{"id":921074,"date":"2024-12-26T14:07:27","date_gmt":"2024-12-26T06:07:27","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/921074.html"},"modified":"2024-12-26T14:07:29","modified_gmt":"2024-12-26T06:07:29","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96excel%e6%96%87%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/921074.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u53d6excel\u6587\u4ef6"},"content":{"rendered":"

\"python\u5982\u4f55\u8bfb\u53d6excel\u6587\u4ef6\"<\/p>\n

\u5f00\u5934\u6bb5\u843d:
Python\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u65b9\u5f0f\u4e3b\u8981\u6709\u4e09\u79cd\uff1a\u4f7f\u7528pandas\u5e93\u3001\u4f7f\u7528openpyxl\u5e93\u3001\u4f7f\u7528xlrd\u5e93<\/strong>\u3002\u5176\u4e2d\uff0cpandas\u5e93<\/strong> \u662f\u6700\u4e3a\u5e38\u7528\u548c\u4fbf\u6377\u7684\u65b9\u5f0f\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u80fd\u591f\u9ad8\u6548\u5730\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u8fd8\u80fd\u5bf9\u6570\u636e\u8fdb\u884c\u5404\u79cd\u5904\u7406\u548c\u5206\u6790\u3002Pandas\u5e93\u63d0\u4f9b\u4e86\u4e00\u4e2a\u51fd\u6570read_excel()<\/code>\uff0c\u8fd9\u4e2a\u51fd\u6570\u975e\u5e38\u5f3a\u5927\uff0c\u53ef\u4ee5\u8bfb\u53d6Excel\u6587\u4ef6\u4e2d\u7684\u7279\u5b9a\u5de5\u4f5c\u8868\u3001\u6307\u5b9a\u6570\u636e\u8303\u56f4\u7b49\u3002\u901a\u8fc7\u5229\u7528pandas\u5e93\uff0c\u7528\u6237\u53ef\u4ee5\u5feb\u901f\u8bfb\u53d6Excel\u6587\u4ef6\u5e76\u8fdb\u884c\u6570\u636e\u5904\u7406\uff0c\u4ece\u800c\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n<\/p>\n

\u4e00\u3001PANDAS\u5e93\u8bfb\u53d6EXCEL\u6587\u4ef6<\/p>\n<\/p>\n

Pandas\u662f\u4e00\u4e2a\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u5f3a\u5927\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u3002\u4f7f\u7528Pandas\u5e93\u8bfb\u53d6Excel\u6587\u4ef6\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u51e0\u884c\u4ee3\u7801\u5373\u53ef\u5b9e\u73b0\u3002<\/p>\n<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5pandas\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528read_excel()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6Excel\u6587\u4ef6\u3002\u5982\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_excel('file.xlsx')<\/p>\n
\u8f93\u51fa\u6570\u636e<\/strong><\/h2>\n
print(df.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0cread_excel()<\/code>\u51fd\u6570\u53ef\u4ee5\u63a5\u53d7\u591a\u4e2a\u53c2\u6570\uff0c\u5982\u6587\u4ef6\u540d\u3001\u5de5\u4f5c\u8868\u540d\u79f0\u3001\u5217\u540d\u3001\u6570\u636e\u7c7b\u578b\u7b49\u3002\u901a\u8fc7\u8fd9\u4e9b\u53c2\u6570\uff0c\u53ef\u4ee5\u5bf9\u8bfb\u53d6\u7684\u6570\u636e\u8fdb\u884c\u66f4\u4e3a\u7cbe\u7ec6\u7684\u63a7\u5236\u3002<\/p>\n<\/p>\n
\u4e8c\u3001OPENPYXL\u5e93\u8bfb\u53d6EXCEL\u6587\u4ef6<\/p>\n<\/p>\n
Openpyxl\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6\u548c\u5199\u5165Excel 2010 xlsx\/xlsm\/xltx\/xltm\u6587\u4ef6\u7684\u5e93\u3002\u4e0ePandas\u76f8\u6bd4\uff0cOpenpyxl\u66f4\u9002\u5408\u7528\u4e8e\u5904\u7406Excel\u6587\u4ef6\u7684\u683c\u5f0f\u5316\u548c\u6837\u5f0f\u3002<\/p>\n<\/p>\n
\u5b89\u88c5openpyxl\u5e93\uff1a<\/p>\n<\/p>\n
