{"id":1077838,"date":"2025-01-08T12:05:59","date_gmt":"2025-01-08T04:05:59","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1077838.html"},"modified":"2025-01-08T12:06:01","modified_gmt":"2025-01-08T04:06:01","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86pdf%e8%bd%ac%e5%8c%96%e4%b8%baexcel-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1077838.html","title":{"rendered":"python\u5982\u4f55\u5c06pdf\u8f6c\u5316\u4e3aexcel"},"content":{"rendered":"

\"python\u5982\u4f55\u5c06pdf\u8f6c\u5316\u4e3aexcel\"<\/p>\n

Python \u5c06 PDF \u8f6c\u5316\u4e3a Excel \u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u5e93\u5982 PyMuPDF\u3001pdfplumber\u3001tabula-py\u3001pandas \u7b49\u3002<\/strong><\/p>\n<\/p>\n

\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u4ee5\u4e0b\u51e0\u79cd\u5e38\u89c1\u7684\u5e93\u548c\u65b9\u6cd5\u6765\u5b9e\u73b0 PDF \u5230 Excel \u7684\u8f6c\u6362\uff0c\u5e76\u5bf9\u5176\u4e2d\u4e00\u4e9b\u5e93\u7684\u4f7f\u7528\u65b9\u6cd5\u8fdb\u884c\u8be6\u7ec6\u63cf\u8ff0\u3002<\/p>\n<\/p>\n

\u4e00\u3001PyMuPDF<\/p>\n<\/p>\n

PyMuPDF \u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684 PDF \u64cd\u4f5c\u5e93\uff0c\u53ef\u4ee5\u7528\u6765\u4ece PDF \u4e2d\u63d0\u53d6\u6587\u672c\u3001\u56fe\u50cf\u4ee5\u53ca\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528 PyMuPDF \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002<\/p>\n<\/p>\n

    \n
  1. \u5b89\u88c5 PyMuPDF<\/li>\n<\/ol>\n

    \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5 PyMuPDF \u5e93\u3002\u4f7f\u7528 pip \u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

    pip install pymupdf<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u4f7f\u7528 PyMuPDF \u63d0\u53d6\u8868\u683c\u6570\u636e<\/li>\n<\/ol>\n
      \u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528 PyMuPDF \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\uff1a<\/p>\n<\/p>\n
      import fitz  # PyMuPDF<\/p>\n
      import pandas as pd<\/p>\n
      def extract_table_from_pdf(pdf_path, page_number):<\/p>\n
          # \u6253\u5f00 PDF \u6587\u4ef6<\/p>\n
          pdf_document = fitz.open(pdf_path)<\/p>\n
          # \u83b7\u53d6\u6307\u5b9a\u9875<\/p>\n
          page = pdf_document.load_page(page_number)<\/p>\n
          # \u63d0\u53d6\u6587\u672c<\/p>\n
          text = page.get_text("text")<\/p>\n
          # \u5047\u8bbe\u8868\u683c\u6570\u636e\u6bcf\u884c\u7528\u6362\u884c\u7b26\u5206\u9694\uff0c\u6bcf\u5217\u7528\u7a7a\u683c\u5206\u9694<\/p>\n
          rows = text.split('\\n')<\/p>\n
          table_data = [row.split() for row in rows]<\/p>\n
          # \u521b\u5efa DataFrame<\/p>\n
          df = pd.DataFrame(table_data)<\/p>\n
          return df<\/p>\n
      def save_to_excel(df, excel_path):<\/p>\n
          # \u4fdd\u5b58\u4e3a Excel \u6587\u4ef6<\/p>\n
          df.to_excel(excel_path, index=False)<\/p>\n
      \u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
      pdf_path = "example.pdf"<\/p>\n
      excel_path = "output.xlsx"<\/p>\n
      page_number = 0  # \u5047\u8bbe\u8868\u683c\u5728\u7b2c\u4e00\u9875<\/p>\n
      df = extract_table_from_pdf(pdf_path, page_number)<\/p>\n
