{"id":1177751,"date":"2025-01-15T18:01:50","date_gmt":"2025-01-15T10:01:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1177751.html"},"modified":"2025-01-15T18:01:53","modified_gmt":"2025-01-15T10:01:53","slug":"python%e5%a6%82%e4%bd%95%e7%bb%99excel%e5%8a%a0%e5%88%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1177751.html","title":{"rendered":"python\u5982\u4f55\u7ed9excel\u52a0\u5217"},"content":{"rendered":"

\"python\u5982\u4f55\u7ed9excel\u52a0\u5217\"<\/p>\n

\u4f7f\u7528Python\u7ed9Excel\u6587\u4ef6\u6dfb\u52a0\u5217\uff0c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b8c\u6210\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u5c31\u662f\u4f7f\u7528Pandas\u5e93\u3002<\/strong>\u3001\u901a\u8fc7\u8bfb\u53d6Excel\u6587\u4ef6<\/strong>\u3001\u589e\u52a0\u65b0\u5217<\/strong>\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u6587\u4ef6<\/strong>\u3002\u5728\u672c\u7bc7\u6587\u7ae0\u4e2d\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5b9e\u73b0\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u5e76\u8ba8\u8bba\u4e00\u4e9b\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\u548c\u6280\u5de7\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5Pandas\u5e93\u5e76\u5bfc\u5165\u6240\u9700\u6a21\u5757<\/h3>\n<\/p>\n

\u5728\u5f00\u59cb\u64cd\u4f5c\u4e4b\u524d\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86Pandas\u5e93\u548cOpenpyxl\u5e93\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install pandas openpyxl<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5bfc\u5165\u6240\u9700\u7684\u6a21\u5757\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6Excel\u6587\u4ef6\u3002Pandas\u63d0\u4f9b\u4e86read_excel<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06Excel\u6587\u4ef6\u8bfb\u53d6\u4e3aDataFrame\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
df = pd.read_excel('example.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6837\u6211\u4eec\u5c31\u5c06Excel\u6587\u4ef6\u8bfb\u53d6\u4e3a\u4e00\u4e2aDataFrame\u5bf9\u8c61\uff0c\u63a5\u4e0b\u6765\u53ef\u4ee5\u5bf9\u5176\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u6dfb\u52a0\u65b0\u5217<\/h3>\n<\/p>\n
\u589e\u52a0\u65b0\u5217\u975e\u5e38\u7b80\u5355<\/strong>\uff0c\u53ea\u9700\u8981\u4e3aDataFrame\u5bf9\u8c61\u6dfb\u52a0\u4e00\u4e2a\u65b0\u7684\u5217\u540d\uff0c\u5e76\u4e3a\u5176\u5206\u914d\u76f8\u5e94\u7684\u503c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
df['\u65b0\u5217\u540d'] = [\u503c1, \u503c2, \u503c3, ...]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u4f60\u5df2\u7ecf\u6709\u4e86\u4e00\u7ec4\u6570\u636e\uff0c\u5e76\u4e14\u60f3\u8981\u5c06\u5176\u6dfb\u52a0\u5230Excel\u6587\u4ef6\u4e2d\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u793a\u4f8b\u4ee3\u7801<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u5b66\u751f\u6210\u7ee9\u7684Excel\u6587\u4ef6\uff0c\u6211\u4eec\u60f3\u8981\u6dfb\u52a0\u4e00\u5217\u8868\u793a\u5b66\u751f\u7684\u603b\u6210\u7ee9\u3002\u6211\u4eec\u53ef\u4ee5\u8fd9\u6837\u505a\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_excel('students_scores.xlsx')<\/p>\n
