{"id":957223,"date":"2024-12-27T02:54:50","date_gmt":"2024-12-26T18:54:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/957223.html"},"modified":"2024-12-27T02:54:53","modified_gmt":"2024-12-26T18:54:53","slug":"python%e5%a6%82%e4%bd%95%e8%ae%be%e7%bd%ae%e8%a1%a8%e6%a0%bc%e5%90%88%e5%b9%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/957223.html","title":{"rendered":"python\u5982\u4f55\u8bbe\u7f6e\u8868\u683c\u5408\u5e76"},"content":{"rendered":"

\"python\u5982\u4f55\u8bbe\u7f6e\u8868\u683c\u5408\u5e76\"<\/p>\n

\u5728Python\u4e2d\u8bbe\u7f6e\u8868\u683c\u5408\u5e76\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528openpyxl\u5e93\u3001\u4f7f\u7528XlsxWriter\u5e93\u6765\u5b9e\u73b0\u3002Pandas\u5e93\u64c5\u957f\u5904\u7406\u6570\u636e\uff0c\u800copenpyxl\u548cXlsxWriter\u5e93\u5219\u66f4\u9002\u5408\u5904\u7406Excel\u6587\u4ef6\u4e2d\u7684\u5177\u4f53\u683c\u5f0f\u548c\u5e03\u5c40\u3002\u8fd9\u91cc\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4f7f\u7528Pandas\u5e93\u7684\u65b9\u6cd5\u3002<\/strong><\/p>\n<\/p>\n

\u8981\u8be6\u7ec6\u4ecb\u7ecdPandas\u5e93\u7684\u4f7f\u7528\uff0c\u6211\u4eec\u9996\u5148\u8981\u4e86\u89e3Pandas\u5e93\u662f\u4e00\u4e2a\u7528\u4e8e\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u8868\u683c\u6570\u636e\u65f6\u3002Pandas\u5e93\u63d0\u4f9b\u4e86DataFrame\u548cSeries\u8fd9\u4e24\u4e2a\u4e3b\u8981\u7684\u6570\u636e\u7ed3\u6784\uff0cDataFrame\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u4e2d\u7684\u8868\u683c\u3002\u901a\u8fc7Pandas\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5408\u5e76\u4e0d\u540c\u7684\u6570\u636e\u96c6\uff0c\u6267\u884c\u6570\u636e\u6e05\u7406\uff0c\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

\u4e00\u3001PANDAS\u5e93\u7684\u5b89\u88c5\u4e0e\u57fa\u672c\u4f7f\u7528<\/strong><\/p>\n<\/p>\n

Pandas\u5e93\u662f\u57fa\u4e8ePython\u7684\u5f00\u6e90\u6570\u636e\u5206\u6790\u5e93\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\u5b83\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5bfc\u5165Pandas\u5e93\u5f00\u59cb\u4f7f\u7528\u3002\u901a\u5e38\u6211\u4eec\u4f1a\u5c06Pandas\u5e93\u5bfc\u5165\u4e3apd<\/code>\uff0c\u56e0\u4e3a\u8fd9\u6837\u53ef\u4ee5\u7b80\u5316\u4ee3\u7801\u4e66\u5199\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
Pandas\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u8bfb\u53d6\u548c\u5199\u5165\u6570\u636e\u7684\u65b9\u6cd5\u3002\u6700\u5e38\u89c1\u7684\u683c\u5f0f\u4e4b\u4e00\u662fCSV\u6587\u4ef6\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pd.read_csv()<\/code>\u51fd\u6570\u8bfb\u53d6CSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('your_file.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u6570\u636e\u5408\u5e76\u7684\u57fa\u672c\u65b9\u6cd5<\/strong><\/p>\n<\/p>\n
\u5728Pandas\u4e2d\uff0c\u5408\u5e76\u6570\u636e\u7684\u57fa\u672c\u65b9\u6cd5\u6709\u4e09\u79cd\uff1amerge<\/code>\u3001concat<\/code>\u548cjoin<\/code>\u3002<\/p>\n<\/p>\n
    \n
  1. \u4f7f\u7528merge\u51fd\u6570<\/strong><\/li>\n<\/ol>\n
    merge()<\/code>\u51fd\u6570\u7528\u4e8e\u5408\u5e76\u4e24\u4e2aDataFrame\uff0c\u7c7b\u4f3c\u4e8eSQL\u4e2d\u7684JOIN\u64cd\u4f5c\u3002\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u4e00\u4e2a\u6216\u591a\u4e2a\u952e\u6765\u5b9e\u73b0\u5408\u5e76\uff1a<\/p>\n<\/p>\n
    df1 = pd.DataFrame({<\/p>\n
        'key': ['A', 'B', 'C', 'D'],<\/p>\n
        'value': [1, 2, 3, 4]<\/p>\n
    })<\/p>\n
    df2 = pd.DataFrame({<\/p>\n
        'key': ['B', 'D', 'E'],<\/p>\n
        'value': [5, 6, 7]<\/p>\n
    })<\/p>\n