      save_to_excel(df, excel_path)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u901a\u8fc7\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u63d0\u53d6\u51fa\u6765\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u8fd9\u91cc\u5047\u8bbe\u8868\u683c\u6570\u636e\u662f\u7528\u6362\u884c\u7b26\u548c\u7a7a\u683c\u5206\u9694\u7684\uff0c\u5b9e\u9645\u60c5\u51b5\u53ef\u80fd\u9700\u8981\u6839\u636e\u5177\u4f53 PDF \u6587\u4ef6\u8fdb\u884c\u8c03\u6574\u3002<\/p>\n<\/p>\n
      \u4e8c\u3001pdfplumber<\/p>\n<\/p>\n
      pdfplumber \u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684 PDF \u89e3\u6790\u5e93\uff0c\u5c24\u5176\u64c5\u957f\u5904\u7406\u590d\u6742\u7684\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 pdfplumber \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002<\/p>\n<\/p>\n
        \n
      1. \u5b89\u88c5 pdfplumber<\/li>\n<\/ol>\n
        \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5 pdfplumber \u5e93\u3002\u4f7f\u7528 pip \u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
        pip install pdfplumber<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u4f7f\u7528 pdfplumber \u63d0\u53d6\u8868\u683c\u6570\u636e<\/li>\n<\/ol>\n
          \u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528 pdfplumber \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\uff1a<\/p>\n<\/p>\n
          import pdfplumber<\/p>\n
          import pandas as pd<\/p>\n
          def extract_table_from_pdf(pdf_path, page_number):<\/p>\n
              # \u6253\u5f00 PDF \u6587\u4ef6<\/p>\n
              with pdfplumber.open(pdf_path) as pdf:<\/p>\n
                  # \u83b7\u53d6\u6307\u5b9a\u9875<\/p>\n
                  page = pdf.pages[page_number]<\/p>\n
                  # \u63d0\u53d6\u8868\u683c\u6570\u636e<\/p>\n
                  table = page.extract_table()<\/p>\n
              # \u521b\u5efa DataFrame<\/p>\n
              df = pd.DataFrame(table[1:], columns=table[0])<\/p>\n
              return df<\/p>\n
          def save_to_excel(df, excel_path):<\/p>\n
              # \u4fdd\u5b58\u4e3a Excel \u6587\u4ef6<\/p>\n
              df.to_excel(excel_path, index=False)<\/p>\n
          \u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
          pdf_path = "example.pdf"<\/p>\n
          excel_path = "output.xlsx"<\/p>\n
          page_number = 0  # \u5047\u8bbe\u8868\u683c\u5728\u7b2c\u4e00\u9875<\/p>\n
          df = extract_table_from_pdf(pdf_path, page_number)<\/p>\n
          save_to_excel(df, excel_path)<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u901a\u8fc7\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 pdfplumber \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002pdfplumber \u63d0\u4f9b\u4e86\u66f4\u5f3a\u5927\u7684\u8868\u683c\u89e3\u6790\u80fd\u529b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u590d\u6742\u7684\u8868\u683c\u6570\u636e\u3002<\/p>\n<\/p>\n
          \u4e09\u3001tabula-py<\/p>\n<\/p>\n
          tabula-py \u662f\u4e00\u4e2a\u57fa\u4e8e Java \u7684 Tabula \u9879\u76ee\u7684 Python \u5c01\u88c5\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u4ece PDF \u4e2d\u63d0\u53d6\u8868\u683c\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 tabula-py \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002<\/p>\n<\/p>\n
            \n
          1. \u5b89\u88c5 tabula-py<\/li>\n<\/ol>\n
