湾      CN-TA  \n",
       "1945                  China Airlines           NaN       中国台湾      CN-TA  \n",
       "1948                  Wing Hang Bank           NaN       中国香港      CN-HK  \n",
       "1959                            PCCW           NaN       中国香港      CN-HK  \n",
       "1960                            Benq           NaN       中国台湾      CN-TA  \n",
       "1963                        TCL Corp           NaN       中国大陆         CN  \n",
       "1970                 Wuliangye Yibin           NaN       中国大陆         CN  \n",
       "1973                CNPC (Hong Kong)           NaN       中国香港      CN-HK  \n",
       "1975             K Wah International           NaN       中国香港      CN-HK  \n",
       "1986       China Overseas Land & Inv           NaN       中国香港      CN-HK  \n",
       "1989     Nine Dragons Paper Holdings           NaN       中国香港      CN-HK  \n",
       "\n",
       "[131 rows x 13 columns]"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Country_en'] = df_2007['Country_en'].replace(['HK.*','TA'],['CN-HK', 'CN-TA'],regex=True)\n",
    "df_2007[df_2007['Country_en'].str.contains('CN',regex=True)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 考虑到其他年份，公司所在行业有用英文名称展示的，这里添加一列英文的行业名称，但内容是空白"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>2007</td>\n",
       "      <td>1995</td>\n",
       "      <td>Fremont General</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.17</td>\n",
       "      <td>12.80</td>\n",
       "      <td>0.69</td>\n",
       "      <td>Fremont General</td>\n",
       "      <td>NaN</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>2007</td>\n",
       "      <td>1997</td>\n",
       "      <td>United Rentals</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>商业服务和供应</td>\n",
       "      <td>3.64</td>\n",
       "      <td>0.22</td>\n",
       "      <td>5.37</td>\n",
       "      <td>2.32</td>\n",
       "      <td>United Rentals</td>\n",
       "      <td>NaN</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>2007</td>\n",
       "      <td>1998</td>\n",
       "      <td>CBOT Holdings</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>综合金融</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.81</td>\n",
       "      <td>8.54</td>\n",
       "      <td>CBOT Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>2007</td>\n",
       "      <td>1998</td>\n",
       "      <td>Singapore Petroleum</td>\n",
       "      <td>新加坡(SI)</td>\n",
       "      <td>炼油</td>\n",
       "      <td>5.59</td>\n",
       "      <td>0.19</td>\n",
       "      <td>2.05</td>\n",
       "      <td>1.50</td>\n",
       "      <td>Singapore Petroleum</td>\n",
       "      <td>NaN</td>\n",
       "      <td>新加坡</td>\n",
       "      <td>SI</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>2007</td>\n",
       "      <td>2000</td>\n",
       "      <td>DVB Bank</td>\n",
       "      <td>德国(GE)</td>\n",
       "      <td>银行</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.06</td>\n",
       "      <td>12.74</td>\n",
       "      <td>1.26</td>\n",
       "      <td>DVB Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td>德国</td>\n",
       "      <td>GE</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year  Rank        Company_cn_en Country_cn_en Industry_cn  Sales  \\\n",
       "1995  2007  1995      Fremont General        美国(US)        综合金融   1.25   \n",
       "1996  2007  1997       United Rentals        美国(US)     商业服务和供应   3.64   \n",
       "1997  2007  1998        CBOT Holdings        美国(US)        综合金融   0.64   \n",
       "1998  2007  1998  Singapore Petroleum       新加坡(SI)          炼油   5.59   \n",
       "1999  2007  2000             DVB Bank        德国(GE)          银行   0.77   \n",
       "\n",
       "      Profits  Assets  Market_value           Company_en Company_cn  \\\n",
       "1995     0.17   12.80          0.69      Fremont General        NaN   \n",
       "1996     0.22    5.37          2.32       United Rentals        NaN   \n",
       "1997     0.17    0.81          8.54        CBOT Holdings        NaN   \n",
       "1998     0.19    2.05          1.50  Singapore Petroleum        NaN   \n",
       "1999     0.06   12.74          1.26             DVB Bank        NaN   \n",
       "\n",
       "     Country_cn Country_en Industry_en  \n",
       "1995         美国         US              \n",
       "1996         美国         US              \n",
       "1997         美国         US              \n",
       "1998        新加坡         SI              \n",
       "1999         德国         GE              "
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007['Industry_en'] = ''\n",
    "df_2007.tail(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **将列名进行重新排序**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "columns_sort = ['Year', 'Rank', 'Company_cn_en','Company_en',\n",
    "                'Company_cn', 'Country_cn_en', 'Country_cn', \n",
    "                'Country_en', 'Industry_cn', 'Industry_en',\n",
    "                'Sales', 'Profits', 'Assets', 'Market_value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>Citigroup /花旗集团</td>\n",
       "      <td>Citigroup</td>\n",
       "      <td>花旗集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>146.56</td>\n",
       "      <td>21.54</td>\n",
       "      <td>1884.32</td>\n",
       "      <td>247.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>Bank of America /美国银行</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>116.57</td>\n",
       "      <td>21.13</td>\n",
       "      <td>1459.74</td>\n",
       "      <td>226.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>HSBC Holdings/汇丰集团</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>121.51</td>\n",
       "      <td>16.63</td>\n",
       "      <td>1860.76</td>\n",
       "      <td>202.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank          Company_cn_en        Company_en Company_cn  \\\n",
       "0  2007     1        Citigroup /花旗集团        Citigroup        花旗集团   \n",
       "1  2007     2  Bank of America /美国银行  Bank of America        美国银行   \n",
       "2  2007     3     HSBC Holdings/汇丰集团     HSBC Holdings       汇丰集团   \n",
       "\n",
       "  Country_cn_en Country_cn Country_en Industry_cn Industry_en   Sales  \\\n",
       "0        美国(US)         美国         US          银行              146.56   \n",
       "1        美国(US)         美国         US          银行              116.57   \n",
       "2        英国(UK)         英国         UK          银行              121.51   \n",
       "\n",
       "   Profits   Assets  Market_value  \n",
       "0    21.54  1884.32        247.42  \n",
       "1    21.13  1459.74        226.61  \n",
       "2    16.63  1860.76        202.29  "
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按指定list重新将columns进行排序\n",
    "df_2007 = df_2007.reindex(columns=columns_sort)\n",
    "print(df_2007.shape)\n",
    "print(df_2007.dtypes)\n",
    "df_2007.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2008"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 10)\n",
      "年份                         int64\n",
      "Rank                       int64\n",
      "公司名称（英文）                  object\n",
      "公司名称（中文）                  object\n",
      "Country/area（国家或地区）       object\n",
      "Industry（行业）              object\n",
      "Sales （销售额）($bil十亿美元)     object\n",
      "Profits （利润）($bil)        object\n",
      "Assets 资产($bil)           object\n",
      "Market Value 市值($bil)    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>Rank</th>\n",
       "      <th>公司名称（英文）</th>\n",
       "      <th>公司名称（中文）</th>\n",
       "      <th>Country/area（国家或地区）</th>\n",
       "      <th>Industry（行业）</th>\n",
       "      <th>Sales （销售额）($bil十亿美元)</th>\n",
       "      <th>Profits （利润）($bil)</th>\n",
       "      <th>Assets 资产($bil)</th>\n",
       "      <th>Market Value 市值($bil)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Banking</td>\n",
       "      <td>146.5</td>\n",
       "      <td>19.13</td>\n",
       "      <td>2,348.98</td>\n",
       "      <td>180.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>172.74</td>\n",
       "      <td>22.21</td>\n",
       "      <td>795.34</td>\n",
       "      <td>330.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>3</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>119.19</td>\n",
       "      <td>14.98</td>\n",
       "      <td>1,715.75</td>\n",
       "      <td>176.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>116.35</td>\n",
       "      <td>15.37</td>\n",
       "      <td>1,562.15</td>\n",
       "      <td>136.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>5</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>358.6</td>\n",
       "      <td>40.61</td>\n",
       "      <td>242.08</td>\n",
       "      <td>465.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份  Rank          公司名称（英文） 公司名称（中文） Country/area（国家或地区）  \\\n",
       "0  2008     1     HSBC Holdings     汇丰集团      United Kingdom   \n",
       "1  2008     2  General Electric   通用电气公司       United States   \n",
       "2  2008     3   Bank of America     美国银行       United States   \n",
       "3  2008     4    JPMorgan Chase   摩根大通公司       United States   \n",
       "4  2008     5        ExxonMobil  埃克森美孚公司       United States   \n",
       "\n",
       "           Industry（行业） Sales （销售额）($bil十亿美元) Profits （利润）($bil)  \\\n",
       "0               Banking                 146.5              19.13   \n",
       "1         Conglomerates                172.74              22.21   \n",
       "2               Banking                119.19              14.98   \n",
       "3               Banking                116.35              15.37   \n",
       "4  Oil & Gas Operations                 358.6              40.61   \n",
       "\n",
       "  Assets 资产($bil)  Market Value 市值($bil)  \n",
       "0        2,348.98                 180.81  \n",
       "1          795.34                 330.93  \n",
       "2        1,715.75                 176.53  \n",
       "3        1,562.15                 136.88  \n",
       "4          242.08                 465.51  "
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2008 = pd.read_csv('./data/data_forbes_2008.csv', encoding='gbk', thousands=',')\n",
    "print('the shape of DataFrame: ', df_2008.shape)\n",
    "print(df_2008.dtypes)\n",
    "df_2008.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 更新columns的名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Banking</td>\n",
       "      <td>146.5</td>\n",
       "      <td>19.13</td>\n",
       "      <td>2,348.98</td>\n",
       "      <td>180.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>172.74</td>\n",
       "      <td>22.21</td>\n",
       "      <td>795.34</td>\n",
       "      <td>330.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>3</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>119.19</td>\n",
       "      <td>14.98</td>\n",
       "      <td>1,715.75</td>\n",
       "      <td>176.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>116.35</td>\n",
       "      <td>15.37</td>\n",
       "      <td>1,562.15</td>\n",
       "      <td>136.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>5</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>358.6</td>\n",
       "      <td>40.61</td>\n",
       "      <td>242.08</td>\n",
       "      <td>465.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank        Company_en Company_cn      Country_en  \\\n",
       "0  2008     1     HSBC Holdings       汇丰集团  United Kingdom   \n",
       "1  2008     2  General Electric     通用电气公司   United States   \n",
       "2  2008     3   Bank of America       美国银行   United States   \n",
       "3  2008     4    JPMorgan Chase     摩根大通公司   United States   \n",
       "4  2008     5        ExxonMobil    埃克森美孚公司   United States   \n",
       "\n",
       "            Industry_en   Sales Profits    Assets  Market_value  \n",
       "0               Banking   146.5   19.13  2,348.98        180.81  \n",
       "1         Conglomerates  172.74   22.21    795.34        330.93  \n",
       "2               Banking  119.19   14.98  1,715.75        176.53  \n",
       "3               Banking  116.35   15.37  1,562.15        136.88  \n",
       "4  Oil & Gas Operations   358.6   40.61    242.08        465.51  "
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2008.columns = ['Year', 'Rank', 'Company_en', 'Company_cn','Country_en', 'Industry_en', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2008.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加空白列，使之与其他年份的格式保持一致"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Banking</td>\n",
       "      <td>146.5</td>\n",
       "      <td>19.13</td>\n",
       "      <td>2,348.98</td>\n",
       "      <td>180.81</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>172.74</td>\n",
       "      <td>22.21</td>\n",
       "      <td>795.34</td>\n",
       "      <td>330.93</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>3</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>119.19</td>\n",
       "      <td>14.98</td>\n",
       "      <td>1,715.75</td>\n",
       "      <td>176.53</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>116.35</td>\n",
       "      <td>15.37</td>\n",
       "      <td>1,562.15</td>\n",
       "      <td>136.88</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>5</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>358.6</td>\n",
       "      <td>40.61</td>\n",
       "      <td>242.08</td>\n",
       "      <td>465.51</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank        Company_en Company_cn      Country_en  \\\n",
       "0  2008     1     HSBC Holdings       汇丰集团  United Kingdom   \n",
       "1  2008     2  General Electric     通用电气公司   United States   \n",
       "2  2008     3   Bank of America       美国银行   United States   \n",
       "3  2008     4    JPMorgan Chase     摩根大通公司   United States   \n",
       "4  2008     5        ExxonMobil    埃克森美孚公司   United States   \n",
       "\n",
       "            Industry_en   Sales Profits    Assets  Market_value Company_cn_en  \\\n",
       "0               Banking   146.5   19.13  2,348.98        180.81                 \n",
       "1         Conglomerates  172.74   22.21    795.34        330.93                 \n",
       "2               Banking  119.19   14.98  1,715.75        176.53                 \n",
       "3               Banking  116.35   15.37  1,562.15        136.88                 \n",
       "4  Oil & Gas Operations   358.6   40.61    242.08        465.51                 \n",
       "\n",
       "  Country_cn_en Country_cn Industry_cn  \n",
       "0                                       \n",
       "1                                       \n",
       "2                                       \n",
       "3                                       \n",
       "4                                       "
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2008['Company_cn_en'], df_2008['Country_cn_en'], df_2008['Country_cn'], df_2008['Industry_cn'] = ['','','','']\n",
    "df_2008.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "col_digit = ['Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "for col in col_digit:\n",
    "    # 将数字后面的字母进行替换\n",
    "    df_2008[col] = df_2008[col].replace('([A-Za-z])', '', regex=True)\n",
    "\n",
    "    # 千分位数字的逗号被识别为string了，需要替换\n",
    "    df_2008[col] = df_2008[col].replace(',', '', regex=True)\n",
    "    \n",
    "    #将数字型字符串转换为可进行计算的数据类型\n",
    "    df_2008[col] = pd.to_numeric(df_2008[col])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# df_2008['Sales'] = pd.to_numeric(df_2008['Sales'])\n",
    "# df_2008['Profits'] = pd.to_numeric(df_2008['Profits'])\n",
    "# df_2008['Assets'] = pd.to_numeric(df_2008['Assets'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 按指定list重新将columns进行排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>146.50</td>\n",
       "      <td>19.13</td>\n",
       "      <td>2348.98</td>\n",
       "      <td>180.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>172.74</td>\n",
       "      <td>22.21</td>\n",
       "      <td>795.34</td>\n",
       "      <td>330.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>119.19</td>\n",
       "      <td>14.98</td>\n",
       "      <td>1715.75</td>\n",
       "      <td>176.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>116.35</td>\n",
       "      <td>15.37</td>\n",
       "      <td>1562.15</td>\n",
       "      <td>136.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>358.60</td>\n",
       "      <td>40.61</td>\n",
       "      <td>242.08</td>\n",
       "      <td>465.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn_en        Company_en Company_cn Country_cn_en  \\\n",
       "0  2008     1                   HSBC Holdings       汇丰集团                 \n",
       "1  2008     2                General Electric     通用电气公司                 \n",
       "2  2008     3                 Bank of America       美国银行                 \n",
       "3  2008     4                  JPMorgan Chase     摩根大通公司                 \n",
       "4  2008     5                      ExxonMobil    埃克森美孚公司                 \n",
       "\n",
       "  Country_cn      Country_en Industry_cn           Industry_en   Sales  \\\n",
       "0             United Kingdom                           Banking  146.50   \n",
       "1              United States                     Conglomerates  172.74   \n",
       "2              United States                           Banking  119.19   \n",
       "3              United States                           Banking  116.35   \n",
       "4              United States              Oil & Gas Operations  358.60   \n",
       "\n",
       "   Profits   Assets  Market_value  \n",
       "0    19.13  2348.98        180.81  \n",
       "1    22.21   795.34        330.93  \n",
       "2    14.98  1715.75        176.53  \n",
       "3    15.37  1562.15        136.88  \n",
       "4    40.61   242.08        465.51  "
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按指定list重新将columns进行排序\n",
    "df_2008 = df_2008.reindex(columns=columns_sort)\n",
    "print(df_2008.shape)\n",
    "print(df_2008.dtypes)\n",
    "df_2008.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2009"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>排名(Rank)</th>\n",
       "      <th>公司名称(Company)</th>\n",
       "      <th>所在国家或地区(Country)</th>\n",
       "      <th>所在行业(Industry)</th>\n",
       "      <th>销售收入(Sales) ($bil)</th>\n",
       "      <th>利润(Profits)</th>\n",
       "      <th>总资产(Assets) ($bil)</th>\n",
       "      <th>市值(Market Vaue) ($bil)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>General Electric/通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>182.52</td>\n",
       "      <td>17.41</td>\n",
       "      <td>797.77</td>\n",
       "      <td>89.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Dutch Shell/英荷壳牌集团</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>458.36</td>\n",
       "      <td>26.28</td>\n",
       "      <td>278.44</td>\n",
       "      <td>135.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>3</td>\n",
       "      <td>Toyota Motor/丰田汽车公司</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>263.42</td>\n",
       "      <td>17.21</td>\n",
       "      <td>324.98</td>\n",
       "      <td>102.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil/埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>425.7</td>\n",