    result = pd.merge(df1, df2, on='key', how='inner')<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528on='key'<\/code>\u6307\u5b9a\u4e86\u5408\u5e76\u7684\u952e\uff0chow='inner'<\/code>\u8868\u793a\u53ea\u4fdd\u7559\u4e24\u4e2aDataFrame\u4e2d\u90fd\u5b58\u5728\u7684\u952e\u3002<\/p>\n<\/p>\n
      \n
    1. \u4f7f\u7528concat\u51fd\u6570<\/strong><\/li>\n<\/ol>\n
      concat()<\/code>\u51fd\u6570\u7528\u4e8e\u6cbf\u6307\u5b9a\u8f74\u8fde\u63a5\u591a\u4e2aDataFrame\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6eaxis=0<\/code>\u6216axis=1<\/code>\u6765\u6307\u5b9a\u7eb5\u5411\u6216\u6a2a\u5411\u5408\u5e76\uff1a<\/p>\n<\/p>\n
      df1 = pd.DataFrame({<\/p>\n
          'A': ['A0', 'A1', 'A2', 'A3'],<\/p>\n
          'B': ['B0', 'B1', 'B2', 'B3']<\/p>\n
      })<\/p>\n
      df2 = pd.DataFrame({<\/p>\n
          'A': ['A4', 'A5', 'A6', 'A7'],<\/p>\n
          'B': ['B4', 'B5', 'B6', 'B7']<\/p>\n
      })<\/p>\n
      result = pd.concat([df1, df2], axis=0)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u4f7f\u7528join\u51fd\u6570<\/strong><\/li>\n<\/ol>\n
        join()<\/code>\u51fd\u6570\u7528\u4e8e\u5c06\u4e00\u4e2aDataFrame\u4e0e\u53e6\u4e00\u4e2aDataFrame\u7684\u7d22\u5f15\u5bf9\u9f50\u3002\u5b83\u4e3b\u8981\u7528\u4e8e\u5408\u5e76\u7d22\u5f15\u4e0d\u540c\u4f46\u9700\u8981\u5bf9\u9f50\u7684\u6570\u636e\uff1a<\/p>\n<\/p>\n
        df1 = pd.DataFrame({<\/p>\n
            'A': ['A0', 'A1', 'A2'],<\/p>\n
            'B': ['B0', 'B1', 'B2']<\/p>\n
        }, index=['K0', 'K1', 'K2'])<\/p>\n
        df2 = pd.DataFrame({<\/p>\n
            'C': ['C0', 'C2', 'C3'],<\/p>\n
            'D': ['D0', 'D2', 'D3']<\/p>\n
        }, index=['K0', 'K2', 'K3'])<\/p>\n
        result = df1.join(df2, how='outer')<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        \u4e09\u3001\u5408\u5e76\u7684\u9ad8\u7ea7\u6280\u5de7<\/strong><\/p>\n<\/p>\n
          \n
        1. \u5904\u7406\u91cd\u590d\u503c<\/strong><\/li>\n<\/ol>\n
          \u5728\u5408\u5e76\u64cd\u4f5c\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u4f1a\u9047\u5230\u91cd\u590d\u503c\u7684\u95ee\u9898\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u53c2\u6570suffixes<\/code>\u6765\u4e3a\u91cd\u590d\u7684\u5217\u540d\u6dfb\u52a0\u540e\u7f00\uff1a<\/p>\n<\/p>\n
          result = pd.merge(df1, df2, on='key', suffixes=('_left', '_right'))<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          1. \u63a7\u5236\u5408\u5e76\u65b9\u5f0f<\/strong><\/li>\n<\/ol>\n
            \u53ef\u4ee5\u901a\u8fc7how<\/code>\u53c2\u6570\u63a7\u5236\u5408\u5e76\u7684\u65b9\u5f0f\uff1ainner<\/code>\uff08\u9ed8\u8ba4\uff09\u3001outer<\/code>\u3001left<\/code>\u3001right<\/code>\u3002\u5176\u4e2d\uff1a<\/p>\n<\/p>\n
              \n
            • inner<\/code>\u53ea\u4fdd\u7559\u4e24\u4e2aDataFrame\u4e2d\u90fd\u5b58\u5728\u7684\u952e\u3002<\/li>\n
            • outer<\/code>\u4fdd\u7559\u6240\u6709\u952e\u3002<\/li>\n
            • left<\/code>\u4fdd\u7559\u5de6DataFrame\u4e2d\u7684\u6240\u6709\u952e\u3002<\/li>\n
            • right<\/code>\u4fdd\u7559\u53f3DataFrame\u4e2d\u7684\u6240\u6709\u952e\u3002<\/li>\n<\/ul>\n
                \n
              1. \u6839\u636e\u591a\u4e2a\u952e\u5408\u5e76<\/strong><\/li>\n<\/ol>\n
                \u53ef\u4ee5\u901a\u8fc7\u4f20\u9012\u4e00\u4e2a\u952e\u5217\u8868\u6765\u5b9e\u73b0\u591a\u952e\u5408\u5e76\uff1a<\/p>\n<\/p>\n
                result = pd.merge(df1, df2, on=['key1', 'key2'])<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u56db\u3001\u5904\u7406\u5408\u5e76\u540e\u7684\u6570\u636e<\/strong><\/p>\n<\/p>\n