            \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5 tabula-py \u5e93\u3002\u4f7f\u7528 pip \u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
            pip install tabula-py<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u4f7f\u7528 tabula-py \u63d0\u53d6\u8868\u683c\u6570\u636e<\/li>\n<\/ol>\n
              \u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528 tabula-py \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\uff1a<\/p>\n<\/p>\n
              import tabula<\/p>\n
              import pandas as pd<\/p>\n
              def extract_table_from_pdf(pdf_path, page_number):<\/p>\n
                  # \u63d0\u53d6\u8868\u683c\u6570\u636e<\/p>\n
                  tables = tabula.read_pdf(pdf_path, pages=page_number + 1, multiple_tables=True)<\/p>\n
                  # \u5047\u8bbe\u6bcf\u9875\u53ea\u6709\u4e00\u4e2a\u8868\u683c<\/p>\n
                  df = tables[0]<\/p>\n
                  return df<\/p>\n
              def save_to_excel(df, excel_path):<\/p>\n
                  # \u4fdd\u5b58\u4e3a Excel \u6587\u4ef6<\/p>\n
                  df.to_excel(excel_path, index=False)<\/p>\n
              \u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
              pdf_path = "example.pdf"<\/p>\n
              excel_path = "output.xlsx"<\/p>\n
              page_number = 0  # \u5047\u8bbe\u8868\u683c\u5728\u7b2c\u4e00\u9875<\/p>\n
              df = extract_table_from_pdf(pdf_path, page_number)<\/p>\n
              save_to_excel(df, excel_path)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u901a\u8fc7\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 tabula-py \u63d0\u53d6 PDF \u4e2d\u7684\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002tabula-py \u4f7f\u7528\u4e86 Tabula \u9879\u76ee\u7684\u5f3a\u5927\u529f\u80fd\uff0c\u80fd\u591f\u5904\u7406\u591a\u79cd\u683c\u5f0f\u7684\u8868\u683c\u6570\u636e\u3002<\/p>\n<\/p>\n
              \u56db\u3001pandas<\/p>\n<\/p>\n
              \u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u4ee5\u7ed3\u5408 pandas \u5e93\u76f4\u63a5\u5904\u7406\u4ece PDF \u4e2d\u63d0\u53d6\u7684\u6587\u672c\u6570\u636e\uff0c\u5e76\u5c06\u5176\u8f6c\u6362\u4e3a\u8868\u683c\u683c\u5f0f\u3002\u867d\u7136\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u7b80\u5355\u7684\u8868\u683c\u6570\u636e\uff0c\u4f46\u5bf9\u4e8e\u590d\u6742\u7684\u8868\u683c\u53ef\u80fd\u9700\u8981\u66f4\u591a\u7684\u5904\u7406\u3002<\/p>\n<\/p>\n
                \n
              1. \u5b89\u88c5 pandas<\/li>\n<\/ol>\n
                \u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5 pandas \u5e93\u3002\u4f7f\u7528 pip \u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
                pip install pandas<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                1. \u4f7f\u7528 pandas \u5904\u7406\u8868\u683c\u6570\u636e<\/li>\n<\/ol>\n
                  \u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528 pandas \u5904\u7406\u4ece PDF \u4e2d\u63d0\u53d6\u7684\u6587\u672c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\uff1a<\/p>\n<\/p>\n
                  import pandas as pd<\/p>\n
                  def extract_table_from_text(text):<\/p>\n