\u8ba1\u7b97\u603b\u6210\u7ee9\u5e76\u6dfb\u52a0\u65b0\u5217<\/strong><\/h2>\n
df['\u603b\u6210\u7ee9'] = df['\u6570\u5b66'] + df['\u82f1\u8bed'] + df['\u79d1\u5b66']<\/p>\n
\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u6587\u4ef6<\/strong><\/h2>\n
df.to_excel('students_scores_with_total.xlsx', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u6587\u4ef6<\/h3>\n<\/p>\n
\u5b8c\u6210\u4fee\u6539\u540e\uff0c\u9700\u8981\u5c06DataFrame\u4fdd\u5b58\u56deExcel\u6587\u4ef6\u3002Pandas\u63d0\u4f9b\u4e86to_excel<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5c06DataFrame\u4fdd\u5b58\u4e3aExcel\u6587\u4ef6\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
df.to_excel('modified_example.xlsx', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u5e38\u89c1\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n
1\u3001\u6279\u91cf\u6dfb\u52a0\u8ba1\u7b97\u5217<\/h4>\n<\/p>\n
\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u7ecf\u5e38\u9700\u8981\u6839\u636e\u73b0\u6709\u7684\u5217\u8ba1\u7b97\u51fa\u65b0\u7684\u5217\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u5229\u6da6\u7387\u3001\u589e\u957f\u7387\u7b49\u3002<\/p>\n<\/p>\n
df['\u5229\u6da6\u7387'] = df['\u5229\u6da6'] \/ df['\u6536\u5165'] * 100<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6839\u636e\u6761\u4ef6\u6dfb\u52a0\u65b0\u5217<\/h4>\n<\/p>\n
\u6709\u65f6\u5019\u9700\u8981\u6839\u636e\u67d0\u4e9b\u6761\u4ef6\u6765\u6dfb\u52a0\u65b0\u7684\u5217\u3002\u4f8b\u5982\uff0c\u6839\u636e\u6210\u7ee9\u6765\u5224\u65ad\u5b66\u751f\u662f\u5426\u53ca\u683c\uff1a<\/p>\n<\/p>\n
df['\u662f\u5426\u53ca\u683c'] = df['\u603b\u6210\u7ee9'].apply(lambda x: '\u53ca\u683c' if x >= 60 else '\u4e0d\u53ca\u683c')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u6dfb\u52a0\u65e5\u671f\u5217<\/h4>\n<\/p>\n
\u5728\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u65f6\uff0c\u7ecf\u5e38\u9700\u8981\u6dfb\u52a0\u65e5\u671f\u5217\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import datetime<\/p>\n
df['\u65e5\u671f'] = pd.date_range(start='2023-01-01', periods=len(df), freq='D')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u8fdb\u9636\u6280\u5de7<\/h3>\n<\/p>\n
1\u3001\u4f7f\u7528apply\u51fd\u6570\u8fdb\u884c\u590d\u6742\u64cd\u4f5c<\/h4>\n<\/p>\n
apply<\/code>\u51fd\u6570\u5141\u8bb8\u4f60\u5bf9DataFrame\u4e2d\u7684\u6bcf\u4e00\u884c\u6216\u6bcf\u4e00\u5217\u8fdb\u884c\u590d\u6742\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u6bcf\u4e2a\u5b66\u751f\u7684\u52a0\u6743\u603b\u6210\u7ee9\uff1a<\/p>\n<\/p>\n
def \u8ba1\u7b97\u52a0\u6743\u603b\u6210\u7ee9(row):<\/p>\n
