{"id":985885,"date":"2024-12-27T07:40:24","date_gmt":"2024-12-26T23:40:24","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/985885.html"},"modified":"2024-12-27T07:40:26","modified_gmt":"2024-12-26T23:40:26","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96ods%e6%96%87%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/985885.html","title":{"rendered":"Python\u5982\u4f55\u8bfb\u53d6ods\u6587\u4ef6"},"content":{"rendered":"

\"Python\u5982\u4f55\u8bfb\u53d6ods\u6587\u4ef6\"<\/p>\n

Python\u8bfb\u53d6ODS\u6587\u4ef6\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528ezodf<\/code>\u5e93\u3001\u4f7f\u7528pandas<\/code>\u7ed3\u5408odfpy<\/code>\u5e93\u3001\u4f7f\u7528pyexcel-ods<\/code>\u5e93\u3002<\/strong>\u5728\u8be6\u7ec6\u63cf\u8ff0\u4e2d\uff0c\u6211\u4eec\u5c06\u91cd\u70b9\u63a2\u8ba8\u5982\u4f55\u4f7f\u7528pandas<\/code>\u7ed3\u5408odfpy<\/code>\u5e93\u8fdb\u884cODS\u6587\u4ef6\u8bfb\u53d6\uff0c\u8fd9\u79cd\u65b9\u6cd5\u5229\u7528\u4e86pandas<\/code>\u7684\u5f3a\u5927\u6570\u636e\u5904\u7406\u80fd\u529b\uff0c\u4f7f\u5f97\u8bfb\u53d6ODS\u6587\u4ef6\u540e\u7684\u6570\u636e\u5904\u7406\u53d8\u5f97\u66f4\u52a0\u4fbf\u6377\u3002<\/p>\n<\/p>\n

\u5728\u4f7f\u7528pandas<\/code>\u7ed3\u5408odfpy<\/code>\u5e93\u65f6\uff0c\u6211\u4eec\u9700\u8981\u9996\u5148\u5b89\u88c5\u4e24\u4e2a\u5e93\uff0cpandas<\/code>\u7528\u4e8e\u6570\u636e\u5904\u7406\uff0c\u800codfpy<\/code>\u7528\u4e8eODS\u6587\u4ef6\u7684\u89e3\u6790\u3002\u901a\u8fc7odfpy<\/code>\u8bfb\u53d6ODS\u6587\u4ef6\u4e2d\u7684\u8868\u683c\u5185\u5bb9\uff0c\u7136\u540e\u5c06\u6570\u636e\u8f6c\u6362\u4e3apandas<\/code>\u7684DataFrame\u7ed3\u6784\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5904\u7406\u3002\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u52bf\u5728\u4e8e\u53ef\u4ee5\u65b9\u4fbf\u5730\u5229\u7528pandas<\/code>\u63d0\u4f9b\u7684\u4e30\u5bcc\u529f\u80fd\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u6790\u548c\u64cd\u4f5c\uff0c\u6bd4\u5982\u6570\u636e\u8fc7\u6ee4\u3001\u5206\u7ec4\u6c47\u603b\u7b49\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u5fc5\u8981\u7684Python\u5e93<\/p>\n<\/p>\n

\u5728\u5f00\u59cb\u4f7f\u7528Python\u8bfb\u53d6ODS\u6587\u4ef6\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86\u76f8\u5173\u7684Python\u5e93\u3002\u8fd9\u4e9b\u5e93\u5305\u62ecpandas<\/code>\u3001odfpy<\/code>\u548c\u5176\u4ed6\u53ef\u9009\u5e93\u5982ezodf<\/code>\u6216pyexcel-ods<\/code>\u3002\u53ef\u4ee5\u4f7f\u7528Python\u5305\u7ba1\u7406\u5de5\u5177pip<\/code>\u6765\u5b89\u88c5\u8fd9\u4e9b\u5e93\u3002<\/p>\n<\/p>\n

pip install pandas odfpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5982\u679c\u4f60\u9009\u62e9\u4f7f\u7528ezodf<\/code>\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install ezodf<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528PANDAS\u7ed3\u5408ODFPY\u5e93\u8bfb\u53d6ODS\u6587\u4ef6<\/p>\n<\/p>\n
    \n
  1. \u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
    \u4f7f\u7528odfpy<\/code>\u5e93\u6765\u89e3\u6790ODS\u6587\u4ef6\uff0c\u5e76\u4f7f\u7528pandas<\/code>\u5c06\u6570\u636e\u8f6c\u6362\u4e3aDataFrame\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
    import pandas as pd<\/p>\n
    from odf.opendocument import load<\/p>\n
    from odf.table import Table, TableRow, TableCell<\/p>\n
    def read_ods(file_path):<\/p>\n
        spreadsheet = load(file_path)<\/p>\n
        for sheet in spreadsheet.spreadsheet.getElementsByType(Table):<\/p>\n
            rows = []<\/p>\n
            for row in sheet.getElementsByType(TableRow):<\/p>\n