       "      <td>45.22</td>\n",
       "      <td>228.05</td>\n",
       "      <td>335.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>BP/英国石油公司</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>361.14</td>\n",
       "      <td>21.16</td>\n",
       "      <td>228.24</td>\n",
       "      <td>119.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份  排名(Rank)             公司名称(Company) 所在国家或地区(Country)  \\\n",
       "0  2009         1   General Electric/通用电气公司    United States   \n",
       "1  2009         2  Royal Dutch Shell/英荷壳牌集团      Netherlands   \n",
       "2  2009         3       Toyota Motor/丰田汽车公司            Japan   \n",
       "3  2009         4        ExxonMobil/埃克森美孚公司    United States   \n",
       "4  2009         5                 BP/英国石油公司   United Kingdom   \n",
       "\n",
       "         所在行业(Industry) 销售收入(Sales) ($bil) 利润(Profits) 总资产(Assets) ($bil)  \\\n",
       "0         Conglomerates             182.52       17.41             797.77   \n",
       "1  Oil & Gas Operations             458.36       26.28             278.44   \n",
       "2     Consumer Durables             263.42       17.21             324.98   \n",
       "3  Oil & Gas Operations              425.7       45.22             228.05   \n",
       "4  Oil & Gas Operations             361.14       21.16             228.24   \n",
       "\n",
       "   市值(Market Vaue) ($bil)  \n",
       "0                   89.87  \n",
       "1                  135.10  \n",
       "2                  102.35  \n",
       "3                  335.54  \n",
       "4                  119.70  "
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2009 = pd.read_csv('./data/data_forbes_2009.csv', encoding='gbk')\n",
    "print('the shape of DataFrame: ', df_2009.shape)\n",
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 更新columns名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>General Electric/通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>182.52</td>\n",
       "      <td>17.41</td>\n",
       "      <td>797.77</td>\n",
       "      <td>89.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Dutch Shell/英荷壳牌集团</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>458.36</td>\n",
       "      <td>26.28</td>\n",
       "      <td>278.44</td>\n",
       "      <td>135.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>3</td>\n",
       "      <td>Toyota Motor/丰田汽车公司</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>263.42</td>\n",
       "      <td>17.21</td>\n",
       "      <td>324.98</td>\n",
       "      <td>102.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil/埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>425.7</td>\n",
       "      <td>45.22</td>\n",
       "      <td>228.05</td>\n",
       "      <td>335.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>BP/英国石油公司</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>361.14</td>\n",
       "      <td>21.16</td>\n",
       "      <td>228.24</td>\n",
       "      <td>119.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank             Company_cn_en      Country_en           Industry_en  \\\n",
       "0  2009     1   General Electric/通用电气公司   United States         Conglomerates   \n",
       "1  2009     2  Royal Dutch Shell/英荷壳牌集团     Netherlands  Oil & Gas Operations   \n",
       "2  2009     3       Toyota Motor/丰田汽车公司           Japan     Consumer Durables   \n",
       "3  2009     4        ExxonMobil/埃克森美孚公司   United States  Oil & Gas Operations   \n",
       "4  2009     5                 BP/英国石油公司  United Kingdom  Oil & Gas Operations   \n",
       "\n",
       "    Sales Profits  Assets  Market_value  \n",
       "0  182.52   17.41  797.77         89.87  \n",
       "1  458.36   26.28  278.44        135.10  \n",
       "2  263.42   17.21  324.98        102.35  \n",
       "3   425.7   45.22  228.05        335.54  \n",
       "4  361.14   21.16  228.24        119.70  "
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2009.columns = ['Year', 'Rank', 'Company_cn_en', 'Country_en', 'Industry_en', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* **拆分\"Company_cn_en\"列**，新生成两列，分别为公司英文名称和中文名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     General Electric\n",
      "1    Royal Dutch Shell\n",
      "2         Toyota Motor\n",
      "3           ExxonMobil\n",
      "4                   BP\n",
      "Name: Company_en, dtype: object\n",
      "1995    NaN\n",
      "1996    NaN\n",
      "1997    NaN\n",
      "1998    NaN\n",
      "1999    NaN\n",
      "Name: Company_cn, dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>General Electric/通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>182.52</td>\n",
       "      <td>17.41</td>\n",
       "      <td>797.77</td>\n",
       "      <td>89.87</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Dutch Shell/英荷壳牌集团</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>458.36</td>\n",
       "      <td>26.28</td>\n",
       "      <td>278.44</td>\n",
       "      <td>135.10</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>英荷壳牌集团</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>3</td>\n",
       "      <td>Toyota Motor/丰田汽车公司</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>263.42</td>\n",
       "      <td>17.21</td>\n",
       "      <td>324.98</td>\n",
       "      <td>102.35</td>\n",
       "      <td>Toyota Motor</td>\n",
       "      <td>丰田汽车公司</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil/埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>425.7</td>\n",
       "      <td>45.22</td>\n",
       "      <td>228.05</td>\n",
       "      <td>335.54</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>BP/英国石油公司</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>361.14</td>\n",
       "      <td>21.16</td>\n",
       "      <td>228.24</td>\n",
       "      <td>119.70</td>\n",
       "      <td>BP</td>\n",
       "      <td>英国石油公司</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank             Company_cn_en      Country_en           Industry_en  \\\n",
       "0  2009     1   General Electric/通用电气公司   United States         Conglomerates   \n",
       "1  2009     2  Royal Dutch Shell/英荷壳牌集团     Netherlands  Oil & Gas Operations   \n",
       "2  2009     3       Toyota Motor/丰田汽车公司           Japan     Consumer Durables   \n",
       "3  2009     4        ExxonMobil/埃克森美孚公司   United States  Oil & Gas Operations   \n",
       "4  2009     5                 BP/英国石油公司  United Kingdom  Oil & Gas Operations   \n",
       "\n",
       "    Sales Profits  Assets  Market_value         Company_en Company_cn  \n",
       "0  182.52   17.41  797.77         89.87   General Electric     通用电气公司  \n",
       "1  458.36   26.28  278.44        135.10  Royal Dutch Shell     英荷壳牌集团  \n",
       "2  263.42   17.21  324.98        102.35       Toyota Motor     丰田汽车公司  \n",
       "3   425.7   45.22  228.05        335.54         ExxonMobil    埃克森美孚公司  \n",
       "4  361.14   21.16  228.24        119.70                 BP     英国石油公司  "
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2009['Company_en'],df_2009['Company_cn'] = df_2009['Company_cn_en'].str.split('/', 1).str\n",
    "print(df_2009['Company_en'][:5])\n",
    "print(df_2009['Company_cn'] [-5:])\n",
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加空白列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>General Electric/通用电气公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>182.52</td>\n",
       "      <td>17.41</td>\n",
       "      <td>797.77</td>\n",
       "      <td>89.87</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Dutch Shell/英荷壳牌集团</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>458.36</td>\n",
       "      <td>26.28</td>\n",
       "      <td>278.44</td>\n",
       "      <td>135.10</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>英荷壳牌集团</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>3</td>\n",
       "      <td>Toyota Motor/丰田汽车公司</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>263.42</td>\n",
       "      <td>17.21</td>\n",
       "      <td>324.98</td>\n",
       "      <td>102.35</td>\n",
       "      <td>Toyota Motor</td>\n",
       "      <td>丰田汽车公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil/埃克森美孚公司</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>425.7</td>\n",
       "      <td>45.22</td>\n",
       "      <td>228.05</td>\n",
       "      <td>335.54</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>BP/英国石油公司</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>361.14</td>\n",
       "      <td>21.16</td>\n",
       "      <td>228.24</td>\n",
       "      <td>119.70</td>\n",
       "      <td>BP</td>\n",
       "      <td>英国石油公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank             Company_cn_en      Country_en           Industry_en  \\\n",
       "0  2009     1   General Electric/通用电气公司   United States         Conglomerates   \n",
       "1  2009     2  Royal Dutch Shell/英荷壳牌集团     Netherlands  Oil & Gas Operations   \n",
       "2  2009     3       Toyota Motor/丰田汽车公司           Japan     Consumer Durables   \n",
       "3  2009     4        ExxonMobil/埃克森美孚公司   United States  Oil & Gas Operations   \n",
       "4  2009     5                 BP/英国石油公司  United Kingdom  Oil & Gas Operations   \n",
       "\n",
       "    Sales Profits  Assets  Market_value         Company_en Company_cn  \\\n",
       "0  182.52   17.41  797.77         89.87   General Electric     通用电气公司   \n",
       "1  458.36   26.28  278.44        135.10  Royal Dutch Shell     英荷壳牌集团   \n",
       "2  263.42   17.21  324.98        102.35       Toyota Motor     丰田汽车公司   \n",
       "3   425.7   45.22  228.05        335.54         ExxonMobil    埃克森美孚公司   \n",
       "4  361.14   21.16  228.24        119.70                 BP     英国石油公司   \n",
       "\n",
       "  Country_cn_en Country_cn Industry_cn  \n",
       "0                                       \n",
       "1                                       \n",
       "2                                       \n",
       "3                                       \n",
       "4                                       "
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2009['Country_cn_en'], df_2009['Country_cn'], df_2009['Industry_cn'] = ['','','']\n",
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "col_digit = ['Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "for col in col_digit:\n",
    "    # 将数字后面的字母进行替换\n",
    "    df_2009[col] = df_2009[col].replace('([A-Za-z])', '', regex=True)\n",
    "\n",
    "    # 千分位数字的逗号被识别为string了，需要替换\n",
    "    df_2009[col] = df_2009[col].replace(',', '', regex=True)\n",
    "    \n",
    "    df_2009[col] = pd.to_numeric(df_2009[col])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 将columns重新排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009</td>\n",
       "      <td>1</td>\n",
       "      <td>General Electric/通用电气公司</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>182.52</td>\n",
       "      <td>17.41</td>\n",
       "      <td>797.77</td>\n",
       "      <td>89.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Dutch Shell/英荷壳牌集团</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>英荷壳牌集团</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Netherlands</td>\n",
       "      <td></td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>458.36</td>\n",
       "      <td>26.28</td>\n",
       "      <td>278.44</td>\n",
       "      <td>135.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>3</td>\n",
       "      <td>Toyota Motor/丰田汽车公司</td>\n",
       "      <td>Toyota Motor</td>\n",
       "      <td>丰田汽车公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>263.42</td>\n",
       "      <td>17.21</td>\n",
       "      <td>324.98</td>\n",
       "      <td>102.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil/埃克森美孚公司</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>425.70</td>\n",
       "      <td>45.22</td>\n",
       "      <td>228.05</td>\n",
       "      <td>335.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>5</td>\n",
       "      <td>BP/英国石油公司</td>\n",
       "      <td>BP</td>\n",
       "      <td>英国石油公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td></td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>361.14</td>\n",
       "      <td>21.16</td>\n",
       "      <td>228.24</td>\n",
       "      <td>119.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank             Company_cn_en         Company_en Company_cn  \\\n",
       "0  2009     1   General Electric/通用电气公司   General Electric     通用电气公司   \n",
       "1  2009     2  Royal Dutch Shell/英荷壳牌集团  Royal Dutch Shell     英荷壳牌集团   \n",
       "2  2009     3       Toyota Motor/丰田汽车公司       Toyota Motor     丰田汽车公司   \n",
       "3  2009     4        ExxonMobil/埃克森美孚公司         ExxonMobil    埃克森美孚公司   \n",
       "4  2009     5                 BP/英国石油公司                 BP     英国石油公司   \n",
       "\n",
       "  Country_cn_en Country_cn      Country_en Industry_cn           Industry_en  \\\n",
       "0                            United States                     Conglomerates   \n",
       "1                              Netherlands              Oil & Gas Operations   \n",
       "2                                    Japan                 Consumer Durables   \n",
       "3                            United States              Oil & Gas Operations   \n",
       "4                           United Kingdom              Oil & Gas Operations   \n",
       "\n",
       "    Sales  Profits  Assets  Market_value  \n",
       "0  182.52    17.41  797.77         89.87  \n",
       "1  458.36    26.28  278.44        135.10  \n",
       "2  263.42    17.21  324.98        102.35  \n",
       "3  425.70    45.22  228.05        335.54  \n",
       "4  361.14    21.16  228.24        119.70  "
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按指定list重新将columns进行排序\n",
    "df_2009 = df_2009.reindex(columns=columns_sort)\n",
    "print(df_2009.shape)\n",
    "print(df_2009.dtypes)\n",
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2010"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据加载，单位为十亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2001, 10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>115.63</td>\n",
       "      <td>11.65</td>\n",
       "      <td>2,031.99</td>\n",
       "      <td>166.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>156.78</td>\n",
       "      <td>11.03</td>\n",
       "      <td>781.82</td>\n",
       "      <td>169.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>150.45</td>\n",
       "      <td>6.28</td>\n",
       "      <td>2,223.30</td>\n",
       "      <td>167.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>275.56</td>\n",
       "      <td>19.28</td>\n",
       "      <td>233.32</td>\n",
       "      <td>308.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>Banking</td>\n",
       "      <td>71.86</td>\n",
       "      <td>16.27</td>\n",
       "      <td>1,428.46</td>\n",
       "      <td>242.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1        2                 3              4                     5  \\\n",
       "0  2010  1   摩根大通公司    JPMorgan Chase  United States               Banking   \n",
       "1  2010  2   通用电气公司  General Electric  United States         Conglomerates   \n",
       "2  2010  3     美国银行   Bank of America  United States               Banking   \n",
       "3  2010  4  埃克森美孚公司        ExxonMobil  United States  Oil & Gas Operations   \n",
       "4  2010  5   中国工商银行              ICBC          China               Banking   \n",
       "\n",
       "        6      7         8       9  \n",
       "0  115.63  11.65  2,031.99  166.19  \n",
       "1  156.78  11.03    781.82  169.65  \n",
       "2  150.45   6.28  2,223.30  167.63  \n",
       "3  275.56  19.28    233.32  308.77  \n",
       "4   71.86  16.27  1,428.46  242.23  "
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2010 = pd.read_csv('./data/data_forbes_2010.csv', encoding='gbk', header=None)\n",
    "print('the shape of DataFrame: ', df_2010.shape)\n",
    "df_2010.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加columns的名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>115.63</td>\n",
       "      <td>11.65</td>\n",
       "      <td>2,031.99</td>\n",
       "      <td>166.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>156.78</td>\n",
       "      <td>11.03</td>\n",
       "      <td>781.82</td>\n",
       "      <td>169.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>150.45</td>\n",
       "      <td>6.28</td>\n",
       "      <td>2,223.30</td>\n",
       "      <td>167.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>275.56</td>\n",
       "      <td>19.28</td>\n",
       "      <td>233.32</td>\n",
       "      <td>308.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>Banking</td>\n",
       "      <td>71.86</td>\n",
       "      <td>16.27</td>\n",
       "      <td>1,428.46</td>\n",
       "      <td>242.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year Rank Company_cn        Company_en     Country_en  \\\n",
       "0  2010    1     摩根大通公司    JPMorgan Chase  United States   \n",
       "1  2010    2     通用电气公司  General Electric  United States   \n",
       "2  2010    3       美国银行   Bank of America  United States   \n",
       "3  2010    4    埃克森美孚公司        ExxonMobil  United States   \n",
       "4  2010    5     中国工商银行              ICBC          China   \n",
       "\n",
       "            Industry_en   Sales Profits    Assets Market_value  \n",
       "0               Banking  115.63   11.65  2,031.99       166.19  \n",
       "1         Conglomerates  156.78   11.03    781.82       169.65  \n",
       "2               Banking  150.45    6.28  2,223.30       167.63  \n",
       "3  Oil & Gas Operations  275.56   19.28    233.32       308.77  \n",
       "4               Banking   71.86   16.27  1,428.46       242.23  "
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2010.columns = ['Year', 'Rank', 'Company_cn','Company_en', 'Country_en', \n",
    "                   'Industry_en', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2010.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加空白列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>115.63</td>\n",
       "      <td>11.65</td>\n",
       "      <td>2,031.99</td>\n",
       "      <td>166.19</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>United States</td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>156.78</td>\n",
       "      <td>11.03</td>\n",
       "      <td>781.82</td>\n",
       "      <td>169.65</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>United States</td>\n",
       "      <td>Banking</td>\n",
       "      <td>150.45</td>\n",
       "      <td>6.28</td>\n",
       "      <td>2,223.30</td>\n",
       "      <td>167.63</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>275.56</td>\n",
       "      <td>19.28</td>\n",
       "      <td>233.32</td>\n",
       "      <td>308.77</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>Banking</td>\n",
       "      <td>71.86</td>\n",
       "      <td>16.27</td>\n",
       "      <td>1,428.46</td>\n",
       "      <td>242.23</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year Rank Company_cn        Company_en     Country_en  \\\n",
       "0  2010    1     摩根大通公司    JPMorgan Chase  United States   \n",