                \u5408\u5e76\u540e\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u8fdb\u4e00\u6b65\u5904\u7406\u6570\u636e\uff0c\u4f8b\u5982\u5220\u9664\u91cd\u590d\u884c\u3001\u586b\u5145\u7f3a\u5931\u503c\u6216\u91cd\u65b0\u6392\u5e8f\u5217\u3002Pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u51fd\u6570\u6765\u5b9e\u73b0\u8fd9\u4e9b\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
                  \n
                1. \u5220\u9664\u91cd\u590d\u884c<\/strong><\/li>\n<\/ol>\n
                  \u53ef\u4ee5\u4f7f\u7528drop_duplicates()<\/code>\u51fd\u6570\u5220\u9664\u91cd\u590d\u884c\uff1a<\/p>\n<\/p>\n
                  result = result.drop_duplicates()<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                    \n
                  1. \u586b\u5145\u7f3a\u5931\u503c<\/strong><\/li>\n<\/ol>\n
                    \u53ef\u4ee5\u4f7f\u7528fillna()<\/code>\u51fd\u6570\u586b\u5145\u7f3a\u5931\u503c\uff1a<\/p>\n<\/p>\n
                    result = result.fillna(0)<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                      \n
                    1. \u91cd\u65b0\u6392\u5e8f\u5217<\/strong><\/li>\n<\/ol>\n
                      \u53ef\u4ee5\u901a\u8fc7\u76f4\u63a5\u91cd\u65b0\u5b9a\u4e49\u5217\u987a\u5e8f\u6765\u91cd\u65b0\u6392\u5e8f\uff1a<\/p>\n<\/p>\n
                      result = result[['key', 'value_left', 'value_right']]<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      \u4e94\u3001\u5bfc\u51fa\u5408\u5e76\u540e\u7684\u6570\u636e<\/strong><\/p>\n<\/p>\n
                      \u5b8c\u6210\u6570\u636e\u5408\u5e76\u548c\u5904\u7406\u540e\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u5c06\u7ed3\u679c\u5bfc\u51fa\u4e3a\u6587\u4ef6\u3002Pandas\u652f\u6301\u591a\u79cd\u6587\u4ef6\u683c\u5f0f\u7684\u5bfc\u51fa\uff0c\u5305\u62ecCSV\u3001Excel\u3001JSON\u7b49\uff1a<\/p>\n<\/p>\n
                        \n
                      1. \u5bfc\u51fa\u4e3aCSV\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
                        \u53ef\u4ee5\u4f7f\u7528to_csv()<\/code>\u51fd\u6570\u5bfc\u51fa\u4e3aCSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
                        result.to_csv('output.csv', index=False)<\/p>\n
                        <\/code><\/pre>\n<\/p>\n
                          \n
                        1. \u5bfc\u51fa\u4e3aExcel\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
                          \u53ef\u4ee5\u4f7f\u7528to_excel()<\/code>\u51fd\u6570\u5bfc\u51fa\u4e3aExcel\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
                          result.to_excel('output.xlsx', index=False)<\/p>\n
                          <\/code><\/pre>\n<\/p>\n
                            \n
                          1. \u5bfc\u51fa\u4e3aJSON\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
                            \u53ef\u4ee5\u4f7f\u7528to_json()<\/code>\u51fd\u6570\u5bfc\u51fa\u4e3aJSON\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
                            result.to_json('output.json')<\/p>\n
                            <\/code><\/pre>\n<\/p>\n
                            \u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528Pandas\u5e93\u8f7b\u677e\u5730\u5b9e\u73b0\u8868\u683c\u5408\u5e76\uff0c\u5e76\u8fdb\u884c\u540e\u7eed\u7684\u6570\u636e\u5904\u7406\u548c\u5bfc\u51fa\u3002Pandas\u5e93\u7684\u5f3a\u5927\u529f\u80fd\u548c\u7075\u6d3b\u6027\uff0c\u4f7f\u5176\u6210\u4e3a\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u7684\u9996\u9009\u5de5\u5177\u4e4b\u4e00\u3002<\/p>\n<\/p>\n