    return row['\u6570\u5b66'] * 0.3 + row['\u82f1\u8bed'] * 0.3 + row['\u79d1\u5b66'] * 0.4<\/p>\n
df['\u52a0\u6743\u603b\u6210\u7ee9'] = df.apply(\u8ba1\u7b97\u52a0\u6743\u603b\u6210\u7ee9, axis=1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528lambda\u51fd\u6570\u7b80\u5316\u64cd\u4f5c<\/h4>\n<\/p>\n
\u5728\u5904\u7406\u7b80\u5355\u64cd\u4f5c\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528lambda\u51fd\u6570\u3002\u4f8b\u5982\uff0c\u6839\u636e\u6210\u7ee9\u6dfb\u52a0\u65b0\u7684\u8bc4\u7ea7\u5217\uff1a<\/p>\n<\/p>\n
df['\u8bc4\u7ea7'] = df['\u603b\u6210\u7ee9'].apply(lambda x: '\u4f18\u79c0' if x >= 90 else '\u826f\u597d' if x >= 75 else '\u53ca\u683c' if x >= 60 else '\u4e0d\u53ca\u683c')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n
\u5728\u6dfb\u52a0\u65b0\u5217\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u7f3a\u5931\u503c\u3002\u53ef\u4ee5\u4f7f\u7528Pandas\u63d0\u4f9b\u7684\u586b\u5145\u51fd\u6570\u6765\u5904\u7406\u7f3a\u5931\u503c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
df['\u603b\u6210\u7ee9'].fillna(0, inplace=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u5b8c\u6574\u4ee3\u7801\u793a\u4f8b<\/h3>\n<\/p>\n
\u7ed3\u5408\u4e0a\u8ff0\u5404\u4e2a\u6b65\u9aa4\u548c\u6280\u5de7\uff0c\u6211\u4eec\u53ef\u4ee5\u7f16\u5199\u4e00\u4e2a\u5b8c\u6574\u7684\u4ee3\u7801\u793a\u4f8b\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u5b66\u751f\u6210\u7ee9\u7684Excel\u6587\u4ef6\uff0c\u6211\u4eec\u60f3\u8981\u6dfb\u52a0\u603b\u6210\u7ee9\u3001\u52a0\u6743\u603b\u6210\u7ee9\u3001\u8bc4\u7ea7\u7b49\u5217\u3002\u5b8c\u6574\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_excel('students_scores.xlsx')<\/p>\n
\u8ba1\u7b97\u603b\u6210\u7ee9\u5e76\u6dfb\u52a0\u65b0\u5217<\/strong><\/h2>\n
df['\u603b\u6210\u7ee9'] = df['\u6570\u5b66'] + df['\u82f1\u8bed'] + df['\u79d1\u5b66']<\/p>\n
\u5904\u7406\u7f3a\u5931\u503c<\/strong><\/h2>\n
df['\u603b\u6210\u7ee9'].fillna(0, inplace=True)<\/p>\n
\u8ba1\u7b97\u52a0\u6743\u603b\u6210\u7ee9\u5e76\u6dfb\u52a0\u65b0\u5217<\/strong><\/h2>\n
def \u8ba1\u7b97\u52a0\u6743\u603b\u6210\u7ee9(row):<\/p>\n
    return row['\u6570\u5b66'] * 0.3 + row['\u82f1\u8bed'] * 0.3 + row['\u79d1\u5b66'] * 0.4<\/p>\n
df['\u52a0\u6743\u603b\u6210\u7ee9'] = df.apply(\u8ba1\u7b97\u52a0\u6743\u603b\u6210\u7ee9, axis=1)<\/p>\n
\u6839\u636e\u603b\u6210\u7ee9\u6dfb\u52a0\u8bc4\u7ea7\u5217<\/strong><\/h2>\n
df['\u8bc4\u7ea7'] = df['\u603b\u6210\u7ee9'].apply(lambda x: '\u4f18\u79c0' if x >= 90 else '\u826f\u597d' if x >= 75 else '\u53ca\u683c' if x >= 60 else '\u4e0d\u53ca\u683c')<\/p>\n
\u4fdd\u5b58\u4fee\u6539\u540e\u7684\u6587\u4ef6<\/strong><\/h2>\n