                row_data = []<\/p>\n
                for cell in row.getElementsByType(TableCell):<\/p>\n
                    repeat = cell.getAttribute("numbercolumnsrepeated")<\/p>\n
                    value = cell.firstChild and cell.firstChild.data or ""<\/p>\n
                    if repeat:<\/p>\n
                        row_data.extend([value] * int(repeat))<\/p>\n
                    else:<\/p>\n
                        row_data.append(value)<\/p>\n
                rows.append(row_data)<\/p>\n
            df = pd.DataFrame(rows[1:], columns=rows[0])<\/p>\n
            return df<\/p>\n
    \u4f7f\u7528\u51fd\u6570\u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/h2>\n
    file_path = 'your_file.ods'<\/p>\n
    df = read_ods(file_path)<\/p>\n
    print(df)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u8fd9\u6bb5\u4ee3\u7801\u9996\u5148\u52a0\u8f7dODS\u6587\u4ef6\uff0c\u7136\u540e\u904d\u5386\u6bcf\u4e2a\u8868\u683c\u548c\u884c\uff0c\u6700\u540e\u5c06\u6570\u636e\u8f6c\u6362\u4e3apandas<\/code>\u7684DataFrame\u683c\u5f0f\u3002\u8fd9\u6837\u505a\u7684\u597d\u5904\u662f\u53ef\u4ee5\u5229\u7528pandas<\/code>\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\u6765\u8fdb\u4e00\u6b65\u64cd\u4f5c\u8fd9\u4e9b\u6570\u636e\u3002<\/p>\n<\/p>\n
      \n
    1. \u6570\u636e\u5904\u7406<\/strong><\/li>\n<\/ol>\n
      \u5229\u7528pandas<\/code>\uff0c\u4f60\u53ef\u4ee5\u5bf9\u8bfb\u53d6\u7684\u6570\u636e\u8fdb\u884c\u591a\u79cd\u64cd\u4f5c\uff0c\u5982\u6570\u636e\u8fc7\u6ee4\u3001\u6392\u5e8f\u3001\u805a\u5408\u7b49\u3002\u8fd9\u4f7f\u5f97\u5728\u5206\u6790ODS\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u65f6\uff0c\u80fd\u591f\u66f4\u52a0\u7075\u6d3b\u548c\u9ad8\u6548\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
      # \u8fc7\u6ee4\u6570\u636e<\/p>\n
      filtered_df = df[df['ColumnName'] > 10]<\/p>\n
      \u6392\u5e8f\u6570\u636e<\/strong><\/h2>\n
      sorted_df = df.sort_values(by='ColumnName')<\/p>\n
      \u805a\u5408\u6570\u636e<\/strong><\/h2>\n
      aggregated_data = df.groupby('Category').sum()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u4e09\u3001\u4f7f\u7528EZODF\u5e93\u8bfb\u53d6ODS\u6587\u4ef6<\/p>\n<\/p>\n
      ezodf<\/code>\u5e93\u662f\u53e6\u4e00\u4e2a\u8bfb\u53d6ODS\u6587\u4ef6\u7684\u9009\u62e9\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u63a5\u53e3\u6765\u8bbf\u95eeODS\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
        \n
      1. \u5b89\u88c5EZODF<\/strong><\/li>\n<\/ol>\n
        \u5982\u524d\u6240\u8ff0\uff0c\u901a\u8fc7pip install ezodf<\/code>\u6765\u5b89\u88c5\u5e93\u3002<\/p>\n<\/p>\n
          \n
        1. \u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
          \u4ee5\u4e0b\u662f\u4f7f\u7528ezodf<\/code>\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
          import ezodf<\/p>\n
          def read_ods_with_ezodf(file_path):<\/p>\n
              ezodf.config.set_table_expand_strategy('all')<\/p>\n
              ods = ezodf.opendoc(file_path)<\/p>\n
              sheet = ods.sheets[0]<\/p>\n
              data = []<\/p>\n
              for row in sheet.rows():<\/p>\n
                  data.append([cell.value for cell in row])<\/p>\n
              return pd.DataFrame(data[1:], columns=data[0])<\/p>\n
          \u4f7f\u7528\u51fd\u6570\u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/h2>\n
          df_ezodf = read_ods_with_ezodf(file_path)<\/p>\n