       "1  2010    2     通用电气公司  General Electric  United States   \n",
       "2  2010    3       美国银行   Bank of America  United States   \n",
       "3  2010    4    埃克森美孚公司        ExxonMobil  United States   \n",
       "4  2010    5     中国工商银行              ICBC          China   \n",
       "\n",
       "            Industry_en   Sales Profits    Assets Market_value Company_cn_en  \\\n",
       "0               Banking  115.63   11.65  2,031.99       166.19                 \n",
       "1         Conglomerates  156.78   11.03    781.82       169.65                 \n",
       "2               Banking  150.45    6.28  2,223.30       167.63                 \n",
       "3  Oil & Gas Operations  275.56   19.28    233.32       308.77                 \n",
       "4               Banking   71.86   16.27  1,428.46       242.23                 \n",
       "\n",
       "  Country_cn_en Country_cn Industry_cn  \n",
       "0                                       \n",
       "1                                       \n",
       "2                                       \n",
       "3                                       \n",
       "4                                       "
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2010['Company_cn_en'], df_2010['Country_cn_en'], df_2010['Country_cn'], df_2010['Industry_cn'] = ['','','','']\n",
    "df_2010.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 1600行的标题重复，需要删除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_2010 = df_2010.drop(1600)\n",
    "# df_2010.drop(1600, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "col_digit = ['Sales', 'Profits', 'Assets', 'Market_value', 'Rank']\n",
    "\n",
    "for col in col_digit:\n",
    "    # 将数字后面的字母进行替换\n",
    "    df_2010[col] = df_2010[col].replace('([A-Za-z])', '', regex=True)\n",
    "\n",
    "    # 千分位数字的逗号被识别为string了，需要替换\n",
    "    df_2010[col] = df_2010[col].replace(',', '', regex=True)\n",
    "    \n",
    "    df_2010[col] = pd.to_numeric(df_2010[col])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 将columns重新排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>115.63</td>\n",
       "      <td>11.65</td>\n",
       "      <td>2031.99</td>\n",
       "      <td>166.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Conglomerates</td>\n",
       "      <td>156.78</td>\n",
       "      <td>11.03</td>\n",
       "      <td>781.82</td>\n",
       "      <td>169.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>150.45</td>\n",
       "      <td>6.28</td>\n",
       "      <td>2223.30</td>\n",
       "      <td>167.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚公司</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td>Oil &amp; Gas Operations</td>\n",
       "      <td>275.56</td>\n",
       "      <td>19.28</td>\n",
       "      <td>233.32</td>\n",
       "      <td>308.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td>Banking</td>\n",
       "      <td>71.86</td>\n",
       "      <td>16.27</td>\n",
       "      <td>1428.46</td>\n",
       "      <td>242.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn_en        Company_en Company_cn Country_cn_en  \\\n",
       "0  2010     1                  JPMorgan Chase     摩根大通公司                 \n",
       "1  2010     2                General Electric     通用电气公司                 \n",
       "2  2010     3                 Bank of America       美国银行                 \n",
       "3  2010     4                      ExxonMobil    埃克森美孚公司                 \n",
       "4  2010     5                            ICBC     中国工商银行                 \n",
       "\n",
       "  Country_cn     Country_en Industry_cn           Industry_en   Sales  \\\n",
       "0             United States                           Banking  115.63   \n",
       "1             United States                     Conglomerates  156.78   \n",
       "2             United States                           Banking  150.45   \n",
       "3             United States              Oil & Gas Operations  275.56   \n",
       "4                     China                           Banking   71.86   \n",
       "\n",
       "   Profits   Assets  Market_value  \n",
       "0    11.65  2031.99        166.19  \n",
       "1    11.03   781.82        169.65  \n",
       "2     6.28  2223.30        167.63  \n",
       "3    19.28   233.32        308.77  \n",
       "4    16.27  1428.46        242.23  "
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按指定list重新将columns进行排序\n",
    "df_2010 = df_2010.reindex(columns=columns_sort)\n",
    "print(df_2010.shape)\n",
    "print(df_2010.dtypes)\n",
    "df_2010.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_2010.to_csv('data_forbes_2010_update.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2011"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 加载数据\n",
    "* 原始数据的单位为 亿美元，需要统一成十亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>美国</td>\n",
       "      <td>银行</td>\n",
       "      <td>1155</td>\n",
       "      <td>174</td>\n",
       "      <td>21176</td>\n",
       "      <td>1822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰控股</td>\n",
       "      <td>英国</td>\n",
       "      <td>银行</td>\n",
       "      <td>1033</td>\n",
       "      <td>133</td>\n",
       "      <td>24679</td>\n",
       "      <td>1865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td>美国</td>\n",
       "      <td>企业集团</td>\n",
       "      <td>1502</td>\n",
       "      <td>116</td>\n",
       "      <td>7512</td>\n",
       "      <td>2162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td>美国</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>3416</td>\n",
       "      <td>305</td>\n",
       "      <td>3025</td>\n",
       "      <td>4072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>3691</td>\n",
       "      <td>201</td>\n",
       "      <td>3172</td>\n",
       "      <td>2129</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1                  2         3   4      5     6    7      8     9\n",
       "0  2011  1     JPMorgan Chase      摩根大通  美国     银行  1155  174  21176  1822\n",
       "1  2011  2      HSBC Holdings      汇丰控股  英国     银行  1033  133  24679  1865\n",
       "2  2011  3   General Electric      通用电气  美国   企业集团  1502  116   7512  2162\n",
       "3  2011  4         ExxonMobil     埃克森美孚  美国  石油天然气  3416  305   3025  4072\n",
       "4  2011  5  Royal Dutch Shell  皇家荷兰壳牌集团  荷兰  石油天然气  3691  201   3172  2129"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2011 = pd.read_csv('./data/data_forbes_2011.csv', encoding='gbk', header=None, thousands=',')\n",
    "print('the shape of DataFrame: ', df_2011.shape)\n",
    "df_2011.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加colunmns名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>美国</td>\n",
       "      <td>银行</td>\n",
       "      <td>1155</td>\n",
       "      <td>174</td>\n",
       "      <td>21176</td>\n",
       "      <td>1822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰控股</td>\n",
       "      <td>英国</td>\n",
       "      <td>银行</td>\n",
       "      <td>1033</td>\n",
       "      <td>133</td>\n",
       "      <td>24679</td>\n",
       "      <td>1865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td>美国</td>\n",
       "      <td>企业集团</td>\n",
       "      <td>1502</td>\n",
       "      <td>116</td>\n",
       "      <td>7512</td>\n",
       "      <td>2162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td>美国</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>3416</td>\n",
       "      <td>305</td>\n",
       "      <td>3025</td>\n",
       "      <td>4072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>3691</td>\n",
       "      <td>201</td>\n",
       "      <td>3172</td>\n",
       "      <td>2129</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank         Company_en Company_cn Country_cn Industry_cn  Sales  \\\n",
       "0  2011     1     JPMorgan Chase       摩根大通         美国          银行   1155   \n",
       "1  2011     2      HSBC Holdings       汇丰控股         英国          银行   1033   \n",
       "2  2011     3   General Electric       通用电气         美国        企业集团   1502   \n",
       "3  2011     4         ExxonMobil      埃克森美孚         美国       石油天然气   3416   \n",
       "4  2011     5  Royal Dutch Shell   皇家荷兰壳牌集团         荷兰       石油天然气   3691   \n",
       "\n",
       "   Profits  Assets  Market_value  \n",
       "0      174   21176          1822  \n",
       "1      133   24679          1865  \n",
       "2      116    7512          2162  \n",
       "3      305    3025          4072  \n",
       "4      201    3172          2129  "
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2011.columns = ['Year', 'Rank', 'Company_en','Company_cn', 'Country_cn',\n",
    "                   'Industry_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2011.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year             int64\n",
       "Rank             int64\n",
       "Company_en      object\n",
       "Company_cn      object\n",
       "Country_cn      object\n",
       "Industry_cn     object\n",
       "Sales            int64\n",
       "Profits          int64\n",
       "Assets           int64\n",
       "Market_value     int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2011.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 修改货币单位为 十亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>美国</td>\n",
       "      <td>银行</td>\n",
       "      <td>115.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>2117.6</td>\n",
       "      <td>182.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰控股</td>\n",
       "      <td>英国</td>\n",
       "      <td>银行</td>\n",
       "      <td>103.3</td>\n",
       "      <td>13.3</td>\n",
       "      <td>2467.9</td>\n",
       "      <td>186.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td>美国</td>\n",
       "      <td>企业集团</td>\n",
       "      <td>150.2</td>\n",
       "      <td>11.6</td>\n",
       "      <td>751.2</td>\n",
       "      <td>216.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td>美国</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>341.6</td>\n",
       "      <td>30.5</td>\n",
       "      <td>302.5</td>\n",
       "      <td>407.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>369.1</td>\n",
       "      <td>20.1</td>\n",
       "      <td>317.2</td>\n",
       "      <td>212.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank         Company_en Company_cn Country_cn Industry_cn  Sales  \\\n",
       "0  2011     1     JPMorgan Chase       摩根大通         美国          银行  115.5   \n",
       "1  2011     2      HSBC Holdings       汇丰控股         英国          银行  103.3   \n",
       "2  2011     3   General Electric       通用电气         美国        企业集团  150.2   \n",
       "3  2011     4         ExxonMobil      埃克森美孚         美国       石油天然气  341.6   \n",
       "4  2011     5  Royal Dutch Shell   皇家荷兰壳牌集团         荷兰       石油天然气  369.1   \n",
       "\n",
       "   Profits  Assets  Market_value  \n",
       "0     17.4  2117.6         182.2  \n",
       "1     13.3  2467.9         186.5  \n",
       "2     11.6   751.2         216.2  \n",
       "3     30.5   302.5         407.2  \n",
       "4     20.1   317.2         212.9  "
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2011[['Sales','Profits','Assets','Market_value']] =df_2011[['Sales','Profits','Assets','Market_value']].apply(lambda x: x/10)\n",
    "df_2011.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加空白列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>美国</td>\n",
       "      <td>银行</td>\n",
       "      <td>115.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>2117.6</td>\n",
       "      <td>182.2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰控股</td>\n",
       "      <td>英国</td>\n",
       "      <td>银行</td>\n",
       "      <td>103.3</td>\n",
       "      <td>13.3</td>\n",
       "      <td>2467.9</td>\n",
       "      <td>186.5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td>美国</td>\n",
       "      <td>企业集团</td>\n",
       "      <td>150.2</td>\n",
       "      <td>11.6</td>\n",
       "      <td>751.2</td>\n",
       "      <td>216.2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td>美国</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>341.6</td>\n",
       "      <td>30.5</td>\n",
       "      <td>302.5</td>\n",
       "      <td>407.2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>石油天然气</td>\n",
       "      <td>369.1</td>\n",
       "      <td>20.1</td>\n",
       "      <td>317.2</td>\n",
       "      <td>212.9</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank         Company_en Company_cn Country_cn Industry_cn  Sales  \\\n",
       "0  2011     1     JPMorgan Chase       摩根大通         美国          银行  115.5   \n",
       "1  2011     2      HSBC Holdings       汇丰控股         英国          银行  103.3   \n",
       "2  2011     3   General Electric       通用电气         美国        企业集团  150.2   \n",
       "3  2011     4         ExxonMobil      埃克森美孚         美国       石油天然气  341.6   \n",
       "4  2011     5  Royal Dutch Shell   皇家荷兰壳牌集团         荷兰       石油天然气  369.1   \n",
       "\n",
       "   Profits  Assets  Market_value Company_cn_en Country_cn_en Country_en  \\\n",
       "0     17.4  2117.6         182.2                                          \n",
       "1     13.3  2467.9         186.5                                          \n",
       "2     11.6   751.2         216.2                                          \n",
       "3     30.5   302.5         407.2                                          \n",
       "4     20.1   317.2         212.9                                          \n",
       "\n",
       "  Industry_en  \n",
       "0              \n",
       "1              \n",
       "2              \n",
       "3              \n",
       "4              "
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2011['Company_cn_en'], df_2011['Country_cn_en'], df_2011['Country_en'], df_2011['Industry_en'] = ['','','','']\n",
    "df_2011.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 按指定list重新将columns进行排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>115.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>2117.6</td>\n",
       "      <td>182.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰控股</td>\n",
       "      <td></td>\n",
       "      <td>英国</td>\n",
       "      <td></td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>103.3</td>\n",
       "      <td>13.3</td>\n",
       "      <td>2467.9</td>\n",
       "      <td>186.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td>企业集团</td>\n",
       "      <td></td>\n",
       "      <td>150.2</td>\n",
       "      <td>11.6</td>\n",
       "      <td>751.2</td>\n",
       "      <td>216.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td>石油天然气</td>\n",
       "      <td></td>\n",
       "      <td>341.6</td>\n",
       "      <td>30.5</td>\n",
       "      <td>302.5</td>\n",
       "      <td>407.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td></td>\n",
       "      <td>荷兰</td>\n",
       "      <td></td>\n",
       "      <td>石油天然气</td>\n",
       "      <td></td>\n",
       "      <td>369.1</td>\n",
       "      <td>20.1</td>\n",
       "      <td>317.2</td>\n",
       "      <td>212.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn_en         Company_en Company_cn Country_cn_en  \\\n",
       "0  2011     1                   JPMorgan Chase       摩根大通                 \n",
       "1  2011     2                    HSBC Holdings       汇丰控股                 \n",
       "2  2011     3                 General Electric       通用电气                 \n",
       "3  2011     4                       ExxonMobil      埃克森美孚                 \n",
       "4  2011     5                Royal Dutch Shell   皇家荷兰壳牌集团                 \n",
       "\n",
       "  Country_cn Country_en Industry_cn Industry_en  Sales  Profits  Assets  \\\n",
       "0         美国                     银行              115.5     17.4  2117.6   \n",
       "1         英国                     银行              103.3     13.3  2467.9   \n",
       "2         美国                   企业集团              150.2     11.6   751.2   \n",
       "3         美国                  石油天然气              341.6     30.5   302.5   \n",
       "4         荷兰                  石油天然气              369.1     20.1   317.2   \n",
       "\n",
       "   Market_value  \n",
       "0         182.2  \n",
       "1         186.5  \n",
       "2         216.2  \n",
       "3         407.2  \n",
       "4         212.9  "
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按指定list重新将columns进行排序\n",
    "df_2011 = df_2011.reindex(columns=columns_sort)\n",
    "print(df_2011.shape)\n",
    "print(df_2011.dtypes)\n",
    "df_2011.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2012"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 采集的原始数据有异常，用Pandas不能顺利加载，需要进行手动调整；\n",
    "* 2012年原始数据的单位是 亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n",
      "0      int64\n",
      "1      int64\n",
      "2    float64\n",
      "3     object\n",
      "4     object\n",
      "5      int64\n",
      "6      int64\n",
      "7      int64\n",
      "8    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>埃克森美孚/Exxon Mobil</td>\n",
       "      <td>美国</td>\n",
       "      <td>4335</td>\n",
       "      <td>411</td>\n",
       "      <td>3311</td>\n",
       "      <td>4074.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>美国</td>\n",
       "      <td>1108</td>\n",
       "      <td>190</td>\n",
       "      <td>22658</td>\n",
       "      <td>1701.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>通用电气/General Electric</td>\n",
       "      <td>美国</td>\n",
       "      <td>1473</td>\n",
       "      <td>142</td>\n",
       "      <td>7172</td>\n",
       "      <td>2137.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>皇家荷兰壳牌集团/Royal Dutch Shell</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>4702</td>\n",
       "      <td>309</td>\n",
       "      <td>3405</td>\n",
       "      <td>2276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>中国</td>\n",
       "      <td>826</td>\n",
       "      <td>251</td>\n",
       "      <td>20391</td>\n",
       "      <td>2374.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1   2                           3   4     5    6      7       8\n",
       "0  2012  1 NaN           埃克森美孚/Exxon Mobil  美国  4335  411   3311  4074.0\n",
       "1  2012  2 NaN         摩根大通/JPMorgan Chase  美国  1108  190  22658  1701.0\n",
       "2  2012  3 NaN       通用电气/General Electric  美国  1473  142   7172  2137.0\n",
       "3  2012  4 NaN  皇家荷兰壳牌集团/Royal Dutch Shell  荷兰  4702  309   3405  2276.0\n",
       "4  2012  5 NaN                 中国工商银行/ICBC  中国   826  251  20391  2374.0"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012 = pd.read_csv('./data/data_forbes_2012.csv', encoding='gbk',header=None)\n",
    "print('the shape of DataFrame: ', df_2012.shape)\n",
    "print(df_2012.dtypes)\n",
    "df_2012.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据初步整理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>1</td>\n",
       "      <td>埃克森美孚/Exxon Mobil</td>\n",
       "      <td>Exxon Mobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>433.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>331.1</td>\n",
       "      <td>407.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>110.8</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2265.8</td>\n",