df.to_excel('students_scores_with_additional_columns.xlsx', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u8be6\u7ec6\u8bb2\u89e3\u4e86\u5982\u4f55\u4f7f\u7528Python\u548cPandas\u5e93\u7ed9Excel\u6587\u4ef6\u6dfb\u52a0\u65b0\u5217\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u5217\u6dfb\u52a0<\/strong>\uff0c\u8fd8\u662f\u590d\u6742\u7684\u8ba1\u7b97\u548c\u6761\u4ef6\u5224\u65ad<\/strong>\uff0cPandas\u90fd\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u529f\u80fd\u6765\u6ee1\u8db3\u6211\u4eec\u7684\u9700\u6c42\u3002\u5e0c\u671b\u8fd9\u4e9b\u5185\u5bb9\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u5904\u7406Excel\u6587\u4ef6\uff0c\u63d0\u5347\u6570\u636e\u5206\u6790\u7684\u6548\u7387\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u5e93\u5411Excel\u6587\u4ef6\u6dfb\u52a0\u5217\uff1f<\/strong>
\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u8f7b\u677e\u5730\u5411\u73b0\u6709Excel\u6587\u4ef6\u6dfb\u52a0\u5217\u3002\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5Pandas\u548copenpyxl\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n
pip install pandas openpyxl\n<\/code><\/pre>\n
\u63a5\u4e0b\u6765\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528pd.read_excel()<\/code>\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u5c06\u65b0\u5217\u6dfb\u52a0\u5230DataFrame\u4e2d\uff0c\u7136\u540e\u4f7f\u7528to_excel()<\/code>\u4fdd\u5b58\u66f4\u6539\u3002\u4f8b\u5982\uff1a<\/p>\n
import pandas as pd\n\n# \u8bfb\u53d6Excel\u6587\u4ef6\ndf = pd.read_excel('your_file.xlsx')\n\n# \u6dfb\u52a0\u65b0\u5217\ndf['new_column'] = [value1, value2, value3]  # \u6839\u636e\u9700\u6c42\u8bbe\u7f6e\u65b0\u5217\u7684\u503c\n\n# \u4fdd\u5b58\u66f4\u6539\ndf.to_excel('your_file.xlsx', index=False)\n<\/code><\/pre>\n
\u6b64\u65b9\u6cd5\u7b80\u5355\u6709\u6548\uff0c\u9002\u7528\u4e8e\u5927\u591a\u6570\u6570\u636e\u5904\u7406\u573a\u666f\u3002<\/p>\n
\u4f7f\u7528openpyxl\u5e93\u5728Excel\u6587\u4ef6\u4e2d\u63d2\u5165\u65b0\u5217\u7684\u6b65\u9aa4\u662f\u600e\u6837\u7684\uff1f<\/strong>
openpyxl\u5e93\u63d0\u4f9b\u4e86\u5bf9Excel\u6587\u4ef6\u7684\u66f4\u7cbe\u7ec6\u63a7\u5236\uff0c\u9002\u5408\u9700\u8981\u64cd\u4f5cExcel\u5355\u5143\u683c\u7684\u60c5\u51b5\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u5b9e\u73b0\u5411Excel\u6587\u4ef6\u6dfb\u52a0\u65b0\u5217\uff1a<\/p>\n
    \n
  1. \u5b89\u88c5openpyxl\u5e93\u3002<\/li>\n
  2. \u4f7f\u7528load_workbook()<\/code>\u52a0\u8f7dExcel\u6587\u4ef6\u3002<\/li>\n
  3. \u83b7\u53d6\u6d3b\u52a8\u5de5\u4f5c\u8868\u3002<\/li>\n
  4. \u4f7f\u7528insert_cols()<\/code>\u65b9\u6cd5\u5728\u6307\u5b9a\u4f4d\u7f6e\u63d2\u5165\u65b0\u5217\u3002<\/li>\n
  5. \u4fdd\u5b58\u5de5\u4f5c\u7c3f\u3002<\/li>\n<\/ol>\n
    \u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
    from openpyxl import load_workbook\n\n# \u52a0\u8f7dExcel\u6587\u4ef6\nworkbook = load_workbook('your_file.xlsx')\nsheet = workbook.active\n\n# \u5728\u7b2c2\u5217\u63d2\u5165\u65b0\u5217\nsheet.insert_cols(2)\n\n# \u4e3a\u65b0\u5217\u6dfb\u52a0\u6570\u636e\nfor row in range(1, sheet.max_row + 1):\n    sheet.cell(row=row, column=2).value = 'New Value'\n\n# \u4fdd\u5b58\u66f4\u6539\nworkbook.save('your_file.xlsx')\n<\/code><\/pre>\n