pip install openpyxl<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528openpyxl\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u57fa\u672c\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
\u52a0\u8f7dExcel\u6587\u4ef6<\/strong><\/h2>\n
wb = load_workbook('file.xlsx')<\/p>\n
\u83b7\u53d6\u5de5\u4f5c\u8868<\/strong><\/h2>\n
sheet = wb.active<\/p>\n
\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
for row in sheet.iter_rows(values_only=True):<\/p>\n
    print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u901a\u8fc7load_workbook()<\/code>\u51fd\u6570\u52a0\u8f7dExcel\u6587\u4ef6\uff0c\u7136\u540e\u901a\u8fc7wb.active<\/code>\u83b7\u53d6\u6d3b\u52a8\u7684\u5de5\u4f5c\u8868\uff0c\u6700\u540e\u901a\u8fc7\u8fed\u4ee3\u5de5\u4f5c\u8868\u7684\u884c\u6765\u8bfb\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n
\u4e09\u3001XLRT\u5e93\u8bfb\u53d6EXCEL\u6587\u4ef6<\/p>\n<\/p>\n
Xlrd\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u5e93\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u5904\u7406\u8001\u7248\u672c\u7684xls\u6587\u4ef6\u3002\u7136\u800c\uff0c\u7531\u4e8e\u5176\u4e0d\u652f\u6301xlsx\u683c\u5f0f\u7684\u65b0Excel\u6587\u4ef6\uff0c\u4f7f\u7528\u8303\u56f4\u53d7\u9650\u3002<\/p>\n<\/p>\n
\u5b89\u88c5xlrd\u5e93\uff1a<\/p>\n<\/p>\n
pip install xlrd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528xlrd\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u57fa\u672c\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import xlrd<\/p>\n
\u6253\u5f00Excel\u6587\u4ef6<\/strong><\/h2>\n
workbook = xlrd.open_workbook('file.xls')<\/p>\n
\u83b7\u53d6\u5de5\u4f5c\u8868<\/strong><\/h2>\n
sheet = workbook.sheet_by_index(0)<\/p>\n
\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n
for row_idx in range(sheet.nrows):<\/p>\n
    print(sheet.row(row_idx))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0copen_workbook()<\/code>\u51fd\u6570\u7528\u4e8e\u6253\u5f00Excel\u6587\u4ef6\uff0csheet_by_index()<\/code>\u51fd\u6570\u7528\u4e8e\u83b7\u53d6\u5de5\u4f5c\u8868\u3002\u7136\u540e\uff0c\u901a\u8fc7\u8fed\u4ee3\u5de5\u4f5c\u8868\u7684\u884c\uff0c\u8bfb\u53d6\u6bcf\u4e00\u884c\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
\u56db\u3001PANDAS\u5e93\u4e2d\u5e38\u7528\u7684\u53c2\u6570<\/p>\n<\/p>\n
\u5728\u4f7f\u7528Pandas\u5e93\u7684read_excel()<\/code>\u51fd\u6570\u65f6\uff0c\u6709\u4e00\u4e9b\u5e38\u7528\u7684\u53c2\u6570\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u7075\u6d3b\u5730\u8bfb\u53d6Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    \n
  1. \n
    sheet_name<\/code>: \u6307\u5b9a\u8981\u8bfb\u53d6\u7684\u5de5\u4f5c\u8868\u540d\u79f0\u6216\u7d22\u5f15\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u8bfb\u53d6\u7b2c\u4e00\u4e2a\u5de5\u4f5c\u8868\u3002<\/p>\n<\/p>\n<\/li>\n
  2. \n
    header<\/code>: \u6307\u5b9a\u5217\u540d\u6240\u5728\u7684\u884c\u7d22\u5f15\u3002\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u7b2c\u4e00\u884c\u4f5c\u4e3a\u5217\u540d\u3002<\/p>\n<\/p>\n<\/li>\n
  3. \n
    usecols<\/code>: \u6307\u5b9a\u8981\u8bfb\u53d6\u7684\u5217\u3002\u53ef\u4ee5\u662f\u5217\u540d\u3001\u5217\u7d22\u5f15\u6216\u4e8c\u8005\u7684\u7ec4\u5408\u3002<\/p>\n<\/p>\n<\/li>\n
  4. \n