                            \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                             \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u5408\u5e76\u8868\u683c\uff1f<\/strong>
                            \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u975e\u5e38\u65b9\u4fbf\u5730\u5408\u5e76\u8868\u683c\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Pandas\u5e93\u3002\u4f7f\u7528pd.concat()<\/code>\u53ef\u4ee5\u5c06\u591a\u4e2aDataFrame\u6cbf\u7740\u4e00\u4e2a\u8f74\u5408\u5e76\uff0c\u4f8b\u5982\u5782\u76f4\u5408\u5e76\u6216\u6c34\u5e73\u5408\u5e76\u3002\u4e5f\u53ef\u4ee5\u4f7f\u7528pd.merge()<\/code>\u6765\u6839\u636e\u67d0\u4e9b\u5171\u540c\u7684\u5217\u8fdb\u884c\u5408\u5e76\uff0c\u8fd9\u7c7b\u4f3c\u4e8eSQL\u4e2d\u7684JOIN\u64cd\u4f5c\u3002\u5408\u5e76\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u53c2\u6570\u6765\u5904\u7406\u91cd\u590d\u503c\u6216NaN\u503c\uff0c\u4ee5\u4fbf\u83b7\u5f97\u7406\u60f3\u7684\u7ed3\u679c\u3002<\/p>\n
                            \u5728\u5408\u5e76\u8868\u683c\u65f6\uff0c\u5982\u4f55\u5904\u7406\u91cd\u590d\u6570\u636e\uff1f<\/strong>
                            \u5f53\u5408\u5e76\u591a\u4e2a\u8868\u683c\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u91cd\u590d\u6570\u636e\u3002\u53ef\u4ee5\u4f7f\u7528Pandas\u4e2d\u7684drop_duplicates()<\/code>\u51fd\u6570\u6765\u53bb\u9664\u91cd\u590d\u9879\u3002\u6b64\u51fd\u6570\u53ef\u4ee5\u5728\u5408\u5e76\u64cd\u4f5c\u4e4b\u524d\u5e94\u7528\u4e8e\u6bcf\u4e2aDataFrame\uff0c\u4e5f\u53ef\u4ee5\u5728\u5408\u5e76\u540e\u5bf9\u7ed3\u679c\u8fdb\u884c\u5904\u7406\u3002\u6b64\u5916\uff0c\u5408\u5e76\u65f6\u4e5f\u53ef\u4ee5\u901a\u8fc7how<\/code>\u53c2\u6570\u9009\u62e9\u5408\u5e76\u65b9\u5f0f\uff08\u5982inner\u3001outer\u7b49\uff09\uff0c\u4ee5\u4fbf\u5728\u5408\u5e76\u65f6\u63a7\u5236\u4fdd\u7559\u54ea\u4e9b\u6570\u636e\u3002<\/p>\n
                            \u5728\u5408\u5e76\u8868\u683c\u540e\uff0c\u5982\u4f55\u4fdd\u5b58\u7ed3\u679c\u5230CSV\u6587\u4ef6\uff1f<\/strong>
                            \u5408\u5e76\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684to_csv()<\/code>\u65b9\u6cd5\u5c06\u7ed3\u679c\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\u3002\u53ea\u9700\u6307\u5b9a\u6587\u4ef6\u540d\u548c\u6240\u9700\u7684\u53c2\u6570\uff0c\u5982index=False<\/code>\u4ee5\u907f\u514d\u5c06\u7d22\u5f15\u5199\u5165\u6587\u4ef6\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u5408\u5e76\u540e\u7684\u6570\u636e\u53ef\u4ee5\u65b9\u4fbf\u5730\u5b58\u50a8\u548c\u5206\u4eab\uff0c\u9002\u5408\u7528\u4e8e\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u6216\u62a5\u544a\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u8bbe\u7f6e\u8868\u683c\u5408\u5e76\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528openpyxl\u5e93\u3001\u4f7f\u7528XlsxWriter\u5e93\u6765\u5b9e […]","protected":false},"author":3,"featured_media":957230,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/957223"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=957223"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/957223\/revisions"}],"predecessor-version":[{"id":957232,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/957223\/revisions\/957232"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/957230"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=957223"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=957223"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=957223"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}