    \u8fd9\u79cd\u65b9\u5f0f\u975e\u5e38\u9002\u5408\u9700\u8981\u5728\u7279\u5b9a\u4f4d\u7f6e\u63d2\u5165\u5217\u7684\u9700\u6c42\u3002<\/p>\n
    \u5728\u6dfb\u52a0\u5217\u65f6\uff0c\u5982\u4f55\u786e\u4fdd\u65b0\u5217\u7684\u6570\u636e\u683c\u5f0f\u4e0e\u5176\u4ed6\u5217\u4e00\u81f4\uff1f<\/strong>
    \u5728\u5411Excel\u6587\u4ef6\u4e2d\u6dfb\u52a0\u65b0\u5217\u65f6\uff0c\u786e\u4fdd\u65b0\u5217\u7684\u6570\u636e\u683c\u5f0f\u4e0e\u5176\u4ed6\u5217\u4e00\u81f4\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u5b9e\u73b0\uff1a<\/p>\n
      \n
    • \u5728\u6dfb\u52a0\u65b0\u5217\u4e4b\u524d\uff0c\u53ef\u4ee5\u68c0\u67e5\u73b0\u6709\u5217\u7684\u6570\u636e\u7c7b\u578b\uff0c\u786e\u4fdd\u65b0\u5217\u7684\u6570\u636e\u7c7b\u578b\u76f8\u5339\u914d\u3002<\/li>\n
    • \u4f7f\u7528Pandas\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7astype()<\/code>\u65b9\u6cd5\u5c06\u65b0\u5217\u7684\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u4e3a\u4e0e\u5176\u4ed6\u5217\u4e00\u81f4\uff0c\u4f8b\u5982\uff1a<\/li>\n<\/ul>\n
      df['new_column'] = df['existing_column'].astype('int')  # \u5c06\u65b0\u5217\u8f6c\u6362\u4e3a\u6574\u6570\u7c7b\u578b\n<\/code><\/pre>\n
        \n
      • \u5728openpyxl\u4e2d\uff0c\u53ef\u4ee5\u624b\u52a8\u8bbe\u7f6e\u5355\u5143\u683c\u7684\u683c\u5f0f\uff0c\u786e\u4fdd\u65b0\u5217\u7684\u683c\u5f0f\u4e0e\u5176\u4ed6\u5217\u4e00\u81f4\u3002\u901a\u8fc7number_format<\/code>\u5c5e\u6027\u53ef\u4ee5\u8bbe\u7f6e\u5355\u5143\u683c\u683c\u5f0f\uff0c\u4f8b\u5982\uff1a<\/li>\n<\/ul>\n
        sheet.cell(row=row, column=2).number_format = '0.00'  # \u8bbe\u7f6e\u4e3a\u4e24\u4f4d\u5c0f\u6570\n<\/code><\/pre>\n
        \u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u4fdd\u6301\u6570\u636e\u7684\u4e00\u81f4\u6027\u548c\u683c\u5f0f\u5316\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4f7f\u7528Python\u7ed9Excel\u6587\u4ef6\u6dfb\u52a0\u5217\uff0c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b8c\u6210\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u5c31\u662f\u4f7f\u7528Pandas\u5e93\u3002\u3001\u901a\u8fc7\u8bfb\u53d6E […]","protected":false},"author":3,"featured_media":1177754,"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\/1177751"}],"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=1177751"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1177751\/revisions"}],"predecessor-version":[{"id":1177755,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1177751\/revisions\/1177755"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1177754"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1177751"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1177751"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1177751"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}