          print(df_ezodf)<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e0eodfpy<\/code>\u4e0d\u540c\u7684\u662f\uff0cezodf<\/code>\u76f4\u63a5\u5c06ODS\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u8bfb\u53d6\u5230\u5185\u5b58\u4e2d\uff0c\u4f7f\u7528pandas<\/code>\u6765\u8f6c\u6362\u4e3aDataFrame\u683c\u5f0f\u3002\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u4ee3\u7801\u66f4\u7b80\u6d01\uff0c\u4f46\u5728\u5904\u7406\u975e\u5e38\u5927\u7684\u6587\u4ef6\u65f6\u53ef\u80fd\u4f1a\u66f4\u8017\u5185\u5b58\u3002<\/p>\n<\/p>\n
          \u56db\u3001\u4f7f\u7528PYEXCEL-ODS\u5e93\u8bfb\u53d6ODS\u6587\u4ef6<\/p>\n<\/p>\n
          pyexcel-ods<\/code>\u5e93\u63d0\u4f9b\u4e86\u53e6\u4e00\u79cd\u8bfb\u53d6ODS\u6587\u4ef6\u7684\u65b9\u5f0f\uff0c\u9002\u5408\u4e8e\u7b80\u5355\u7684ODS\u6587\u4ef6\u8bfb\u53d6\u4efb\u52a1\u3002<\/p>\n<\/p>\n
            \n
          1. \u5b89\u88c5PYEXCEL-ODS<\/strong><\/li>\n<\/ol>\n
            \u540c\u6837\u901a\u8fc7pip install pyexcel-ods<\/code>\u6765\u5b89\u88c5\u5e93\u3002<\/p>\n<\/p>\n
              \n
            1. \u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/li>\n<\/ol>\n
              \u4ee5\u4e0b\u662f\u4f7f\u7528pyexcel-ods<\/code>\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
              import pyexcel_ods<\/p>\n
              def read_ods_with_pyexcel(file_path):<\/p>\n
                  data = pyexcel_ods.get_data(file_path)<\/p>\n
                  sheet_name = list(data.keys())[0]  # \u83b7\u53d6\u7b2c\u4e00\u4e2a\u5de5\u4f5c\u8868\u7684\u540d\u79f0<\/p>\n
                  return pd.DataFrame(data[sheet_name][1:], columns=data[sheet_name][0])<\/p>\n
              \u4f7f\u7528\u51fd\u6570\u8bfb\u53d6ODS\u6587\u4ef6<\/strong><\/h2>\n
              df_pyexcel = read_ods_with_pyexcel(file_path)<\/p>\n
              print(df_pyexcel)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              pyexcel-ods<\/code>\u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u5355\u7684\u65b9\u6cd5\u6765\u8bfb\u53d6ODS\u6587\u4ef6\uff0c\u5e76\u4e14\u4e0e\u5176\u4ed6\u5e93\u76f8\u6bd4\uff0c\u4ee3\u7801\u66f4\u52a0\u7b80\u6d01\u3002\u4f46\u662f\uff0c\u8fd9\u79cd\u65b9\u6cd5\u5728\u5904\u7406\u590d\u6742\u7684ODS\u6587\u4ef6\u65f6\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u9650\u5236\u3002<\/p>\n<\/p>\n
              \u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n
              Python\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u8bfb\u53d6ODS\u6587\u4ef6\uff0c\u5305\u62ecpandas<\/code>\u7ed3\u5408odfpy<\/code>\u3001ezodf<\/code>\u548cpyexcel-ods<\/code>\u3002<\/strong>\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u7f3a\u70b9\uff0c\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u9700\u6c42\u548c\u6587\u4ef6\u7684\u590d\u6742\u6027\u3002\u5bf9\u4e8e\u9700\u8981\u8fdb\u884c\u590d\u6742\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u7684\u4efb\u52a1\uff0c\u63a8\u8350\u4f7f\u7528pandas<\/code>\u7ed3\u5408odfpy<\/code>\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\u3002\u800c\u5bf9\u4e8e\u7b80\u5355\u7684\u8bfb\u53d6\u4efb\u52a1\uff0cezodf<\/code>\u548cpyexcel-ods<\/code>\u90fd\u662f\u4e0d\u9519\u7684\u9009\u62e9\u3002\u5728\u4f7f\u7528\u8fd9\u4e9b\u5e93\u4e4b\u524d\uff0c\u8bf7\u786e\u4fdd\u5b89\u88c5\u4e86\u76f8\u5e94\u7684Python\u5305\u3002\u901a\u8fc7\u672c\u6587\u6240\u8ff0\u7684\u65b9\u6cd5\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06ODS\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u8bfb\u53d6\u5230Python\u73af\u5883\u4e2d\uff0c\u5e76\u5229\u7528Python\u7684\u5f3a\u5927\u529f\u80fd\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