                      # \u5047\u8bbe\u8868\u683c\u6570\u636e\u6bcf\u884c\u7528\u6362\u884c\u7b26\u5206\u9694\uff0c\u6bcf\u5217\u7528\u7a7a\u683c\u5206\u9694<\/p>\n
                      rows = text.split('\\n')<\/p>\n
                      table_data = [row.split() for row in rows]<\/p>\n
                      # \u521b\u5efa DataFrame<\/p>\n
                      df = pd.DataFrame(table_data)<\/p>\n
                      return df<\/p>\n
                  def save_to_excel(df, excel_path):<\/p>\n
                      # \u4fdd\u5b58\u4e3a Excel \u6587\u4ef6<\/p>\n
                      df.to_excel(excel_path, index=False)<\/p>\n
                  \u793a\u4f8b\u4f7f\u7528<\/strong><\/h2>\n
                  text = """<\/p>\n
                  Name Age Gender<\/p>\n
                  Alice 30 Female<\/p>\n
                  Bob 25 Male<\/p>\n
                  Carol 22 Female<\/p>\n
                  """<\/p>\n
                  excel_path = "output.xlsx"<\/p>\n
                  df = extract_table_from_text(text)<\/p>\n
                  save_to_excel(df, excel_path)<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u901a\u8fc7\u8fd9\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 pandas \u5904\u7406\u4ece PDF \u4e2d\u63d0\u53d6\u7684\u7b80\u5355\u8868\u683c\u6570\u636e\u5e76\u4fdd\u5b58\u4e3a Excel \u6587\u4ef6\u3002\u5bf9\u4e8e\u590d\u6742\u7684\u8868\u683c\u6570\u636e\uff0c\u53ef\u80fd\u9700\u8981\u66f4\u591a\u7684\u5904\u7406\u6b65\u9aa4\u3002<\/p>\n<\/p>\n
                  \u4e94\u3001\u603b\u7ed3<\/p>\n<\/p>\n
                  \u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u4ecb\u7ecd\u4e86\u51e0\u79cd\u5e38\u89c1\u7684 Python \u5e93\u548c\u65b9\u6cd5\uff0c\u7528\u4e8e\u5c06 PDF \u8f6c\u5316\u4e3a Excel \u6587\u4ef6\u3002\u5177\u4f53\u5305\u62ec PyMuPDF\u3001pdfplumber\u3001tabula-py \u548c pandas \u7b49\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u9002\u7528\u7684\u573a\u666f\u548c\u4f18\u52bf\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53ef\u4ee5\u6709\u6548\u5730\u5b8c\u6210 PDF \u5230 Excel \u7684\u8f6c\u6362\u4efb\u52a1\u3002<\/p>\n<\/p>\n
                  PyMuPDF<\/strong> \u63d0\u4f9b\u4e86\u5f3a\u5927\u7684 PDF \u64cd\u4f5c\u529f\u80fd\uff0c\u9002\u7528\u4e8e\u5904\u7406\u6587\u672c\u548c\u56fe\u50cf\u63d0\u53d6\uff1bpdfplumber<\/strong> \u64c5\u957f\u5904\u7406\u590d\u6742\u7684\u8868\u683c\u6570\u636e\uff1btabula-py<\/strong> \u57fa\u4e8e Java \u7684 Tabula \u9879\u76ee\uff0c\u5177\u6709\u5f3a\u5927\u7684\u8868\u683c\u89e3\u6790\u80fd\u529b\uff1bpandas<\/strong> \u53ef\u4ee5\u7ed3\u5408\u5176\u4ed6\u5e93\u5904\u7406\u7b80\u5355\u7684\u8868\u683c\u6570\u636e\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u548c\u65b9\u6cd5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8f6c\u6362\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
                  \u5e0c\u671b\u672c\u6587\u5bf9\u60a8\u4e86\u89e3\u548c\u5b9e\u73b0 Python \u5c06 PDF \u8f6c\u5316\u4e3a Excel \u6587\u4ef6\u6709\u6240\u5e2e\u52a9\u3002\u5982\u679c\u60a8\u6709\u4efb\u4f55\u7591\u95ee\u6216\u9700\u8981\u8fdb\u4e00\u6b65\u7684\u5e2e\u52a9\uff0c\u8bf7\u968f\u65f6\u8054\u7cfb\u6211\u3002<\/p>\n<\/p>\n
                  \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                   \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u5c06PDF\u8f6c\u5316\u4e3aExcel\u6587\u4ef6\uff1f<\/strong>