       "      <td>170.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>3</td>\n",
       "      <td>通用电气/General Electric</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>147.3</td>\n",
       "      <td>14.2</td>\n",
       "      <td>717.2</td>\n",
       "      <td>213.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012</td>\n",
       "      <td>4</td>\n",
       "      <td>皇家荷兰壳牌集团/Royal Dutch Shell</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td></td>\n",
       "      <td>荷兰</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>470.2</td>\n",
       "      <td>30.9</td>\n",
       "      <td>340.5</td>\n",
       "      <td>227.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012</td>\n",
       "      <td>5</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td>中国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>82.6</td>\n",
       "      <td>25.1</td>\n",
       "      <td>2039.1</td>\n",
       "      <td>237.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank               Company_cn_en         Company_en Company_cn  \\\n",
       "0  2012     1           埃克森美孚/Exxon Mobil        Exxon Mobil      埃克森美孚   \n",
       "1  2012     2         摩根大通/JPMorgan Chase     JPMorgan Chase       摩根大通   \n",
       "2  2012     3       通用电气/General Electric   General Electric       通用电气   \n",
       "3  2012     4  皇家荷兰壳牌集团/Royal Dutch Shell  Royal Dutch Shell   皇家荷兰壳牌集团   \n",
       "4  2012     5                 中国工商银行/ICBC               ICBC     中国工商银行   \n",
       "\n",
       "  Country_cn_en Country_cn Country_en Industry_cn Industry_en  Sales  Profits  \\\n",
       "0                       美国                                     433.5     41.1   \n",
       "1                       美国                                     110.8     19.0   \n",
       "2                       美国                                     147.3     14.2   \n",
       "3                       荷兰                                     470.2     30.9   \n",
       "4                       中国                                      82.6     25.1   \n",
       "\n",
       "   Assets  Market_value  \n",
       "0   331.1         407.4  \n",
       "1  2265.8         170.1  \n",
       "2   717.2         213.7  \n",
       "3   340.5         227.6  \n",
       "4  2039.1         237.4  "
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 更新列名\n",
    "df_2012.columns = ['Year', 'Rank', 'Company_cn','Company_cn_en', \n",
    "                   'Country_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "# 拆分\"Company_cn_en\"列，新生成两列，分别为公司英文名称和中文名称\n",
    "df_2012['Company_cn'],df_2012['Company_en'] = df_2012['Company_cn_en'].str.split('/', 1).str\n",
    "# print(df_2012['Company_cn'][:5])\n",
    "# print(df_2012['Company_en'] [-5:])\n",
    "\n",
    "# 将数据单位转换成十亿美元\n",
    "df_2012[['Sales','Profits','Assets','Market_value']] =df_2012[['Sales','Profits','Assets','Market_value']].apply(lambda x: x/10)\n",
    "\n",
    "# 添加空白列\n",
    "df_2012['Country_en'],df_2012['Country_cn_en'], df_2012['Industry_cn'], df_2012['Industry_en'] = ['','','','']\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "df_2012 = df_2012.reindex(columns=columns_sort)\n",
    "print(df_2012.shape)\n",
    "print(df_2012.dtypes)\n",
    "df_2012.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2013"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Source 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2013年原始数据的单位是 亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (1991, 9)\n",
      "0      int64\n",
      "1      int64\n",
      "2    float64\n",
      "3     object\n",
      "4     object\n",
      "5     object\n",
      "6     object\n",
      "7     object\n",
      "8     object\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
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       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1348</td>\n",
       "      <td>378</td>\n",
       "      <td>28135</td>\n",
       "      <td>2373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1131</td>\n",
       "      <td>306</td>\n",
       "      <td>22410</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>美国</td>\n",
       "      <td>1082</td>\n",
       "      <td>213</td>\n",
       "      <td>23591</td>\n",
       "      <td>1914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>通用电气/General Electric</td>\n",
       "      <td>美国</td>\n",
       "      <td>1474</td>\n",
       "      <td>136</td>\n",
       "      <td>6853</td>\n",
       "      <td>2437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>埃克森美孚/Exxon Mobil</td>\n",
       "      <td>美国</td>\n",
       "      <td>4207</td>\n",
       "      <td>449</td>\n",
       "      <td>3338</td>\n",
       "      <td>4004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1   2                               3     4     5    6      7     8\n",
       "0  2013  1 NaN                     中国工商银行/ICBC  中国大陆  1348  378  28135  2373\n",
       "1  2013  2 NaN  中国建设银行/China Construction Bank  中国大陆  1131  306  22410  2020\n",
       "2  2013  3 NaN             摩根大通/JPMorgan Chase    美国  1082  213  23591  1914\n",
       "3  2013  4 NaN           通用电气/General Electric    美国  1474  136   6853  2437\n",
       "4  2013  5 NaN               埃克森美孚/Exxon Mobil    美国  4207  449   3338  4004"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2013 = pd.read_csv('./data/data_forbes_2013.csv', encoding='gbk',header=None)\n",
    "print('the shape of DataFrame: ', df_2013.shape)\n",
    "print(df_2013.dtypes)\n",
    "df_2013.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2013年的数据只有1991条记录，数据可能有缺失，待进一步核实。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Source 2 补充数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2013年的数据在网上继续寻找，发现Economy Watch网站有相关数据，于是进行数据爬取\n",
    "* Economy Watch：Forbes Global 2000: China's Largest Companies\n",
    "* http://www.economywatch.com/companies/forbes-list/china.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (1984, 7)\n",
      "Global Rank                               int64\n",
      "Company                                  object\n",
      "Country                                  object\n",
      "Sales\\n            ($billion)           float64\n",
      "Profits\\n            ($billion)         float64\n",
      "Assets\\n            ($billion)          float64\n",
      "Market Value\\n            ($billion)    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Global Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Country</th>\n",
       "      <th>Sales\n",
       "            ($billion)</th>\n",
       "      <th>Profits\n",
       "            ($billion)</th>\n",
       "      <th>Assets\n",
       "            ($billion)</th>\n",
       "      <th>Market Value\n",
       "            ($billion)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>134.8</td>\n",
       "      <td>37.8</td>\n",
       "      <td>2813.5</td>\n",
       "      <td>237.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>China</td>\n",
       "      <td>113.1</td>\n",
       "      <td>30.6</td>\n",
       "      <td>2241.0</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>China</td>\n",
       "      <td>103.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2124.2</td>\n",
       "      <td>150.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>China</td>\n",
       "      <td>308.9</td>\n",
       "      <td>18.3</td>\n",
       "      <td>347.8</td>\n",
       "      <td>261.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>Bank of China</td>\n",
       "      <td>China</td>\n",
       "      <td>98.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>2033.8</td>\n",
       "      <td>131.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Global Rank                     Company      Country  \\\n",
       "0                 1                        ICBC   China   \n",
       "1                 2     China Construction Bank   China   \n",
       "2                 8  Agricultural Bank of China   China   \n",
       "3                 9                  PetroChina   China   \n",
       "4                11               Bank of China   China   \n",
       "\n",
       "   Sales\\n            ($billion)       Profits\\n            ($billion)  \\\n",
       "0                               134.8                             37.8   \n",
       "1                               113.1                             30.6   \n",
       "2                               103.0                             23.0   \n",
       "3                               308.9                             18.3   \n",
       "4                                98.1                             22.1   \n",
       "\n",
       "   Assets\\n            ($billion)  Market Value\\n            ($billion)  \n",
       "0                          2813.5                                 237.3  \n",
       "1                          2241.0                                 202.0  \n",
       "2                          2124.2                                 150.8  \n",
       "3                           347.8                                 261.2  \n",
       "4                          2033.8                                 131.7  "
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2013_economy = pd.read_csv('./data/data_forbes_2013_economywatch.csv', encoding='gbk')\n",
    "print('the shape of DataFrame: ', df_2013_economy.shape)\n",
    "print(df_2013_economy.dtypes)\n",
    "df_2013_economy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 发现数据只有1984条记录，也缺少相关记录\n",
    "* 继续寻找其他记录"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Source 3： 2013年使用excel数据源"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 后来，在找到一个excel文件，发现数据记录是完整的，如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 7)\n",
      "排名           int64\n",
      "公司名         object\n",
      "国家（地区）      object\n",
      "销售额（亿美元）     int64\n",
      "利润（亿美元）      int64\n",
      "资产（亿美元）      int64\n",
      "市值（亿美元）      int64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>公司名</th>\n",
       "      <th>国家（地区）</th>\n",
       "      <th>销售额（亿美元）</th>\n",
       "      <th>利润（亿美元）</th>\n",
       "      <th>资产（亿美元）</th>\n",
       "      <th>市值（亿美元）</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1348</td>\n",
       "      <td>378</td>\n",
       "      <td>28135</td>\n",
       "      <td>2373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1131</td>\n",
       "      <td>306</td>\n",
       "      <td>22410</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>美国</td>\n",
       "      <td>1082</td>\n",
       "      <td>213</td>\n",
       "      <td>23591</td>\n",
       "      <td>1914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>通用电气/General Electric</td>\n",
       "      <td>美国</td>\n",
       "      <td>1474</td>\n",
       "      <td>136</td>\n",
       "      <td>6853</td>\n",
       "      <td>2437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>埃克森美孚/Exxon Mobil</td>\n",
       "      <td>美国</td>\n",
       "      <td>4207</td>\n",
       "      <td>449</td>\n",
       "      <td>3338</td>\n",
       "      <td>4004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名                             公司名 国家（地区）  销售额（亿美元）  利润（亿美元）  资产（亿美元）  \\\n",
       "0   1                     中国工商银行/ICBC   中国大陆      1348      378    28135   \n",
       "1   2  中国建设银行/China Construction Bank   中国大陆      1131      306    22410   \n",
       "2   3             摩根大通/JPMorgan Chase     美国      1082      213    23591   \n",
       "3   4           通用电气/General Electric     美国      1474      136     6853   \n",
       "4   5               埃克森美孚/Exxon Mobil     美国      4207      449     3338   \n",
       "\n",
       "   市值（亿美元）  \n",
       "0     2373  \n",
       "1     2020  \n",
       "2     1914  \n",
       "3     2437  \n",
       "4     4004  "
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2013_all = pd.read_excel('./data/data_forbes_2013_all.xlsx')\n",
    "print('the shape of DataFrame: ', df_2013_all.shape)\n",
    "print(df_2013_all.dtypes)\n",
    "df_2013_all.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据整理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>134.8</td>\n",
       "      <td>37.8</td>\n",
       "      <td>2813.5</td>\n",
       "      <td>237.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>113.1</td>\n",
       "      <td>30.6</td>\n",
       "      <td>2241.0</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>3</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>108.2</td>\n",
       "      <td>21.3</td>\n",
       "      <td>2359.1</td>\n",
       "      <td>191.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>4</td>\n",
       "      <td>通用电气/General Electric</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>147.4</td>\n",
       "      <td>13.6</td>\n",
       "      <td>685.3</td>\n",
       "      <td>243.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>5</td>\n",
       "      <td>埃克森美孚/Exxon Mobil</td>\n",
       "      <td>Exxon Mobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>420.7</td>\n",
       "      <td>44.9</td>\n",
       "      <td>333.8</td>\n",
       "      <td>400.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank                   Company_cn_en               Company_en  \\\n",
       "0  2013     1                     中国工商银行/ICBC                     ICBC   \n",
       "1  2013     2  中国建设银行/China Construction Bank  China Construction Bank   \n",
       "2  2013     3             摩根大通/JPMorgan Chase           JPMorgan Chase   \n",
       "3  2013     4           通用电气/General Electric         General Electric   \n",
       "4  2013     5               埃克森美孚/Exxon Mobil              Exxon Mobil   \n",
       "\n",
       "  Company_cn Country_cn_en Country_cn Country_en Industry_cn Industry_en  \\\n",
       "0     中国工商银行                     中国大陆                                      \n",
       "1     中国建设银行                     中国大陆                                      \n",
       "2       摩根大通                       美国                                      \n",
       "3       通用电气                       美国                                      \n",
       "4      埃克森美孚                       美国                                      \n",
       "\n",
       "   Sales  Profits  Assets  Market_value  \n",
       "0  134.8     37.8  2813.5         237.3  \n",
       "1  113.1     30.6  2241.0         202.0  \n",
       "2  108.2     21.3  2359.1         191.4  \n",
       "3  147.4     13.6   685.3         243.7  \n",
       "4  420.7     44.9   333.8         400.4  "
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 更新列名\n",
    "df_2013_all.columns = ['Rank', 'Company_cn_en', \n",
    "                   'Country_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "# 拆分\"Company_cn_en\"列，新生成两列，分别为公司英文名称和中文名称\n",
    "df_2013_all['Company_cn'],df_2013_all['Company_en'] = df_2013_all['Company_cn_en'].str.split('/', 1).str\n",
    "# print(df_2013_all['Company_cn'][:5])\n",
    "# print(df_2013_all['Company_en'] [-5:])\n",
    "\n",
    "# 将数据单位转换成十亿美元\n",
    "df_2013_all[['Sales','Profits','Assets','Market_value']] =df_2013_all[['Sales','Profits','Assets','Market_value']].apply(lambda x: x/10)\n",
    "\n",
    "# 添加年份2013\n",
    "df_2013_all['Year'] = 2013\n",
    "\n",
    "# 添加空白列\n",
    "df_2013_all['Country_en'],df_2013_all['Country_cn_en'], df_2013_all['Industry_cn'], df_2013_all['Industry_en'] = ['','','','']\n",
    "\n",
    "df_2013_all['Rank'] = pd.to_numeric(df_2013_all['Rank'])\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "df_2013_all = df_2013_all.reindex(columns=columns_sort)\n",
    "print(df_2013_all.shape)\n",
    "print(df_2013_all.dtypes)\n",
    "df_2013_all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2014"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 采集的原始数据有异常，用Pandas不能顺利加载，需要进行手动调整；\n",
    "* 2014年原始数据的单位是 亿美元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# columns_sort = ['Year', 'Rank', 'Company_cn_en','Company_en','Company_cn', 'Country_cn_en', 'Country_cn', 'Country_en', 'Industry_cn', 'Industry_en','Sales', 'Profits', 'Assets', 'Market_value']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n",
      "0      int64\n",
      "1      int64\n",
      "2    float64\n",
      "3     object\n",
      "4     object\n",
      "5      int64\n",
      "6      int64\n",
      "7      int64\n",
      "8      int64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1487</td>\n",
       "      <td>427</td>\n",
       "      <td>31249</td>\n",
       "      <td>2156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1213</td>\n",
       "      <td>342</td>\n",
       "      <td>24495</td>\n",
       "      <td>1744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国农业银行/Agricultural Bank of China</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1364</td>\n",
       "      <td>270</td>\n",
       "      <td>24054</td>\n",
       "      <td>1411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>美国</td>\n",
       "      <td>1057</td>\n",
       "      <td>173</td>\n",
       "      <td>24353</td>\n",
       "      <td>2297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>伯克希尔哈撒韦/Berkshire Hathaway</td>\n",
       "      <td>美国</td>\n",
       "      <td>1788</td>\n",
       "      <td>195</td>\n",
       "      <td>4934</td>\n",
       "      <td>3091</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1   2                                  3     4     5    6      7  \\\n",
       "0  2014  1 NaN                        中国工商银行/ICBC  中国大陆  1487  427  31249   \n",
       "1  2014  2 NaN     中国建设银行/China Construction Bank  中国大陆  1213  342  24495   \n",
       "2  2014  3 NaN  中国农业银行/Agricultural Bank of China  中国大陆  1364  270  24054   \n",
       "3  2014  4 NaN                摩根大通/JPMorgan Chase    美国  1057  173  24353   \n",
       "4  2014  5 NaN         伯克希尔哈撒韦/Berkshire Hathaway    美国  1788  195   4934   \n",
       "\n",
       "      8  \n",
       "0  2156  \n",
       "1  1744  \n",
       "2  1411  \n",
       "3  2297  \n",
       "4  3091  "
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2014 = pd.read_csv('./data/data_forbes_2014.csv', encoding='gbk',header=None)\n",
    "print('the shape of DataFrame: ', df_2014.shape)\n",
    "print(df_2014.dtypes)\n",
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>148.7</td>\n",
       "      <td>42.7</td>\n",
       "      <td>3124.9</td>\n",
       "      <td>215.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>121.3</td>\n",
       "      <td>34.2</td>\n",
       "      <td>2449.5</td>\n",
       "      <td>174.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>3</td>\n",
       "      <td>中国农业银行/Agricultural Bank of China</td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>中国农业银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>136.4</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2405.4</td>\n",
       "      <td>141.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>摩根大通/JPMorgan Chase</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>105.7</td>\n",
       "      <td>17.3</td>\n",
       "      <td>2435.3</td>\n",
       "      <td>229.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>5</td>\n",
       "      <td>伯克希尔哈撒韦/Berkshire Hathaway</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>伯克希尔哈撒韦</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>178.8</td>\n",