    dtype<\/code>: \u6307\u5b9a\u5217\u7684\u6570\u636e\u7c7b\u578b\u3002\u53ef\u4ee5\u901a\u8fc7\u5b57\u5178\u5f62\u5f0f\u4e3a\u4e0d\u540c\u5217\u8bbe\u7f6e\u4e0d\u540c\u7684\u6570\u636e\u7c7b\u578b\u3002<\/p>\n<\/p>\n<\/li>\n
  5. \n
    skiprows<\/code>: \u6307\u5b9a\u8df3\u8fc7\u7684\u884c\u6570\uff0c\u9002\u7528\u4e8e\u6587\u4ef6\u5934\u90e8\u6709\u591a\u884c\u8bf4\u660e\u4fe1\u606f\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n
    \u5229\u7528\u8fd9\u4e9b\u53c2\u6570\uff0c\u53ef\u4ee5\u5b9e\u73b0\u5bf9Excel\u6587\u4ef6\u7684\u7cbe\u786e\u8bfb\u53d6\uff0c\u6ee1\u8db3\u591a\u6837\u5316\u7684\u6570\u636e\u5206\u6790\u9700\u6c42\u3002<\/p>\n<\/p>\n
    \u4e94\u3001OPENPYXL\u5e93\u4e2d\u7684\u5de5\u4f5c\u8868\u64cd\u4f5c<\/p>\n<\/p>\n
    Openpyxl\u5e93\u4e0d\u4ec5\u53ef\u4ee5\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u8fd8\u53ef\u4ee5\u8fdb\u884c\u66f4\u590d\u6742\u7684\u5de5\u4f5c\u8868\u64cd\u4f5c\uff0c\u5982\u521b\u5efa\u3001\u5220\u9664\u548c\u91cd\u547d\u540d\u5de5\u4f5c\u8868\uff0c\u6dfb\u52a0\u548c\u5220\u9664\u884c\u5217\u7b49\u3002<\/p>\n<\/p>\n
      \n
    1. \u521b\u5efa\u5de5\u4f5c\u8868\uff1a<\/li>\n<\/ol>\n
      # \u521b\u5efa\u65b0\u5de5\u4f5c\u8868<\/p>\n
      new_sheet = wb.create_sheet(title='NewSheet')<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u5220\u9664\u5de5\u4f5c\u8868\uff1a<\/li>\n<\/ol>\n
        # \u5220\u9664\u5de5\u4f5c\u8868<\/p>\n
        wb.remove(wb['SheetName'])<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u91cd\u547d\u540d\u5de5\u4f5c\u8868\uff1a<\/li>\n<\/ol>\n
          # \u91cd\u547d\u540d\u5de5\u4f5c\u8868<\/p>\n
          sheet.title = 'RenamedSheet'<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          1. \u6dfb\u52a0\u548c\u5220\u9664\u884c\u5217\uff1a<\/li>\n<\/ol>\n
            # \u63d2\u5165\u4e00\u884c<\/p>\n
            sheet.insert_rows(idx=1)<\/p>\n
            \u5220\u9664\u4e00\u5217<\/strong><\/h2>\n
            sheet.delete_cols(idx=2)<\/p>\n
            <\/code><\/pre>\n<\/p>\n
            \u901a\u8fc7\u8fd9\u4e9b\u64cd\u4f5c\uff0c\u7528\u6237\u53ef\u4ee5\u5728\u4e0d\u79bb\u5f00Python\u73af\u5883\u7684\u60c5\u51b5\u4e0b\uff0c\u5bf9Excel\u6587\u4ef6\u8fdb\u884c\u5168\u9762\u7684\u7ba1\u7406\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
            \u516d\u3001\u6570\u636e\u5904\u7406\u548c\u5206\u6790<\/p>\n<\/p>\n
            \u8bfb\u53d6Excel\u6587\u4ef6\u540e\uff0c\u5e38\u5e38\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5904\u7406\u548c\u5206\u6790\u3002Pandas\u5e93\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5de5\u5177\u3002<\/p>\n<\/p>\n
              \n
            1. \u6570\u636e\u6e05\u6d17\uff1a\u5305\u62ec\u53bb\u9664\u7f3a\u5931\u503c\u3001\u91cd\u590d\u503c\u3001\u6570\u636e\u683c\u5f0f\u8f6c\u6362\u7b49\u64cd\u4f5c\u3002<\/li>\n<\/ol>\n
              # \u53bb\u9664\u7f3a\u5931\u503c<\/p>\n
              df.dropna(inplace=True)<\/p>\n
              \u53bb\u9664\u91cd\u590d\u503c<\/strong><\/h2>\n
              df.drop_duplicates(inplace=True)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
                \n
              1. \u6570\u636e\u5206\u6790\uff1a\u5305\u62ec\u5206\u7ec4\u3001\u805a\u5408\u3001\u7edf\u8ba1\u5206\u6790\u7b49\u64cd\u4f5c\u3002<\/li>\n<\/ol>\n