                  \u5728\u5e02\u573a\u4e0a\uff0c\u6709\u8bb8\u591a\u5de5\u5177\u53ef\u4ee5\u5b9e\u73b0PDF\u5230Excel\u7684\u8f6c\u6362\uff0c\u5305\u62ec\u5728\u7ebf\u670d\u52a1\u548c\u684c\u9762\u8f6f\u4ef6\u3002\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u65f6\uff0c\u8003\u8651\u56e0\u7d20\u5305\u62ec\u6587\u4ef6\u7684\u590d\u6742\u7a0b\u5ea6\u3001\u8f6c\u6362\u7684\u51c6\u786e\u6027\u3001\u662f\u5426\u9700\u8981\u6279\u91cf\u5904\u7406\u3001\u4ee5\u53ca\u662f\u5426\u9700\u8981\u4fdd\u7559\u539f\u6709\u683c\u5f0f\u3002\u5728\u9009\u62e9\u65f6\uff0c\u53ef\u4ee5\u5148\u67e5\u770b\u7528\u6237\u8bc4\u4ef7\u548c\u8bd5\u7528\u7248\u672c\uff0c\u4ee5\u786e\u4fdd\u6ee1\u8db3\u4f60\u7684\u9700\u6c42\u3002<\/p>\n
                  \u8f6c\u6362\u540e\u7684Excel\u6587\u4ef6\u51c6\u786e\u6027\u5982\u4f55\u4fdd\u8bc1\uff1f<\/strong>
                  \u867d\u7136\u8bb8\u591a\u5de5\u5177\u58f0\u79f0\u53ef\u4ee5\u9ad8\u6548\u5730\u8fdb\u884cPDF\u5230Excel\u7684\u8f6c\u6362\uff0c\u4f46\u8f6c\u6362\u540e\u7684\u7ed3\u679c\u53ef\u80fd\u4f1a\u56e0PDF\u6587\u4ef6\u7684\u683c\u5f0f\u548c\u5185\u5bb9\u590d\u6742\u6027\u800c\u6709\u6240\u4e0d\u540c\u3002\u4e3a\u786e\u4fdd\u51c6\u786e\u6027\uff0c\u5efa\u8bae\u5728\u8f6c\u6362\u540e\u4ed4\u7ec6\u68c0\u67e5Excel\u6587\u4ef6\u4e2d\u7684\u6570\u636e\uff0c\u5c24\u5176\u662f\u8868\u683c\u548c\u6570\u503c\u7684\u51c6\u786e\u6027\u3002\u5fc5\u8981\u65f6\uff0c\u53ef\u4ee5\u624b\u52a8\u8c03\u6574\uff0c\u4ee5\u786e\u4fdd\u4fe1\u606f\u7684\u5b8c\u6574\u6027\u3002<\/p>\n
                  \u662f\u5426\u6709\u514d\u8d39\u7684\u65b9\u6cd5\u5c06PDF\u6587\u4ef6\u8f6c\u6362\u4e3aExcel\uff1f<\/strong>
                  \u662f\u7684\uff0c\u5e02\u9762\u4e0a\u6709\u4e00\u4e9b\u514d\u8d39\u7684\u5728\u7ebf\u5de5\u5177\u53ef\u4ee5\u5b9e\u73b0PDF\u5230Excel\u7684\u8f6c\u6362\uff0c\u5982Smallpdf\u3001ILovePDF\u7b49\u3002\u8fd9\u4e9b\u5de5\u5177\u901a\u5e38\u63d0\u4f9b\u57fa\u7840\u7684\u8f6c\u6362\u529f\u80fd\uff0c\u4f46\u53ef\u80fd\u4f1a\u6709\u6587\u4ef6\u5927\u5c0f\u9650\u5236\u6216\u4e0d\u652f\u6301\u6279\u91cf\u8f6c\u6362\u3002\u5bf9\u4e8e\u7ecf\u5e38\u9700\u8981\u8fdb\u884c\u6b64\u7c7b\u8f6c\u6362\u7684\u7528\u6237\uff0c\u8003\u8651\u4f7f\u7528\u4e13\u4e1a\u8f6f\u4ef6\u6216\u670d\u52a1\u53ef\u80fd\u66f4\u4e3a\u9ad8\u6548\u548c\u53ef\u9760\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python \u5c06 PDF \u8f6c\u5316\u4e3a Excel \u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u5e93\u5982 PyMuPDF\u3001pdfplumber\u3001ta […]","protected":false},"author":3,"featured_media":1077843,"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\/1077838"}],"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=1077838"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1077838\/revisions"}],"predecessor-version":[{"id":1077845,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1077838\/revisions\/1077845"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1077843"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1077838"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1077838"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1077838"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}