       "      <td>19.5</td>\n",
       "      <td>493.4</td>\n",
       "      <td>309.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank                      Company_cn_en                  Company_en  \\\n",
       "0  2014     1                        中国工商银行/ICBC                        ICBC   \n",
       "1  2014     2     中国建设银行/China Construction Bank     China Construction Bank   \n",
       "2  2014     3  中国农业银行/Agricultural Bank of China  Agricultural Bank of China   \n",
       "3  2014     4                摩根大通/JPMorgan Chase              JPMorgan Chase   \n",
       "4  2014     5         伯克希尔哈撒韦/Berkshire Hathaway          Berkshire Hathaway   \n",
       "\n",
       "  Company_cn Country_cn_en Country_cn Country_en Industry_cn Industry_en  \\\n",
       "0     中国工商银行                     中国大陆                                      \n",
       "1     中国建设银行                     中国大陆                                      \n",
       "2     中国农业银行                     中国大陆                                      \n",
       "3       摩根大通                       美国                                      \n",
       "4    伯克希尔哈撒韦                       美国                                      \n",
       "\n",
       "   Sales  Profits  Assets  Market_value  \n",
       "0  148.7     42.7  3124.9         215.6  \n",
       "1  121.3     34.2  2449.5         174.4  \n",
       "2  136.4     27.0  2405.4         141.1  \n",
       "3  105.7     17.3  2435.3         229.7  \n",
       "4  178.8     19.5   493.4         309.1  "
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 更新列名\n",
    "df_2014.columns = ['Year', 'Rank', 'Company_cn','Company_cn_en', \n",
    "                   'Country_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "# 拆分\"Company_cn_en\"列，新生成两列，分别为公司英文名称和中文名称\n",
    "df_2014['Company_cn'],df_2014['Company_en'] = df_2014['Company_cn_en'].str.split('/', 1).str\n",
    "# print(df_2014['Company_cn'][:5])\n",
    "# print(df_2014['Company_en'] [-5:])\n",
    "\n",
    "# 将数据单位转换成十亿美元\n",
    "df_2014[['Sales','Profits','Assets','Market_value']] =df_2014[['Sales','Profits','Assets','Market_value']].apply(lambda x: x/10)\n",
    "\n",
    "# 添加空白列\n",
    "df_2014['Country_en'],df_2014['Country_cn_en'], df_2014['Industry_cn'], df_2014['Industry_en'] = ['','','','']\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "df_2014 = df_2014.reindex(columns=columns_sort)\n",
    "print(df_2014.shape)\n",
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2015"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2015年原始数据的单位是 亿美元\n",
    "* 2015年，有部分企业是重复的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2020, 9)\n",
      "0      int64\n",
      "1      int64\n",
      "2    float64\n",
      "3     object\n",
      "4     object\n",
      "5    float64\n",
      "6    float64\n",
      "7    float64\n",
      "8    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>33220.0</td>\n",
       "      <td>2783.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>26989.0</td>\n",
       "      <td>2129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国农业银行/Agricultural Bank of China</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1292.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>25748.0</td>\n",
       "      <td>1899.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国银行/Bank of China</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>24583.0</td>\n",
       "      <td>1991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>伯克希尔哈撒韦/Berkshire Hathaway</td>\n",
       "      <td>美国</td>\n",
       "      <td>1947.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>5346.0</td>\n",
       "      <td>3548.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0  1   2                                  3     4       5      6  \\\n",
       "0  2015  1 NaN                        中国工商银行/ICBC  中国大陆  1668.0  448.0   \n",
       "1  2015  2 NaN     中国建设银行/China Construction Bank  中国大陆  1305.0  370.0   \n",
       "2  2015  3 NaN  中国农业银行/Agricultural Bank of China  中国大陆  1292.0  291.0   \n",
       "3  2015  4 NaN                 中国银行/Bank of China  中国大陆  1203.0  275.0   \n",
       "4  2015  5 NaN         伯克希尔哈撒韦/Berkshire Hathaway    美国  1947.0  199.0   \n",
       "\n",
       "         7       8  \n",
       "0  33220.0  2783.0  \n",
       "1  26989.0  2129.0  \n",
       "2  25748.0  1899.0  \n",
       "3  24583.0  1991.0  \n",
       "4   5346.0  3548.0  "
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2015 = pd.read_csv('./data/data_forbes_2015.csv', encoding='gbk',header=None)\n",
    "print('the shape of DataFrame: ', df_2015.shape)\n",
    "print(df_2015.dtypes)\n",
    "df_2015.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 整理数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2020, 14)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行/ICBC</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>166.8</td>\n",
       "      <td>44.8</td>\n",
       "      <td>3322.0</td>\n",
       "      <td>278.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行/China Construction Bank</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>130.5</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2698.9</td>\n",
       "      <td>212.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>3</td>\n",
       "      <td>中国农业银行/Agricultural Bank of China</td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>中国农业银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>129.2</td>\n",
       "      <td>29.1</td>\n",
       "      <td>2574.8</td>\n",
       "      <td>189.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>中国银行/Bank of China</td>\n",
       "      <td>Bank of China</td>\n",
       "      <td>中国银行</td>\n",
       "      <td></td>\n",
       "      <td>中国大陆</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>120.3</td>\n",
       "      <td>27.5</td>\n",
       "      <td>2458.3</td>\n",
       "      <td>199.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>伯克希尔哈撒韦/Berkshire Hathaway</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>伯克希尔哈撒韦</td>\n",
       "      <td></td>\n",
       "      <td>美国</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>194.7</td>\n",
       "      <td>19.9</td>\n",
       "      <td>534.6</td>\n",
       "      <td>354.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank                      Company_cn_en                  Company_en  \\\n",
       "0  2015     1                        中国工商银行/ICBC                        ICBC   \n",
       "1  2015     2     中国建设银行/China Construction Bank     China Construction Bank   \n",
       "2  2015     3  中国农业银行/Agricultural Bank of China  Agricultural Bank of China   \n",
       "3  2015     4                 中国银行/Bank of China               Bank of China   \n",
       "4  2015     5         伯克希尔哈撒韦/Berkshire Hathaway          Berkshire Hathaway   \n",
       "\n",
       "  Company_cn Country_cn_en Country_cn Country_en Industry_cn Industry_en  \\\n",
       "0     中国工商银行                     中国大陆                                      \n",
       "1     中国建设银行                     中国大陆                                      \n",
       "2     中国农业银行                     中国大陆                                      \n",
       "3       中国银行                     中国大陆                                      \n",
       "4    伯克希尔哈撒韦                       美国                                      \n",
       "\n",
       "   Sales  Profits  Assets  Market_value  \n",
       "0  166.8     44.8  3322.0         278.3  \n",
       "1  130.5     37.0  2698.9         212.9  \n",
       "2  129.2     29.1  2574.8         189.9  \n",
       "3  120.3     27.5  2458.3         199.1  \n",
       "4  194.7     19.9   534.6         354.8  "
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 更新列名\n",
    "df_2015.columns = ['Year', 'Rank', 'Company_cn','Company_cn_en', \n",
    "                   'Country_cn', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "# 拆分\"Company_cn_en\"列，新生成两列，分别为公司英文名称和中文名称\n",
    "df_2015['Company_cn'],df_2015['Company_en'] = df_2015['Company_cn_en'].str.split('/', 1).str\n",
    "# print(df_2014['Company_cn'][:5])\n",
    "# print(df_2014['Company_en'] [-5:])\n",
    "\n",
    "# 将数据单位转换成十亿美元\n",
    "df_2015[['Sales','Profits','Assets','Market_value']] =df_2015[['Sales','Profits','Assets','Market_value']].apply(lambda x: x/10)\n",
    "\n",
    "# 添加空白列\n",
    "df_2015['Country_en'],df_2015['Country_cn_en'], df_2015['Industry_cn'], df_2015['Industry_en'] = ['','','','']\n",
    "\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "df_2015 = df_2015.reindex(columns=columns_sort)\n",
    "print(df_2015.shape)\n",
    "df_2015.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 数据有2020行，有重复行，需要去除重复行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 数据有2020行，有重复行，需要去除重复行\n",
    "# inplace=True，使去重生效\n",
    "df_2015.drop_duplicates('Company_cn_en', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看'Company_cn_en'是否还有重复行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Year, Rank, Company_cn_en, Company_en, Company_cn, Country_cn_en, Country_cn, Country_en, Industry_cn, Industry_en, Sales, Profits, Assets, Market_value]\n",
       "Index: []"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看'Company_cn_en'是否还有重复行\n",
    "df_2015[df_2015['Company_cn_en'].duplicated()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看数据行数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 14)\n"
     ]
    }
   ],
   "source": [
    "print('the shape of DataFrame: ', df_2015.shape)\n",
    "# print(df_2015.dtypes)\n",
    "# df_2015.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2016"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2016年原始数据的单位，各个单元格不一样"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 通过查看原始数据，发现有些行的数据可能不准确\n",
    "* 对比网站的数据，进行了手动修改\n",
    "* http://www.askci.com/news/finance/20160530/13364822511_7.shtml\n",
    "* 修改的情况如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2001, 9)\n",
      "Year              int64\n",
      "Rank              int64\n",
      "Company_cn      float64\n",
      "Company_en       object\n",
      "Country_en       object\n",
      "Sales            object\n",
      "Profits          object\n",
      "Assets           object\n",
      "Market_value     object\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>$171.1 B</td>\n",
       "      <td>$44.2 B</td>\n",
       "      <td>$3,420.3 B</td>\n",
       "      <td>$198 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>China</td>\n",
       "      <td>$146.8 B</td>\n",
       "      <td>$36.4 B</td>\n",
       "      <td>$2,826 B</td>\n",
       "      <td>$162.8 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>China</td>\n",
       "      <td>$131.9 B</td>\n",
       "      <td>$28.8 B</td>\n",
       "      <td>$2,739.8 B</td>\n",
       "      <td>$152.7 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>United States</td>\n",
       "      <td>$210.8 B</td>\n",
       "      <td>$24.1 B</td>\n",
       "      <td>$561.1 B</td>\n",
       "      <td>$360.1 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>$99.9 B</td>\n",
       "      <td>$23.5 B</td>\n",
       "      <td>$2,423.8 B</td>\n",
       "      <td>$234.2 B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank  Company_cn                  Company_en     Country_en  \\\n",
       "0  2016     1         NaN                        ICBC          China   \n",
       "1  2016     2         NaN     China Construction Bank          China   \n",
       "2  2016     3         NaN  Agricultural Bank of China          China   \n",
       "3  2016     4         NaN          Berkshire Hathaway  United States   \n",
       "4  2016     5         NaN              JPMorgan Chase  United States   \n",
       "\n",
       "      Sales  Profits      Assets Market_value  \n",
       "0  $171.1 B  $44.2 B  $3,420.3 B       $198 B  \n",
       "1  $146.8 B  $36.4 B    $2,826 B     $162.8 B  \n",
       "2  $131.9 B  $28.8 B  $2,739.8 B     $152.7 B  \n",
       "3  $210.8 B  $24.1 B    $561.1 B     $360.1 B  \n",
       "4   $99.9 B  $23.5 B  $2,423.8 B     $234.2 B  "
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2016 = pd.read_csv('./data/data_forbes_2016.csv', encoding='gbk',header=None)\n",
    "print('the shape of DataFrame: ', df_2016.shape)\n",
    "\n",
    "# 更新列名\n",
    "df_2016.columns = ['Year', 'Rank', 'Company_cn','Company_en', \n",
    "                   'Country_en', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "print(df_2016.dtypes)\n",
    "df_2016.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "* 编写自定义处理函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def pro_col(df, col):   \n",
    "    # 替换相关字符串，如有更多的替换情形，可以自行添加\n",
    "    df[col] = df[col].str.replace('$','')\n",
    "    df[col] = df[col].str.replace('^[A-Za-z]+$','')\n",
    "    df[col] = df[col].str.replace('B','')\n",
    "    \n",
    "    # 注意这里是'-$'，即以'-'结尾，而不是'-'，因为有负数\n",
    "    df[col] = df[col].str.replace('-$','') \n",
    "    df[col] = df[col].str.replace(',','')\n",
    "    \n",
    "    # 处理含有百万“M”为单位的数据，即以“M”结尾的数据\n",
    "    # 思路：\n",
    "    # （1）设定查找条件mask；\n",
    "    # （2）替换字符串“M”为空值\n",
    "    # （3）用pd.to_numeric()转换为数字\n",
    "    # （4）除以1000，转换为十亿美元，与其他行的数据一致\n",
    "    mask = df[col].str.endswith('M')\n",
    "    df.loc[mask, col] = pd.to_numeric(df.loc[mask, col].str.replace('M',''))/1000\n",
    "    \n",
    "    # 将字符型的数字转换为数字类型\n",
    "    df[col] = pd.to_numeric(df[col])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 应用自定义函数进行数据处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2001, 9)\n",
      "Year              int64\n",
      "Rank              int64\n",
      "Company_cn      float64\n",
      "Company_en       object\n",
      "Country_en       object\n",
      "Sales           float64\n",
      "Profits         float64\n",
      "Assets          float64\n",
      "Market_value    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>171.1</td>\n",
       "      <td>44.2</td>\n",
       "      <td>3420.3</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>China</td>\n",
       "      <td>146.8</td>\n",
       "      <td>36.4</td>\n",
       "      <td>2826.0</td>\n",
       "      <td>162.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>China</td>\n",
       "      <td>131.9</td>\n",
       "      <td>28.8</td>\n",
       "      <td>2739.8</td>\n",
       "      <td>152.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>United States</td>\n",
       "      <td>210.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>561.1</td>\n",
       "      <td>360.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>99.9</td>\n",
       "      <td>23.5</td>\n",
       "      <td>2423.8</td>\n",
       "      <td>234.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank  Company_cn                  Company_en     Country_en  Sales  \\\n",
       "0  2016     1         NaN                        ICBC          China  171.1   \n",
       "1  2016     2         NaN     China Construction Bank          China  146.8   \n",
       "2  2016     3         NaN  Agricultural Bank of China          China  131.9   \n",
       "3  2016     4         NaN          Berkshire Hathaway  United States  210.8   \n",
       "4  2016     5         NaN              JPMorgan Chase  United States   99.9   \n",
       "\n",
       "   Profits  Assets  Market_value  \n",
       "0     44.2  3420.3         198.0  \n",
       "1     36.4  2826.0         162.8  \n",
       "2     28.8  2739.8         152.7  \n",
       "3     24.1   561.1         360.1  \n",
       "4     23.5  2423.8         234.2  "
      ]
     },
     "execution_count": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pro_col(df_2016, 'Sales')\n",
    "# pro_col(df_2016, 'Profits')\n",
    "# pro_col(df_2016, 'Assets')\n",
    "# pro_col(df_2016, 'Market_value')\n",
    "\n",
    "cols = ['Sales', 'Profits', 'Assets', 'Market_value']\n",
    "for col in cols:\n",
    "    pro_col(df_2016, col)\n",
    "\n",
    "\n",
    "print('the shape of DataFrame: ', df_2016.shape)\n",
    "print(df_2016.dtypes)\n",
    "df_2016.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 添加空白列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2001, 14)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>ICBC</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>171.1</td>\n",
       "      <td>44.2</td>\n",
       "      <td>3420.3</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>146.8</td>\n",
       "      <td>36.4</td>\n",
       "      <td>2826.0</td>\n",
       "      <td>162.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td>Agricultural Bank of China</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>131.9</td>\n",
       "      <td>28.8</td>\n",
       "      <td>2739.8</td>\n",
       "      <td>152.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>210.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>561.1</td>\n",
       "      <td>360.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>99.9</td>\n",
       "      <td>23.5</td>\n",
       "      <td>2423.8</td>\n",
       "      <td>234.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn_en                  Company_en  Company_cn  \\\n",
       "0  2016     1                                      ICBC         NaN   \n",
       "1  2016     2                   China Construction Bank         NaN   \n",
       "2  2016     3                Agricultural Bank of China         NaN   \n",
       "3  2016     4                        Berkshire Hathaway         NaN   \n",
       "4  2016     5                            JPMorgan Chase         NaN   \n",
       "\n",
       "  Country_cn_en Country_cn     Country_en Industry_cn Industry_en  Sales  \\\n",
       "0                                   China                          171.1   \n",
       "1                                   China                          146.8   \n",
       "2                                   China                          131.9   \n",
       "3                           United States                          210.8   \n",
       "4                           United States                           99.9   \n",
       "\n",
       "   Profits  Assets  Market_value  \n",
       "0     44.2  3420.3         198.0  \n",
       "1     36.4  2826.0         162.8  \n",
       "2     28.8  2739.8         152.7  \n",
       "3     24.1   561.1         360.1  \n",
       "4     23.5  2423.8         234.2  "
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 添加空白列\n",
    "df_2016['Company_cn_en'],df_2016['Country_cn_en'], df_2016['Country_cn'], df_2016['Industry_cn'], df_2016['Industry_en'] = ['','','','','']\n",
    "\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "df_2016 = df_2016.reindex(columns=columns_sort)\n",
    "print(df_2016.shape)\n",
    "df_2016.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Year 2017"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 2017年原始数据的单位，各个单元格不一样"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>$151.4 B</td>\n",
       "      <td>$42 B</td>\n",
       "      <td>$3,473.2 B</td>\n",
       "      <td>$229.8 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>China</td>\n",
       "      <td>$134.2 B</td>\n",
       "      <td>$35 B</td>\n",
       "      <td>$3,016.6 B</td>\n",