                # \u5206\u7ec4\u5e76\u6c42\u548c<\/p>\n
                grouped = df.groupby('column_name').sum()<\/p>\n
                \u7edf\u8ba1\u63cf\u8ff0<\/strong><\/h2>\n
                stats = df.describe()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                1. \u6570\u636e\u53ef\u89c6\u5316\uff1aPandas\u4e0eMatplotlib\u7ed3\u5408\u53ef\u4ee5\u5b9e\u73b0\u6570\u636e\u7684\u53ef\u89c6\u5316\u3002<\/li>\n<\/ol>\n
                  import matplotlib.pyplot as plt<\/p>\n
                  \u7ed8\u5236\u67f1\u72b6\u56fe<\/strong><\/h2>\n
                  df['column_name'].plot(kind='bar')<\/p>\n
                  plt.show()<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u901a\u8fc7\u8fd9\u4e9b\u5904\u7406\u548c\u5206\u6790\uff0c\u7528\u6237\u53ef\u4ee5\u4eceExcel\u6587\u4ef6\u4e2d\u63d0\u53d6\u51fa\u6709\u4ef7\u503c\u7684\u4fe1\u606f\u3002<\/p>\n<\/p>\n
                  \u4e03\u3001\u7efc\u5408\u5e94\u7528\u5b9e\u4f8b<\/p>\n<\/p>\n
                  \u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6\u548c\u5904\u7406Excel\u6587\u4ef6\uff0c\u8fd9\u91cc\u63d0\u4f9b\u4e00\u4e2a\u7efc\u5408\u5e94\u7528\u5b9e\u4f8b\u3002<\/p>\n<\/p>\n
                  \u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2aExcel\u6587\u4ef6\uff0c\u8bb0\u5f55\u4e86\u67d0\u516c\u53f8\u4e0d\u540c\u90e8\u95e8\u7684\u5458\u5de5\u4fe1\u606f\uff0c\u5305\u62ec\u59d3\u540d\u3001\u5e74\u9f84\u3001\u90e8\u95e8\u548c\u85aa\u6c34\u7b49\u3002\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u8fd9\u4e2a\u6587\u4ef6\uff0c\u5e76\u8ba1\u7b97\u6bcf\u4e2a\u90e8\u95e8\u7684\u5e73\u5747\u85aa\u6c34\u3002<\/p>\n<\/p>\n
                  import pandas as pd<\/p>\n
                  \u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
                  df = pd.read_excel('employees.xlsx')<\/p>\n
                  \u6570\u636e\u6e05\u6d17<\/strong><\/h2>\n
                  df.dropna(inplace=True)<\/p>\n
                  df.drop_duplicates(inplace=True)<\/p>\n
                  \u8ba1\u7b97\u6bcf\u4e2a\u90e8\u95e8\u7684\u5e73\u5747\u85aa\u6c34<\/strong><\/h2>\n
                  average_salary = df.groupby('Department')['Salary'].mean()<\/p>\n
                  \u8f93\u51fa\u7ed3\u679c<\/strong><\/h2>\n
                  print(average_salary)<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u901a\u8fc7\u8fd9\u4e2a\u5b9e\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u5feb\u901f\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u8fdb\u884c\u6570\u636e\u6e05\u6d17\uff0c\u5e76\u8fdb\u884c\u7b80\u5355\u7684\u6570\u636e\u5206\u6790\u3002<\/p>\n<\/p>\n
                  \u603b\u7ed3\uff1a<\/p>\n<\/p>\n
                  Python\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002\u5bf9\u4e8e\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u4efb\u52a1\uff0cPandas\u662f\u9996\u9009\u5de5\u5177\uff1b\u800c\u5bf9\u4e8e\u6d89\u53caExcel\u683c\u5f0f\u548c\u6837\u5f0f\u7684\u590d\u6742\u64cd\u4f5c\uff0cOpenpyxl\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002\u901a\u8fc7\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u5de5\u5177\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u5bf9Excel\u6587\u4ef6\u7684\u8bfb\u53d6\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