              \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
               \u5982\u4f55\u5728Python\u4e2d\u5b89\u88c5\u8bfb\u53d6ODS\u6587\u4ef6\u6240\u9700\u7684\u5e93\uff1f<\/strong>
              \u8981\u5728Python\u4e2d\u8bfb\u53d6ODS\u6587\u4ef6\uff0c\u60a8\u9700\u8981\u5b89\u88c5odfpy<\/code>\u6216pyexcel-ods<\/code>\u7b49\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u5728\u547d\u4ee4\u884c\u4e2d\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5\uff1a  <\/p>\n
              pip install odfpy\n<\/code><\/pre>\n
              \u6216  <\/p>\n
              pip install pyexcel-ods\n<\/code><\/pre>\n
              \u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u60a8\u5c31\u53ef\u4ee5\u5728\u4ee3\u7801\u4e2d\u5bfc\u5165\u8fd9\u4e9b\u5e93\u4ee5\u5904\u7406ODS\u6587\u4ef6\u3002<\/p>\n
              \u8bfb\u53d6ODS\u6587\u4ef6\u65f6\u5982\u4f55\u5904\u7406\u6570\u636e\uff1f<\/strong>
              \u4f7f\u7528odfpy<\/code>\u5e93\u8bfb\u53d6ODS\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u52a0\u8f7d\u6587\u4ef6\u5e76\u904d\u5386\u5de5\u4f5c\u8868\u4e2d\u7684\u884c\u548c\u5355\u5143\u683c\u6765\u5904\u7406\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
              from odf.opendocument import OpenDocumentSpreadsheet\nfrom odf.table import Table, TableCell, TableRow\n\ndoc = OpenDocumentSpreadsheet('example.ods')\nfor table in doc.getElementsByType(Table):\n    for row in table.getElementsByType(TableRow):\n        for cell in row.getElementsByType(TableCell):\n            print(cell.plAI<\/a>ntext())\n<\/code><\/pre>\n
              \u8fd9\u4e2a\u4ee3\u7801\u7247\u6bb5\u5c06\u6253\u5370\u51faODS\u6587\u4ef6\u4e2d\u6240\u6709\u5355\u5143\u683c\u7684\u5185\u5bb9\u3002<\/p>\n
              \u662f\u5426\u53ef\u4ee5\u5c06ODS\u6587\u4ef6\u8f6c\u6362\u4e3a\u5176\u4ed6\u683c\u5f0f\uff1f<\/strong>
              \u662f\u7684\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528Python\u5c06ODS\u6587\u4ef6\u8f6c\u6362\u4e3a\u5176\u4ed6\u683c\u5f0f\uff0c\u5982CSV\u6216Excel\u3002\u901a\u8fc7\u4f7f\u7528pandas<\/code>\u5e93\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5b9e\u73b0\u8fd9\u4e00\u70b9\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5b89\u88c5pandas<\/code>\u548codfpy<\/code>\u5e93\u3002\u4ee5\u4e0b\u662f\u8f6c\u6362ODS\u6587\u4ef6\u4e3aCSV\u683c\u5f0f\u7684\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
              import pandas as pd\n\ndf = pd.read_excel('example.ods', engine='odf')\ndf.to_csv('output.csv', index=False)\n<\/code><\/pre>\n
              \u8fd9\u4e2a\u65b9\u6cd5\u5c06ODS\u6587\u4ef6\u8bfb\u53d6\u4e3aDataFrame\uff0c\u7136\u540e\u5c06\u5176\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u53d6ODS\u6587\u4ef6\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528ezodf\u5e93\u3001\u4f7f\u7528pandas\u7ed3\u5408odfpy\u5e93\u3001\u4f7f\u7528pyexce […]","protected":false},"author":3,"featured_media":985895,"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\/985885"}],"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=985885"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/985885\/revisions"}],"predecessor-version":[{"id":985897,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/985885\/revisions\/985897"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/985895"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=985885"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=985885"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=985885"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}