       "      <td>$200.5 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>伯克希尔哈撒韦</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>United States</td>\n",
       "      <td>$222.9 B</td>\n",
       "      <td>$24.1 B</td>\n",
       "      <td>$620.9 B</td>\n",
       "      <td>$409.9 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>$102.5 B</td>\n",
       "      <td>$24.2 B</td>\n",
       "      <td>$2,513 B</td>\n",
       "      <td>$306.6 B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>富国银行</td>\n",
       "      <td>Wells Fargo</td>\n",
       "      <td>United States</td>\n",
       "      <td>$97.6 B</td>\n",
       "      <td>$21.9 B</td>\n",
       "      <td>$1,943.4 B</td>\n",
       "      <td>$274.4 B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn               Company_en     Country_en     Sales  \\\n",
       "0  2017     1     中国工商银行                     ICBC          China  $151.4 B   \n",
       "1  2017     2     中国建设银行  China Construction Bank          China  $134.2 B   \n",
       "2  2017     3    伯克希尔哈撒韦       Berkshire Hathaway  United States  $222.9 B   \n",
       "3  2017     4       摩根大通           JPMorgan Chase  United States  $102.5 B   \n",
       "4  2017     5       富国银行              Wells Fargo  United States   $97.6 B   \n",
       "\n",
       "   Profits      Assets Market_value  \n",
       "0    $42 B  $3,473.2 B     $229.8 B  \n",
       "1    $35 B  $3,016.6 B     $200.5 B  \n",
       "2  $24.1 B    $620.9 B     $409.9 B  \n",
       "3  $24.2 B    $2,513 B     $306.6 B  \n",
       "4  $21.9 B  $1,943.4 B     $274.4 B  "
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2017 = pd.read_csv('./data/data_forbes_2017.csv', encoding='gbk')\n",
    "\n",
    "# 更新列名\n",
    "df_2017.columns = ['Year', 'Rank', 'Company_cn','Company_en', \n",
    "                   'Country_en', 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "\n",
    "print('the shape of DataFrame: ', df_2017.shape)\n",
    "df_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (2000, 9)\n",
      "Year              int64\n",
      "Rank              int64\n",
      "Company_cn       object\n",
      "Company_en       object\n",
      "Country_en       object\n",
      "Sales           float64\n",
      "Profits         float64\n",
      "Assets          float64\n",
      "Market_value    float64\n",
      "dtype: object\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td>ICBC</td>\n",
       "      <td>China</td>\n",
       "      <td>151.4</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3473.2</td>\n",
       "      <td>229.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>China</td>\n",
       "      <td>134.2</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3016.6</td>\n",
       "      <td>200.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>伯克希尔哈撒韦</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>United States</td>\n",
       "      <td>222.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>620.9</td>\n",
       "      <td>409.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>United States</td>\n",
       "      <td>102.5</td>\n",
       "      <td>24.2</td>\n",
       "      <td>2513.0</td>\n",
       "      <td>306.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>富国银行</td>\n",
       "      <td>Wells Fargo</td>\n",
       "      <td>United States</td>\n",
       "      <td>97.6</td>\n",
       "      <td>21.9</td>\n",
       "      <td>1943.4</td>\n",
       "      <td>274.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn               Company_en     Country_en  Sales  \\\n",
       "0  2017     1     中国工商银行                     ICBC          China  151.4   \n",
       "1  2017     2     中国建设银行  China Construction Bank          China  134.2   \n",
       "2  2017     3    伯克希尔哈撒韦       Berkshire Hathaway  United States  222.9   \n",
       "3  2017     4       摩根大通           JPMorgan Chase  United States  102.5   \n",
       "4  2017     5       富国银行              Wells Fargo  United States   97.6   \n",
       "\n",
       "   Profits  Assets  Market_value  \n",
       "0     42.0  3473.2         229.8  \n",
       "1     35.0  3016.6         200.5  \n",
       "2     24.1   620.9         409.9  \n",
       "3     24.2  2513.0         306.6  \n",
       "4     21.9  1943.4         274.4  "
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['Sales', 'Profits', 'Assets', 'Market_value']\n",
    "for col in cols:\n",
    "    pro_col(df_2017, col)\n",
    "\n",
    "\n",
    "print('the shape of DataFrame: ', df_2017.shape)\n",
    "print(df_2017.dtypes)\n",
    "df_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2000, 14)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>ICBC</td>\n",
       "      <td>中国工商银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>151.4</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3473.2</td>\n",
       "      <td>229.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td>China Construction Bank</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>134.2</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3016.6</td>\n",
       "      <td>200.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>伯克希尔哈撒韦</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>222.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>620.9</td>\n",
       "      <td>409.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>摩根大通</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>102.5</td>\n",
       "      <td>24.2</td>\n",
       "      <td>2513.0</td>\n",
       "      <td>306.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td>Wells Fargo</td>\n",
       "      <td>富国银行</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>97.6</td>\n",
       "      <td>21.9</td>\n",
       "      <td>1943.4</td>\n",
       "      <td>274.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank Company_cn_en               Company_en Company_cn Country_cn_en  \\\n",
       "0  2017     1                                   ICBC     中国工商银行                 \n",
       "1  2017     2                China Construction Bank     中国建设银行                 \n",
       "2  2017     3                     Berkshire Hathaway    伯克希尔哈撒韦                 \n",
       "3  2017     4                         JPMorgan Chase       摩根大通                 \n",
       "4  2017     5                            Wells Fargo       富国银行                 \n",
       "\n",
       "  Country_cn     Country_en Industry_cn Industry_en  Sales  Profits  Assets  \\\n",
       "0                     China                          151.4     42.0  3473.2   \n",
       "1                     China                          134.2     35.0  3016.6   \n",
       "2             United States                          222.9     24.1   620.9   \n",
       "3             United States                          102.5     24.2  2513.0   \n",
       "4             United States                           97.6     21.9  1943.4   \n",
       "\n",
       "   Market_value  \n",
       "0         229.8  \n",
       "1         200.5  \n",
       "2         409.9  \n",
       "3         306.6  \n",
       "4         274.4  "
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 添加空白列\n",
    "df_2017['Company_cn_en'],df_2017['Country_cn_en'], df_2017['Country_cn'], df_2017['Industry_cn'], df_2017['Industry_en'] = ['','','','','']\n",
    "\n",
    "\n",
    "# 按指定list重新将columns进行排序\n",
    "# columns_sort = ['Year', 'Rank', 'Company_cn_en','Company_en',\n",
    "#                 'Company_cn', 'Country_cn_en', 'Country_cn', \n",
    "#                 'Country_en', 'Industry_cn', 'Industry_en',\n",
    "#                 'Sales', 'Profits', 'Assets', 'Market_value']\n",
    "df_2017 = df_2017.reindex(columns=columns_sort)\n",
    "print(df_2017.shape)\n",
    "df_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# df_2017.to_csv('data_forbes_2017_update.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# 数据合并"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company_cn_en</th>\n",
       "      <th>Company_en</th>\n",
       "      <th>Company_cn</th>\n",
       "      <th>Country_cn_en</th>\n",
       "      <th>Country_cn</th>\n",
       "      <th>Country_en</th>\n",
       "      <th>Industry_cn</th>\n",
       "      <th>Industry_en</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profits</th>\n",
       "      <th>Assets</th>\n",
       "      <th>Market_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>1</td>\n",
       "      <td>Citigroup /花旗集团</td>\n",
       "      <td>Citigroup</td>\n",
       "      <td>花旗集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>146.560</td>\n",
       "      <td>21.540</td>\n",
       "      <td>1884.32</td>\n",
       "      <td>247.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "      <td>Bank of America /美国银行</td>\n",
       "      <td>Bank of America</td>\n",
       "      <td>美国银行</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>116.570</td>\n",
       "      <td>21.130</td>\n",
       "      <td>1459.74</td>\n",
       "      <td>226.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>3</td>\n",
       "      <td>HSBC Holdings/汇丰集团</td>\n",
       "      <td>HSBC Holdings</td>\n",
       "      <td>汇丰集团</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>121.510</td>\n",
       "      <td>16.630</td>\n",
       "      <td>1860.76</td>\n",
       "      <td>202.290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>4</td>\n",
       "      <td>General Electric /通用电气</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>通用电气</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>多元化</td>\n",
       "      <td></td>\n",
       "      <td>163.390</td>\n",
       "      <td>20.830</td>\n",
       "      <td>697.24</td>\n",
       "      <td>358.980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>5</td>\n",
       "      <td>JPMorgan Chase /JP摩根大通</td>\n",
       "      <td>JPMorgan Chase</td>\n",
       "      <td>JP摩根大通</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>99.300</td>\n",
       "      <td>14.440</td>\n",
       "      <td>1351.52</td>\n",
       "      <td>170.970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2007</td>\n",
       "      <td>6</td>\n",
       "      <td>American Intl Group /美国国际集团</td>\n",
       "      <td>American Intl Group</td>\n",
       "      <td>美国国际集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>保险</td>\n",
       "      <td></td>\n",
       "      <td>113.190</td>\n",
       "      <td>14.010</td>\n",
       "      <td>979.41</td>\n",
       "      <td>174.470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2007</td>\n",
       "      <td>7</td>\n",
       "      <td>ExxonMobil /埃克森美孚</td>\n",
       "      <td>ExxonMobil</td>\n",
       "      <td>埃克森美孚</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>335.090</td>\n",
       "      <td>39.500</td>\n",
       "      <td>223.95</td>\n",
       "      <td>410.650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2007</td>\n",
       "      <td>8</td>\n",
       "      <td>Royal Dutch Shell /皇家荷兰壳牌集团</td>\n",
       "      <td>Royal Dutch Shell</td>\n",
       "      <td>皇家荷兰壳牌集团</td>\n",
       "      <td>荷兰(NL)</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>NL</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>318.850</td>\n",
       "      <td>25.440</td>\n",
       "      <td>232.31</td>\n",
       "      <td>208.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2007</td>\n",
       "      <td>9</td>\n",
       "      <td>UBS /瑞士银行</td>\n",
       "      <td>UBS</td>\n",
       "      <td>瑞士银行</td>\n",
       "      <td>瑞士(SZ)</td>\n",
       "      <td>瑞士</td>\n",
       "      <td>SZ</td>\n",
       "      <td>综合金融</td>\n",
       "      <td></td>\n",
       "      <td>105.590</td>\n",
       "      <td>9.780</td>\n",
       "      <td>1776.89</td>\n",
       "      <td>116.840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2007</td>\n",
       "      <td>10</td>\n",
       "      <td>ING Group /荷兰国际集团</td>\n",
       "      <td>ING Group</td>\n",
       "      <td>荷兰国际集团</td>\n",
       "      <td>荷兰(NL)</td>\n",
       "      <td>荷兰</td>\n",
       "      <td>NL</td>\n",
       "      <td>保险</td>\n",
       "      <td></td>\n",
       "      <td>153.440</td>\n",
       "      <td>9.650</td>\n",
       "      <td>1615.05</td>\n",
       "      <td>93.990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2007</td>\n",
       "      <td>11</td>\n",
       "      <td>BP /英国石油</td>\n",
       "      <td>BP</td>\n",
       "      <td>英国石油</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>265.910</td>\n",
       "      <td>22.290</td>\n",
       "      <td>217.60</td>\n",
       "      <td>198.140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2007</td>\n",
       "      <td>12</td>\n",
       "      <td>Toyota Motor /丰田汽车</td>\n",
       "      <td>Toyota Motor</td>\n",
       "      <td>丰田汽车</td>\n",
       "      <td>日本(JA)</td>\n",
       "      <td>日本</td>\n",
       "      <td>JA</td>\n",
       "      <td>耐用消费品</td>\n",
       "      <td></td>\n",
       "      <td>179.020</td>\n",
       "      <td>11.680</td>\n",
       "      <td>243.60</td>\n",
       "      <td>217.690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2007</td>\n",
       "      <td>13</td>\n",
       "      <td>Royal Bank of Scotland /苏格兰皇家银行</td>\n",
       "      <td>Royal Bank of Scotland</td>\n",
       "      <td>苏格兰皇家银行</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>77.410</td>\n",
       "      <td>12.510</td>\n",
       "      <td>1705.35</td>\n",
       "      <td>124.130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2007</td>\n",
       "      <td>14</td>\n",
       "      <td>BNP Paribas /法国巴黎银行</td>\n",
       "      <td>BNP Paribas</td>\n",
       "      <td>法国巴黎银行</td>\n",
       "      <td>法国(FR)</td>\n",
       "      <td>法国</td>\n",
       "      <td>FR</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>89.160</td>\n",
       "      <td>9.640</td>\n",
       "      <td>1898.19</td>\n",
       "      <td>97.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2007</td>\n",
       "      <td>15</td>\n",
       "      <td>Allianz /安联</td>\n",
       "      <td>Allianz</td>\n",
       "      <td>安联</td>\n",
       "      <td>德国(GE)</td>\n",
       "      <td>德国</td>\n",
       "      <td>GE</td>\n",
       "      <td>保险</td>\n",
       "      <td></td>\n",
       "      <td>125.330</td>\n",
       "      <td>8.810</td>\n",
       "      <td>1380.88</td>\n",
       "      <td>87.220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2007</td>\n",
       "      <td>16</td>\n",
       "      <td>Berkshire Hathaway /伯克夏·哈萨威</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>伯克夏·哈萨威</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>综合金融</td>\n",
       "      <td></td>\n",
       "      <td>98.540</td>\n",
       "      <td>11.020</td>\n",
       "      <td>248.44</td>\n",
       "      <td>163.790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2007</td>\n",
       "      <td>17</td>\n",
       "      <td>Wal-Mart Stores /沃尔玛</td>\n",
       "      <td>Wal-Mart Stores</td>\n",
       "      <td>沃尔玛</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>零售</td>\n",
       "      <td></td>\n",
       "      <td>348.650</td>\n",
       "      <td>11.290</td>\n",
       "      <td>151.19</td>\n",
       "      <td>201.360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2007</td>\n",
       "      <td>18</td>\n",
       "      <td>Barclays /巴克莱</td>\n",
       "      <td>Barclays</td>\n",
       "      <td>巴克莱</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>67.710</td>\n",
       "      <td>8.950</td>\n",
       "      <td>1949.17</td>\n",
       "      <td>94.790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2007</td>\n",
       "      <td>19</td>\n",
       "      <td>Chevron /雪佛龙</td>\n",
       "      <td>Chevron</td>\n",
       "      <td>雪佛龙</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>195.340</td>\n",
       "      <td>17.140</td>\n",
       "      <td>132.63</td>\n",
       "      <td>149.370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2007</td>\n",
       "      <td>19</td>\n",
       "      <td>Total /道达尔菲纳埃尔夫</td>\n",
       "      <td>Total</td>\n",
       "      <td>道达尔菲纳埃尔夫</td>\n",
       "      <td>法国(FR)</td>\n",
       "      <td>法国</td>\n",
       "      <td>FR</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>175.050</td>\n",
       "      <td>15.530</td>\n",
       "      <td>138.82</td>\n",
       "      <td>152.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2007</td>\n",
       "      <td>21</td>\n",
       "      <td>HBOS /苏格兰哈里法克斯银行</td>\n",
       "      <td>HBOS</td>\n",
       "      <td>苏格兰哈里法克斯银行</td>\n",
       "      <td>英国(UK)</td>\n",
       "      <td>英国</td>\n",
       "      <td>UK</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>84.280</td>\n",
       "      <td>7.590</td>\n",
       "      <td>1156.61</td>\n",
       "      <td>79.830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2007</td>\n",
       "      <td>22</td>\n",
       "      <td>ConocoPhillips /大陆菲利普斯</td>\n",
       "      <td>ConocoPhillips</td>\n",
       "      <td>大陆菲利普斯</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>炼油</td>\n",
       "      <td></td>\n",
       "      <td>167.580</td>\n",
       "      <td>15.550</td>\n",
       "      <td>164.78</td>\n",
       "      <td>107.390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2007</td>\n",
       "      <td>23</td>\n",
       "      <td>AXA Group /安盛保险集团</td>\n",
       "      <td>AXA Group</td>\n",
       "      <td>安盛保险集团</td>\n",
       "      <td>法国(FR)</td>\n",
       "      <td>法国</td>\n",
       "      <td>FR</td>\n",
       "      <td>保险</td>\n",
       "      <td></td>\n",
       "      <td>98.850</td>\n",
       "      <td>6.380</td>\n",
       "      <td>666.47</td>\n",
       "      <td>87.640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2007</td>\n",
       "      <td>24</td>\n",
       "      <td>Société Générale Group /法国兴业银行</td>\n",
       "      <td>Société Générale Group</td>\n",
       "      <td>法国兴业银行</td>\n",
       "      <td>法国(FR)</td>\n",
       "      <td>法国</td>\n",
       "      <td>FR</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>84.470</td>\n",
       "      <td>6.550</td>\n",
       "      <td>1259.32</td>\n",
       "      <td>77.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2007</td>\n",
       "      <td>25</td>\n",
       "      <td>Goldman Sachs Group /高盛集团</td>\n",
       "      <td>Goldman Sachs Group</td>\n",
       "      <td>高盛集团</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>综合金融</td>\n",
       "      <td></td>\n",
       "      <td>69.350</td>\n",
       "      <td>9.540</td>\n",
       "      <td>838.20</td>\n",
       "      <td>83.310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2007</td>\n",
       "      <td>25</td>\n",
       "      <td>Morgan Stanley /摩根士丹利</td>\n",
       "      <td>Morgan Stanley</td>\n",
       "      <td>摩根士丹利</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>综合金融</td>\n",
       "      <td></td>\n",
       "      <td>76.550</td>\n",
       "      <td>7.470</td>\n",
       "      <td>1120.65</td>\n",
       "      <td>79.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2007</td>\n",
       "      <td>27</td>\n",
       "      <td>Banco Santander /桑坦德银行</td>\n",
       "      <td>Banco Santander</td>\n",
       "      <td>桑坦德银行</td>\n",