                  \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                   \u5728Python\u4e2d\u8bfb\u53d6Excel\u6587\u4ef6\u9700\u8981\u54ea\u4e9b\u5e93\uff1f<\/strong>
                  \u4e3a\u4e86\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u901a\u5e38\u4f7f\u7528pandas<\/code>\u5e93\u548copenpyxl<\/code>\u5e93\u3002pandas<\/code>\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\uff0c\u800copenpyxl<\/code>\u5141\u8bb8\u60a8\u8bfb\u53d6\u548c\u5199\u5165Excel 2010 xlsx\/xlsm\/xltx\/xltm\u6587\u4ef6\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7pip install pandas openpyxl<\/code>\u547d\u4ee4\u5b89\u88c5\u8fd9\u4e24\u4e2a\u5e93\u3002<\/p>\n
                  \u5982\u4f55\u4f7f\u7528Pandas\u8bfb\u53d6Excel\u6587\u4ef6\uff1f<\/strong>
                  \u4f7f\u7528pandas<\/code>\u8bfb\u53d6Excel\u6587\u4ef6\u975e\u5e38\u7b80\u5355\u3002\u60a8\u53ea\u9700\u8c03\u7528pandas.read_excel()<\/code>\u65b9\u6cd5\uff0c\u5e76\u4f20\u5165\u6587\u4ef6\u8def\u5f84\u3002\u4f8b\u5982\uff0cimport pandas as pd<\/code>\uff0c\u7136\u540e\u4f7f\u7528df = pd.read_excel('file.xlsx')<\/code>\u6765\u8bfb\u53d6\u6587\u4ef6\u3002\u53ef\u4ee5\u901a\u8fc7sheet_name<\/code>\u53c2\u6570\u6307\u5b9a\u8bfb\u53d6\u7684\u5de5\u4f5c\u8868\uff0c\u5982\u679c\u6587\u4ef6\u4e2d\u6709\u591a\u4e2a\u5de5\u4f5c\u8868\uff0c\u53ef\u4ee5\u901a\u8fc7\u540d\u79f0\u6216\u7d22\u5f15\u6765\u9009\u62e9\u3002<\/p>\n
                  \u8bfb\u53d6Excel\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\uff1f<\/strong>
                  \u5728\u8bfb\u53d6Excel\u6587\u4ef6\u540e\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7DataFrame<\/code>\u7684isnull()<\/code>\u65b9\u6cd5\u6765\u68c0\u67e5\u7f3a\u5931\u503c\u3002\u5904\u7406\u7f3a\u5931\u503c\u7684\u5e38\u7528\u65b9\u6cd5\u5305\u62ec\u586b\u5145\u7f3a\u5931\u503c\uff08\u4f7f\u7528fillna()<\/code>\u65b9\u6cd5\uff09\u6216\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff08\u4f7f\u7528dropna()<\/code>\u65b9\u6cd5\uff09\u3002\u4f8b\u5982\uff0cdf.fillna(0)<\/code>\u53ef\u4ee5\u5c06\u6240\u6709\u7f3a\u5931\u503c\u66ff\u6362\u4e3a0\uff0cdf.dropna()<\/code>\u5c06\u5220\u9664\u6240\u6709\u542b\u7f3a\u5931\u503c\u7684\u884c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d:Python\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u65b9\u5f0f\u4e3b\u8981\u6709\u4e09\u79cd\uff1a\u4f7f\u7528pandas\u5e93\u3001\u4f7f\u7528openpyxl\u5e93\u3001\u4f7f\u7528xl […]","protected":false},"author":3,"featured_media":921077,"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\/921074"}],"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=921074"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/921074\/revisions"}],"predecessor-version":[{"id":921078,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/921074\/revisions\/921078"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/921077"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=921074"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=921074"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=921074"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}