       "      <td>西班牙(SP)</td>\n",
       "      <td>西班牙</td>\n",
       "      <td>SP</td>\n",
       "      <td>银行</td>\n",
       "      <td></td>\n",
       "      <td>62.340</td>\n",
       "      <td>7.370</td>\n",
       "      <td>945.86</td>\n",
       "      <td>115.750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2007</td>\n",
       "      <td>27</td>\n",
       "      <td>Deutsche Bank  /德意志银行</td>\n",
       "      <td>Deutsche Bank</td>\n",
       "      <td>德意志银行</td>\n",
       "      <td>德国(GE)</td>\n",
       "      <td>德国</td>\n",
       "      <td>GE</td>\n",
       "      <td>综合金融</td>\n",
       "      <td></td>\n",
       "      <td>95.500</td>\n",
       "      <td>7.450</td>\n",
       "      <td>1485.58</td>\n",
       "      <td>65.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2007</td>\n",
       "      <td>29</td>\n",
       "      <td>AT&amp;T /美国电话电报公司</td>\n",
       "      <td>AT&amp;T</td>\n",
       "      <td>美国电话电报公司</td>\n",
       "      <td>美国(US)</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>电信运营商</td>\n",
       "      <td></td>\n",
       "      <td>63.060</td>\n",
       "      <td>7.360</td>\n",
       "      <td>270.63</td>\n",
       "      <td>229.780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2007</td>\n",
       "      <td>30</td>\n",
       "      <td>Electricité de France /法国电力公司</td>\n",
       "      <td>Electricité de France</td>\n",
       "      <td>法国电力公司</td>\n",
       "      <td>法国(FR)</td>\n",
       "      <td>法国</td>\n",
       "      <td>FR</td>\n",
       "      <td>公用事业</td>\n",
       "      <td></td>\n",
       "      <td>77.750</td>\n",
       "      <td>7.390</td>\n",
       "      <td>233.40</td>\n",
       "      <td>133.370</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21971</th>\n",
       "      <td>2017</td>\n",
       "      <td>1971</td>\n",
       "      <td></td>\n",
       "      <td>Tian An China Investments</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.244</td>\n",
       "      <td>0.736</td>\n",
       "      <td>4.30</td>\n",
       "      <td>1.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21972</th>\n",
       "      <td>2017</td>\n",
       "      <td>1972</td>\n",
       "      <td></td>\n",
       "      <td>HollyFrontier</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.600</td>\n",
       "      <td>-0.261</td>\n",
       "      <td>9.60</td>\n",
       "      <td>4.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21973</th>\n",
       "      <td>2017</td>\n",
       "      <td>1973</td>\n",
       "      <td></td>\n",
       "      <td>Dah Sing Financial Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.868</td>\n",
       "      <td>0.244</td>\n",
       "      <td>28.80</td>\n",
       "      <td>2.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21974</th>\n",
       "      <td>2017</td>\n",
       "      <td>1973</td>\n",
       "      <td></td>\n",
       "      <td>Nanya Technology</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Taiwan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.300</td>\n",
       "      <td>0.736</td>\n",
       "      <td>4.30</td>\n",
       "      <td>4.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21975</th>\n",
       "      <td>2017</td>\n",
       "      <td>1973</td>\n",
       "      <td></td>\n",
       "      <td>Shanxi Taigang Stainless</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.500</td>\n",
       "      <td>-0.322</td>\n",
       "      <td>11.00</td>\n",
       "      <td>4.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21976</th>\n",
       "      <td>2017</td>\n",
       "      <td>1976</td>\n",
       "      <td></td>\n",
       "      <td>First Horizon National</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.400</td>\n",
       "      <td>0.227</td>\n",
       "      <td>28.70</td>\n",
       "      <td>4.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21977</th>\n",
       "      <td>2017</td>\n",
       "      <td>1977</td>\n",
       "      <td></td>\n",
       "      <td>Brother Industries</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>6.000</td>\n",
       "      <td>0.408</td>\n",
       "      <td>5.80</td>\n",
       "      <td>5.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21978</th>\n",
       "      <td>2017</td>\n",
       "      <td>1977</td>\n",
       "      <td></td>\n",
       "      <td>Chicago Bridge &amp; Iron</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Netherlands</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.700</td>\n",
       "      <td>-0.313</td>\n",
       "      <td>7.80</td>\n",
       "      <td>3.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21979</th>\n",
       "      <td>2017</td>\n",
       "      <td>1979</td>\n",
       "      <td></td>\n",
       "      <td>Belle International Holdings</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>6.300</td>\n",
       "      <td>0.384</td>\n",
       "      <td>4.70</td>\n",
       "      <td>5.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21980</th>\n",
       "      <td>2017</td>\n",
       "      <td>1979</td>\n",
       "      <td></td>\n",
       "      <td>F5 Networks</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.370</td>\n",
       "      <td>2.40</td>\n",
       "      <td>8.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21981</th>\n",
       "      <td>2017</td>\n",
       "      <td>1979</td>\n",
       "      <td></td>\n",
       "      <td>Valspar</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>4.200</td>\n",
       "      <td>0.341</td>\n",
       "      <td>4.20</td>\n",
       "      <td>8.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21982</th>\n",
       "      <td>2017</td>\n",
       "      <td>1982</td>\n",
       "      <td></td>\n",
       "      <td>DKSH Holding</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Switzerland</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.700</td>\n",
       "      <td>0.212</td>\n",
       "      <td>4.30</td>\n",
       "      <td>5.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21983</th>\n",
       "      <td>2017</td>\n",
       "      <td>1982</td>\n",
       "      <td></td>\n",
       "      <td>Grupo Galicia</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Argentina</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3.700</td>\n",
       "      <td>0.407</td>\n",
       "      <td>15.30</td>\n",
       "      <td>5.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21984</th>\n",
       "      <td>2017</td>\n",
       "      <td>1984</td>\n",
       "      <td></td>\n",
       "      <td>Bank of Iwate</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.427</td>\n",
       "      <td>0.097</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21985</th>\n",
       "      <td>2017</td>\n",
       "      <td>1984</td>\n",
       "      <td></td>\n",
       "      <td>Konica Minolta Business Solutions</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.900</td>\n",
       "      <td>0.280</td>\n",
       "      <td>8.80</td>\n",
       "      <td>4.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21986</th>\n",
       "      <td>2017</td>\n",
       "      <td>1986</td>\n",
       "      <td></td>\n",
       "      <td>Synnex Technology Intl</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Taiwan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.600</td>\n",
       "      <td>0.151</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21987</th>\n",
       "      <td>2017</td>\n",
       "      <td>1987</td>\n",
       "      <td></td>\n",
       "      <td>Eurazeo</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>France</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3.400</td>\n",
       "      <td>0.575</td>\n",
       "      <td>10.90</td>\n",
       "      <td>4.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21988</th>\n",
       "      <td>2017</td>\n",
       "      <td>1988</td>\n",
       "      <td></td>\n",
       "      <td>Bankunited</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.200</td>\n",
       "      <td>0.217</td>\n",
       "      <td>28.10</td>\n",
       "      <td>3.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21989</th>\n",
       "      <td>2017</td>\n",
       "      <td>1988</td>\n",
       "      <td></td>\n",
       "      <td>Barry Callebaut</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Switzerland</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>6.800</td>\n",
       "      <td>0.221</td>\n",
       "      <td>5.80</td>\n",
       "      <td>7.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21990</th>\n",
       "      <td>2017</td>\n",
       "      <td>1988</td>\n",
       "      <td></td>\n",
       "      <td>Inchcape</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.600</td>\n",
       "      <td>0.249</td>\n",
       "      <td>5.40</td>\n",
       "      <td>4.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21991</th>\n",
       "      <td>2017</td>\n",
       "      <td>1991</td>\n",
       "      <td></td>\n",
       "      <td>Yamanashi Chuo Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.522</td>\n",
       "      <td>0.062</td>\n",
       "      <td>28.00</td>\n",
       "      <td>0.739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21992</th>\n",
       "      <td>2017</td>\n",
       "      <td>1992</td>\n",
       "      <td></td>\n",
       "      <td>Guangxi Guiguan Electric Power</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.643</td>\n",
       "      <td>6.00</td>\n",
       "      <td>6.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21993</th>\n",
       "      <td>2017</td>\n",
       "      <td>1992</td>\n",
       "      <td></td>\n",
       "      <td>Live Nation Entertainment</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.400</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>6.80</td>\n",
       "      <td>6.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21994</th>\n",
       "      <td>2017</td>\n",
       "      <td>1992</td>\n",
       "      <td></td>\n",
       "      <td>Shaanxi Coal Industry</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>China</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3.800</td>\n",
       "      <td>-0.024</td>\n",
       "      <td>13.60</td>\n",
       "      <td>9.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21995</th>\n",
       "      <td>2017</td>\n",
       "      <td>1995</td>\n",
       "      <td></td>\n",
       "      <td>Aurubis</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Germany</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>10.600</td>\n",
       "      <td>0.249</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21996</th>\n",
       "      <td>2017</td>\n",
       "      <td>1996</td>\n",
       "      <td></td>\n",
       "      <td>BEKB-BCBE</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Switzerland</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.555</td>\n",
       "      <td>0.131</td>\n",
       "      <td>27.90</td>\n",
       "      <td>1.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21997</th>\n",
       "      <td>2017</td>\n",
       "      <td>1996</td>\n",
       "      <td></td>\n",
       "      <td>Fastighets Balder</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Sweden</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.639</td>\n",
       "      <td>10.20</td>\n",
       "      <td>3.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21998</th>\n",
       "      <td>2017</td>\n",
       "      <td>1998</td>\n",
       "      <td></td>\n",
       "      <td>Akamai Technologies</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>United States</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2.300</td>\n",
       "      <td>0.316</td>\n",
       "      <td>4.40</td>\n",
       "      <td>10.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21999</th>\n",
       "      <td>2017</td>\n",
       "      <td>1998</td>\n",
       "      <td></td>\n",
       "      <td>Oita Bank</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Japan</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.523</td>\n",
       "      <td>0.071</td>\n",
       "      <td>27.90</td>\n",
       "      <td>0.595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22000</th>\n",
       "      <td>2017</td>\n",
       "      <td>1998</td>\n",
       "      <td></td>\n",
       "      <td>Tech Mahindra</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>India</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>4.200</td>\n",
       "      <td>0.469</td>\n",
       "      <td>3.60</td>\n",
       "      <td>6.700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22001 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Year  Rank                    Company_cn_en  \\\n",
       "0      2007     1                  Citigroup /花旗集团   \n",
       "1      2007     2            Bank of America /美国银行   \n",
       "2      2007     3               HSBC Holdings/汇丰集团   \n",
       "3      2007     4           General Electric /通用电气   \n",
       "4      2007     5           JPMorgan Chase /JP摩根大通   \n",
       "5      2007     6      American Intl Group /美国国际集团   \n",
       "6      2007     7                ExxonMobil /埃克森美孚   \n",
       "7      2007     8      Royal Dutch Shell /皇家荷兰壳牌集团   \n",
       "8      2007     9                        UBS /瑞士银行   \n",
       "9      2007    10                ING Group /荷兰国际集团   \n",
       "10     2007    11                         BP /英国石油   \n",
       "11     2007    12               Toyota Motor /丰田汽车   \n",
       "12     2007    13  Royal Bank of Scotland /苏格兰皇家银行   \n",
       "13     2007    14              BNP Paribas /法国巴黎银行   \n",
       "14     2007    15                      Allianz /安联   \n",
       "15     2007    16      Berkshire Hathaway /伯克夏·哈萨威   \n",
       "16     2007    17             Wal-Mart Stores /沃尔玛   \n",
       "17     2007    18                    Barclays /巴克莱   \n",
       "18     2007    19                     Chevron /雪佛龙   \n",
       "19     2007    19                  Total /道达尔菲纳埃尔夫   \n",
       "20     2007    21                 HBOS /苏格兰哈里法克斯银行   \n",
       "21     2007    22           ConocoPhillips /大陆菲利普斯   \n",
       "22     2007    23                AXA Group /安盛保险集团   \n",
       "23     2007    24   Société Générale Group /法国兴业银行   \n",
       "24     2007    25        Goldman Sachs Group /高盛集团   \n",
       "25     2007    25            Morgan Stanley /摩根士丹利   \n",
       "26     2007    27           Banco Santander /桑坦德银行   \n",
       "27     2007    27            Deutsche Bank  /德意志银行   \n",
       "28     2007    29                   AT&T /美国电话电报公司   \n",
       "29     2007    30    Electricité de France /法国电力公司   \n",
       "...     ...   ...                              ...   \n",
       "21971  2017  1971                                    \n",
       "21972  2017  1972                                    \n",
       "21973  2017  1973                                    \n",
       "21974  2017  1973                                    \n",
       "21975  2017  1973                                    \n",
       "21976  2017  1976                                    \n",
       "21977  2017  1977                                    \n",
       "21978  2017  1977                                    \n",
       "21979  2017  1979                                    \n",
       "21980  2017  1979                                    \n",
       "21981  2017  1979                                    \n",
       "21982  2017  1982                                    \n",
       "21983  2017  1982                                    \n",
       "21984  2017  1984                                    \n",
       "21985  2017  1984                                    \n",
       "21986  2017  1986                                    \n",
       "21987  2017  1987                                    \n",
       "21988  2017  1988                                    \n",
       "21989  2017  1988                                    \n",
       "21990  2017  1988                                    \n",
       "21991  2017  1991                                    \n",
       "21992  2017  1992                                    \n",
       "21993  2017  1992                                    \n",
       "21994  2017  1992                                    \n",
       "21995  2017  1995                                    \n",
       "21996  2017  1996                                    \n",
       "21997  2017  1996                                    \n",
       "21998  2017  1998                                    \n",
       "21999  2017  1998                                    \n",
       "22000  2017  1998                                    \n",
       "\n",
       "                              Company_en  Company_cn Country_cn_en Country_cn  \\\n",
       "0                             Citigroup         花旗集团        美国(US)         美国   \n",
       "1                       Bank of America         美国银行        美国(US)         美国   \n",
       "2                          HSBC Holdings        汇丰集团        英国(UK)         英国   \n",
       "3                      General Electric         通用电气        美国(US)         美国   \n",
       "4                        JPMorgan Chase       JP摩根大通        美国(US)         美国   \n",
       "5                   American Intl Group       美国国际集团        美国(US)         美国   \n",
       "6                            ExxonMobil        埃克森美孚        美国(US)         美国   \n",
       "7                     Royal Dutch Shell     皇家荷兰壳牌集团        荷兰(NL)         荷兰   \n",
       "8                                   UBS         瑞士银行        瑞士(SZ)         瑞士   \n",
       "9                             ING Group       荷兰国际集团        荷兰(NL)         荷兰   \n",
       "10                                   BP         英国石油        英国(UK)         英国   \n",
       "11                         Toyota Motor         丰田汽车        日本(JA)         日本   \n",
       "12               Royal Bank of Scotland      苏格兰皇家银行        英国(UK)         英国   \n",
       "13                          BNP Paribas       法国巴黎银行        法国(FR)         法国   \n",
       "14                              Allianz           安联        德国(GE)         德国   \n",
       "15                   Berkshire Hathaway      伯克夏·哈萨威        美国(US)         美国   \n",
       "16                      Wal-Mart Stores          沃尔玛        美国(US)         美国   \n",
       "17                             Barclays          巴克莱        英国(UK)         英国   \n",
       "18                              Chevron          雪佛龙        美国(US)         美国   \n",
       "19                                Total     道达尔菲纳埃尔夫        法国(FR)         法国   \n",
       "20                                 HBOS   苏格兰哈里法克斯银行        英国(UK)         英国   \n",
       "21                       ConocoPhillips       大陆菲利普斯        美国(US)         美国   \n",
       "22                            AXA Group       安盛保险集团        法国(FR)         法国   \n",
       "23               Société Générale Group       法国兴业银行        法国(FR)         法国   \n",
       "24                  Goldman Sachs Group         高盛集团        美国(US)         美国   \n",
       "25                       Morgan Stanley        摩根士丹利        美国(US)         美国   \n",
       "26                      Banco Santander        桑坦德银行       西班牙(SP)        西班牙   \n",
       "27                       Deutsche Bank         德意志银行        德国(GE)         德国   \n",
       "28                                 AT&T     美国电话电报公司        美国(US)         美国   \n",
       "29                Electricité de France       法国电力公司        法国(FR)         法国   \n",
       "...                                  ...         ...           ...        ...   \n",
       "21971          Tian An China Investments         NaN                            \n",
       "21972                      HollyFrontier         NaN                            \n",
       "21973        Dah Sing Financial Holdings         NaN                            \n",
       "21974                   Nanya Technology         NaN                            \n",
       "21975           Shanxi Taigang Stainless         NaN                            \n",
       "21976             First Horizon National         NaN                            \n",
       "21977                 Brother Industries         NaN                            \n",
       "21978              Chicago Bridge & Iron         NaN                            \n",
       "21979       Belle International Holdings         NaN                            \n",
       "21980                        F5 Networks         NaN                            \n",
       "21981                            Valspar         NaN                            \n",
       "21982                       DKSH Holding         NaN                            \n",
       "21983                      Grupo Galicia         NaN                            \n",
       "21984                      Bank of Iwate         NaN                            \n",
       "21985  Konica Minolta Business Solutions         NaN                            \n",
       "21986             Synnex Technology Intl         NaN                            \n",
       "21987                            Eurazeo         NaN                            \n",
       "21988                         Bankunited         NaN                            \n",
       "21989                    Barry Callebaut         NaN                            \n",
       "21990                           Inchcape         NaN                            \n",
       "21991                Yamanashi Chuo Bank         NaN                            \n",
       "21992     Guangxi Guiguan Electric Power         NaN                            \n",
       "21993          Live Nation Entertainment         NaN                            \n",
       "21994              Shaanxi Coal Industry         NaN                            \n",
       "21995                            Aurubis         NaN                            \n",
       "21996                          BEKB-BCBE         NaN                            \n",
       "21997                  Fastighets Balder         NaN                            \n",
       "21998                Akamai Technologies         NaN                            \n",
       "21999                          Oita Bank         NaN                            \n",
       "22000                      Tech Mahindra         NaN                            \n",
       "\n",
       "           Country_en Industry_cn Industry_en    Sales  Profits   Assets  \\\n",
       "0                  US          银行              146.560   21.540  1884.32   \n",
       "1                  US          银行              116.570   21.130  1459.74   \n",
       "2                  UK          银行              121.510   16.630  1860.76   \n",
       "3                  US         多元化              163.390   20.830   697.24   \n",
       "4                  US          银行               99.300   14.440  1351.52   \n",
       "5                  US          保险              113.190   14.010   979.41   \n",
       "6                  US          炼油              335.090   39.500   223.95   \n",
       "7                  NL          炼油              318.850   25.440   232.31   \n",
       "8                  SZ        综合金融              105.590    9.780  1776.89   \n",
       "9                  NL          保险              153.440    9.650  1615.05   \n",
       "10                 UK          炼油              265.910   22.290   217.60   \n",
       "11                 JA       耐用消费品              179.020   11.680   243.60   \n",
       "12                 UK          银行               77.410   12.510  1705.35   \n",
       "13                 FR          银行               89.160    9.640  1898.19   \n",
       "14                 GE          保险              125.330    8.810  1380.88   \n",
       "15                 US        综合金融               98.540   11.020   248.44   \n",
       "16                 US          零售              348.650   11.290   151.19   \n",
       "17                 UK          银行               67.710    8.950  1949.17   \n",
       "18                 US          炼油              195.340   17.140   132.63   \n",
       "19                 FR          炼油              175.050   15.530   138.82   \n",
       "20                 UK          银行               84.280    7.590  1156.61   \n",
       "21                 US          炼油              167.580   15.550   164.78   \n",
       "22                 FR          保险               98.850    6.380   666.47   \n",
       "23                 FR          银行               84.470    6.550  1259.32   \n",
       "24                 US        综合金融               69.350    9.540   838.20   \n",
       "25                 US        综合金融               76.550    7.470  1120.65   \n",
       "26                 SP          银行               62.340    7.370   945.86   \n",
       "27                 GE        综合金融               95.500    7.450  1485.58   \n",
       "28                 US       电信运营商               63.060    7.360   270.63   \n",
       "29                 FR        公用事业               77.750    7.390   233.40   \n",
       "...               ...         ...         ...      ...      ...      ...   \n",
       "21971       Hong Kong                            0.244    0.736     4.30   \n",
       "21972   United States                           10.600   -0.261     9.60   \n",
       "21973       Hong Kong                            0.868    0.244    28.80   \n",
       "21974          Taiwan                            1.300    0.736     4.30   \n",
       "21975           China                            8.500   -0.322    11.00   \n",
       "21976   United States                            1.400    0.227    28.70   \n",
       "21977           Japan                            6.000    0.408     5.80   \n",
       "21978     Netherlands                           10.700   -0.313     7.80   \n",
       "21979       Hong Kong                            6.300    0.384     4.70   \n",
       "21980   United States                            2.000    0.370     2.40   \n",
       "21981   United States                            4.200    0.341     4.20   \n",
       "21982     Switzerland                           10.700    0.212     4.30   \n",
       "21983       Argentina                            3.700    0.407    15.30   \n",
       "21984           Japan                            0.427    0.097    28.30   \n",
       "21985           Japan                            8.900    0.280     8.80   \n",
       "21986          Taiwan                           10.600    0.151     4.00   \n",
       "21987          France                            3.400    0.575    10.90   \n",
       "21988   United States                            1.200    0.217    28.10   \n",
       "21989     Switzerland                            6.800    0.221     5.80   \n",
       "21990  United Kingdom                           10.600    0.249     5.40   \n",
       "21991           Japan                            0.522    0.062    28.00   \n",
       "21992           China                            2.000    0.643     6.00   \n",
       "21993   United States                            8.400   -0.047     6.80   \n",
       "21994           China                            3.800   -0.024    13.60   \n",
       "21995         Germany                           10.600    0.249     4.50   \n",
       "21996     Switzerland                            0.555    0.131    27.90   \n",
       "21997          Sweden                            0.630    0.639    10.20   \n",
       "21998   United States                            2.300    0.316     4.40   \n",
       "21999           Japan                            0.523    0.071    27.90   \n",
       "22000           India                            4.200    0.469     3.60   \n",
       "\n",
       "       Market_value  \n",
       "0           247.420  \n",
       "1           226.610  \n",
       "2           202.290  \n",
       "3           358.980  \n",
       "4           170.970  \n",
       "5           174.470  \n",
       "6           410.650  \n",
       "7           208.250  \n",
       "8           116.840  \n",
       "9            93.990  \n",
       "10          198.140  \n",
       "11          217.690  \n",
       "12          124.130  \n",
       "13           97.030  \n",
       "14           87.220  \n",
       "15          163.790  \n",
       "16          201.360  \n",
       "17           94.790  \n",
       "18          149.370  \n",
       "19          152.620  \n",
       "20           79.830  \n",
       "21          107.390  \n",
       "22           87.640  \n",
       "23           77.620  \n",
       "24           83.310  \n",
       "25           79.760  \n",
       "26          115.750  \n",
       "27           65.150  \n",
       "28          229.780  \n",
       "29          133.370  \n",
       "...             ...  \n",
       "21971         1.200  \n",
       "21972         4.700  \n",
       "21973         2.600  \n",
       "21974         4.300  \n",
       "21975         4.100  \n",
       "21976         4.300  \n",
       "21977         5.200  \n",
       "21978         3.100  \n",
       "21979         5.400  \n",
       "21980         8.900  \n",
       "21981         8.800  \n",
       "21982         5.100  \n",
       "21983         5.100  \n",
       "21984         0.721  \n",
       "21985         4.300  \n",
       "21986         1.800  \n",
       "21987         4.500  \n",
       "21988         3.900  \n",
       "21989         7.300  \n",
       "21990         4.400  \n",
       "21991         0.739  \n",
       "21992         6.000  \n",
       "21993         6.400  \n",
       "21994         9.000  \n",
       "21995         3.100  \n",
       "21996         1.700  \n",
       "21997         3.800  \n",
       "21998        10.100  \n",
       "21999         0.595  \n",
       "22000         6.700  \n",
       "\n",
       "[22001 rows x 14 columns]"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_concat = pd.concat([df_2007, df_2008, df_2009, \n",
    "                       df_2010, df_2011, df_2012, \n",
    "                       df_2013_all, df_2014, \n",
    "                       df_2015, df_2016, df_2017], ignore_index=True)\n",
    "df_concat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_concat.to_csv('data_forbes_concat.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the shape of DataFrame:  (22001, 14)\n",
      "Year               int64\n",
      "Rank               int64\n",
      "Company_cn_en     object\n",
      "Company_en        object\n",
      "Company_cn        object\n",
      "Country_cn_en     object\n",
      "Country_cn        object\n",
      "Country_en        object\n",
      "Industry_cn       object\n",
      "Industry_en       object\n",
      "Sales            float64\n",
      "Profits          float64\n",
      "Assets           float64\n",
      "Market_value     float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print('the shape of DataFrame: ', df_concat.shape)\n",
    "print(df_concat.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "source": [
    "* 若 \"Country_en\"列有空值，则用\"Conutry_cn\"列的值替换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_concat.loc[df_concat['Country_en']=='', 'Country_en'] = df_concat.loc[df_concat['Country_en']=='', 'Country_cn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# df_concat[df_concat['Year']==2011]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_concat.to_csv('data_forbes_concat-1.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*　将国家名称统一成英文名称，这里主要用的是　replace()方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "list_origin = [']','AR', 'AS','AU', 'US', 'BE', 'BR', 'BS', 'BU', 'CA', 'CH', 'CI',\n",
    "              'CN-HK', 'CN-TA', 'CO', 'CZ', 'DE', 'EG', 'FI', 'FR', 'GE',\n",
    "              'GR', 'Hong Kong', 'Hong Kong/China', 'HU', 'IC', 'ID', 'IN', 'IR',\n",
    "              'IS','IT', 'JA', 'JO', 'KO','LI', 'LU', 'MX', 'NL', 'NO', 'NZ',\n",
    "               'PA', 'PE', 'PH', 'PK', 'PL', 'PO', 'RU', 'SI', 'SP', 'SU',\n",
    "              'SW', 'SZ', 'Taiwan', 'TH', 'TU', 'UK', 'VE', '阿根廷', '阿联酋',\n",
    "              '阿曼', '埃及', '爱尔兰', '奥地利', '澳大利亚', '巴基斯坦', '巴林',\n",
    "              '巴拿马', '巴西', '百慕大', '比利时', '波多黎各', '波兰', '丹麦',\n",
    "              '德国', '多哥', '俄罗斯', '法国', '菲律宾', '芬兰', '哥伦比亚',\n",
    "              '哈萨克斯坦', '海峡群岛', '韩国', '荷兰', '加拿大', '捷克共和国',\n",
    "              '卡塔尔', '开曼群岛', '科威特', '克罗地亚', '黎巴嫩', '利比里亚',\n",
    "              '列支敦士登', '列支敦斯登', '卢森堡', '马来西亚', '毛里求斯',\n",
    "              '美国', '秘鲁', '摩洛哥', '墨西哥', '南非', '尼日利亚', '挪威',\n",
    "              '葡萄牙', '日本', '瑞典', '瑞士', '塞浦路斯', '沙特$',\n",
    "              '沙特阿拉伯', '斯洛伐克', '泰国', '土耳其', '委内瑞拉', '西班牙',\n",
    "              '希腊', '新加坡', '新西兰', '匈牙利', '以色列', '意大利',\n",
    "              '印度$', '印度尼西亚', '印尼', '英国', '约旦', '越南', '智利',\n",
    "              '中国大陆', '中国台湾', '中国香港', 'CN$', '中国$', 'Netherlands']\n",
    "\n",
    "list_replace = ['','Argentina', 'Austria','Australia', 'United States', 'Belgium',\n",
    "                'Brazil', 'Bahamas', 'Bermuda', 'Canada', 'Chile', 'Cayman Islands',\n",
    "               'China-HongKong', 'China-Taiwan', 'Colombia', 'Czech Republic',\n",
    "               'Denmark', 'Egypt', 'Finland', 'France', 'Germany', 'Greece', 'China-HongKong',\n",
    "               'China-HongKong', 'Hungary', 'Iceland', 'Indonesia', 'India', 'Ireland', 'Israel',\n",
    "               'Italy', 'Japan', 'Jordan', 'South Korea','Liberia', 'Luxembourg', 'Mexico',\n",
    "               'Netherland', 'Norway', 'New Zealand', 'Panama', 'Peru', 'Philippines',\n",
    "               'Pakistan', 'Poland', 'Portugal', 'Russia', 'Singapore', 'Spain',\n",
    "               'Saudi Arabia', 'Sweden', 'Switzerland', 'China-Taiwan',\n",
    "               'Thailand', 'Turkey', 'United Kingdom', 'Venezuela', 'Argentina',\n",
    "               'United Arab Emirates', 'Oman', 'Egypt', 'Ireland', 'Austria', 'Australia',\n",
    "               'Pakistan', 'Bahrain', 'Panama', 'Brazil', 'Bermuda', 'Belgium',\n",
    "               'Puerto Rico', 'Poland', 'Denmark', 'Germany', 'Togo', 'Russia',\n",
    "               'France', 'Philippines', 'Finland', 'Colombia', 'Kazakhstan',\n",
    "               'Channel Islands', 'South Korea', 'Netherland', 'Canada',\n",
    "               'Czech Republic', 'Qatar', 'Cayman Islands', 'Kuwait', 'Croatia', 'Lebanon',\n",
    "               'Liberia', 'Liechtenstein', 'Liechtenstein', 'Luxembourg', 'Malaysia',\n",
    "               'Mauritius', 'United States', 'Peru', 'Morocco', 'Mexico', 'South Africa',\n",
    "               'Nigeria', 'Norway', 'Portugal', 'Japan', 'Sweden', 'Switzerland', 'Cyprus',\n",
    "               'Saudi Arabia', 'Saudi Arabia', 'Slovakia', 'Thailand', 'Turkey', 'Venezuela',\n",
    "               'Spain', 'Greece', 'Singapore', 'New Zealand', 'Hungary', 'Israel', 'Italy',\n",
    "               'India', 'Indonesia', 'Indonesia', 'United Kingdom', 'Jordan', 'Vietnam',\n",
    "               'Chile',  'China', 'China-Taiwan', 'China-HongKong', 'China', 'China',\n",
    "               'Netherland']\n",
    "\n",
    "df_concat['Country_en'] = df_concat['Country_en'].replace(list_origin,list_replace, regex=True)\n",
    "\n",
    "# df_concat['Country_en'] = df_concat['Country_en'].replace(['CN','中国'],['China', 'China'], regex=True)\n",
    "\n",
    "# df_concat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_concat.to_csv('data_forbes_concat-2.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 进一步替换，包括一家公司属于多个国家的情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 进一步替换，包括一家公司属于多个国家的情况\n",
    "# 注意这里没有 regex=True \n",
    "df_concat['Country_en'] = df_concat['Country_en'].replace(['China-China-Taiwan',r'China-HongKong/China', r'Australia)/United Kingdom(United Kingdom',\n",
    "                                                          r'Netherland)/United Kingdom(United Kingdom', r'Panama)/United Kingdom(United Kingdom',\n",
    "                                                          r'SA)/United Kingdom(United Kingdom', r'United Kingdom)/Australia(SA', r'United Kingdom)/Netherland(Netherland',\n",
    "                                                          r'United Kingdom)/South Africa(SA' , 'Netherland/United Kingdom', 'Panama/United Kingdom',\n",
    "                                                          'Australia/United Kingdom'],\n",
    "                                                          ['China-Taiwan', 'China-HongKong', 'United Kingdom/Australia', 'United Kingdom/Netherland',\n",
    "                                                          'United Kingdom/Panama', 'United Kingdom/Australia', 'United Kingdom/Australia',\n",
    "                                                          'United Kingdom/Netherland', 'United Kingdom/South Africa', 'United Kingdom/Netherland',\n",
    "                                                          'United Kingdom/Panama', 'United Kingdom/Australia'])\n",
    "\n",
    "\n",
    "# df_concat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_concat.to_csv('data_forbes_concat-3.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 有两个特殊情况，同样的英文缩写，代表的国家可能不同\n",
    "* 需要进一步处理\n",
    "* SA可以代表Australia or South Africa\n",
    "* MA可以代表 Malaysia or Morocco\n",
    "* 如下图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "处理这类特殊情况的思路与步骤为：\n",
    "\n",
    "（a）将此类英文缩写用空白值替换，\n",
    "\n",
    "（b）将空白值替换为当前样本的中文国家名称\n",
    "\n",
    "（c）将中文国家名称替换为各自的英文国家名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 注意需要以 \"$\"结尾\n",
    "df_concat['Country_en'] = df_concat['Country_en'].replace(['MA$','SA$'],['', ''], regex=True)\n",
    "\n",
    "# df_concat[df_concat['Country_en']=='']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 若 \"Country_en\"列有空值，则用\"Conntry_cn\"列的值替换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_concat.loc[df_concat['Country_en']=='', 'Country_en'] = df_concat.loc[df_concat['Country_en']=='', 'Country_cn']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_concat.to_csv('data_forbes_concat-4.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_concat['Country_en'] = df_concat['Country_en'].replace(['澳大利亚','马来西亚', '摩洛哥', '南非'],\n",
    "                                                          ['Australia', 'Malaysia', 'Morocco', 'South Africa'])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_concat.to_csv('data_forbes_concat.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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