{"id":1143594,"date":"2025-01-08T22:51:48","date_gmt":"2025-01-08T14:51:48","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1143594.html"},"modified":"2025-01-08T22:51:51","modified_gmt":"2025-01-08T14:51:51","slug":"python-%e5%a6%82%e4%bd%95%e5%b0%86%e5%a4%9a%e5%bc%a0%e8%a1%a8%e5%90%88%e5%b9%b6%e4%b8%ba%e4%b8%80%e4%b8%aa%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1143594.html","title":{"rendered":"python \u5982\u4f55\u5c06\u591a\u5f20\u8868\u5408\u5e76\u4e3a\u4e00\u4e2a\u8868"},"content":{"rendered":"

\"python<\/p>\n

\u8981\u5c06\u591a\u5f20\u8868\u5408\u5e76\u4e3a\u4e00\u4e2a\u8868\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u3001\u901a\u8fc7\u5408\u5e76\u51fd\u6570\u3001\u4fdd\u6301\u6570\u636e\u4e00\u81f4\u6027<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u662f\u6700\u5e38\u7528\u548c\u65b9\u4fbf\u7684\u65b9\u6cd5\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u51fd\u6570\u7528\u4e8e\u5408\u5e76\u6570\u636e\u8868\uff0c\u5305\u62ecconcat()<\/code>\u3001merge()<\/code>\u3001join()<\/code>\u7b49\uff0c\u8fd9\u4e9b\u51fd\u6570\u53ef\u4ee5\u5904\u7406\u6570\u636e\u8868\u4e4b\u95f4\u7684\u5404\u79cd\u5173\u7cfb\u548c\u5408\u5e76\u65b9\u5f0f\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u4f7f\u7528Pandas\u5e93\u6765\u5408\u5e76\u591a\u5f20\u8868\u7684\u5177\u4f53\u6b65\u9aa4\u548c\u6ce8\u610f\u4e8b\u9879\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5bfc\u5165Pandas\u5e93<\/h2>\n<\/p>\n

\u5728\u8fdb\u884c\u4efb\u4f55\u6570\u636e\u64cd\u4f5c\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165Pandas\u5e93\u3002Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684Python\u6570\u636e\u5206\u6790\u5e93\uff0c\u4e13\u95e8\u7528\u4e8e\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8bfb\u53d6\u6570\u636e<\/h2>\n<\/p>\n
\u901a\u5e38\uff0c\u6570\u636e\u8868\u4ee5CSV\u3001Excel\u7b49\u683c\u5f0f\u5b58\u50a8\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u7684read_csv()<\/code>\u6216read_excel()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6\u8fd9\u4e9b\u6570\u636e\u8868\u3002<\/p>\n<\/p>\n
# \u8bfb\u53d6CSV\u6587\u4ef6<\/p>\n
df1 = pd.read_csv('table1.csv')<\/p>\n
df2 = pd.read_csv('table2.csv')<\/p>\n
df3 = pd.read_csv('table3.csv')<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
df1 = pd.read_excel('table1.xlsx')<\/p>\n
df2 = pd.read_excel('table2.xlsx')<\/p>\n
df3 = pd.read_excel('table3.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528concat()\u51fd\u6570<\/h2>\n<\/p>\n
concat()<\/code>\u51fd\u6570\u7528\u4e8e\u6cbf\u7740\u4e00\u4e2a\u8f74\uff08\u884c\u6216\u5217\uff09\u5c06\u591a\u4e2aDataFrame\u8fde\u63a5\u8d77\u6765\u3002\u5b83\u662f\u6700\u7b80\u5355\u548c\u76f4\u63a5\u7684\u65b9\u6cd5\uff0c\u7279\u522b\u9002\u7528\u4e8e\u7ed3\u6784\u76f8\u540c\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
# \u5c06\u591a\u5f20\u8868\u6309\u884c\u5408\u5e76<\/p>\n
result = pd.concat([df1, df2, df3], axis=0)<\/p>\n
\u5c06\u591a\u5f20\u8868\u6309\u5217\u5408\u5e76<\/strong><\/h2>\n
result = pd.concat([df1, df2, df3], axis=1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8be6\u7ec6\u63cf\u8ff0\uff1a\u4fdd\u6301\u6570\u636e\u4e00\u81f4\u6027<\/h3>\n<\/p>\n
\u5728\u5408\u5e76\u4e4b\u524d\uff0c\u786e\u4fdd\u6240\u6709\u8868\u7684\u5217\u540d\u4e00\u81f4\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u5426\u5219\uff0cPandas\u4f1a\u5c06\u4e0d\u4e00\u81f4\u7684\u5217\u540d\u89c6\u4e3a\u4e0d\u540c\u7684\u5217\uff0c\u4ece\u800c\u5bfc\u81f4\u7ed3\u679c\u8868\u4e2d\u51fa\u73b0\u5f88\u591aNaN\u503c\u3002<\/p>\n<\/p>\n
# \u786e\u4fdd\u5217\u540d\u4e00\u81f4<\/p>\n
df1.columns = df1.columns.str.lower()<\/p>\n
df2.columns = df2.columns.str.lower()<\/p>\n
df3.columns = df3.columns.str.lower()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528merge()\u51fd\u6570<\/h2>\n<\/p>\n
merge()<\/code>\u51fd\u6570\u7528\u4e8e\u57fa\u4e8e\u4e00\u4e2a\u6216\u591a\u4e2a\u952e\u5c06\u4e24\u4e2aDataFrame\u5408\u5e76\u5728\u4e00\u8d77\uff0c\u7c7b\u4f3c\u4e8eSQL\u4e2d\u7684JOIN\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
# \u57fa\u4e8e\u5171\u540c\u7684\u952e\u5408\u5e76<\/p>\n
result = pd.merge(df1, df2, on='key_column')<\/p>\n
result = pd.merge(result, df3, on='key_column')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u591a\u79cd\u5408\u5e76\u65b9\u5f0f<\/h3>\n<\/p>\n
merge()<\/code>\u51fd\u6570\u63d0\u4f9b\u4e86\u591a\u79cd\u5408\u5e76\u65b9\u5f0f\uff0c\u5305\u62ec\u5185\u8fde\u63a5\uff08inner join\uff09\u3001\u5de6\u8fde\u63a5\uff08left join\uff09\u3001\u53f3\u8fde\u63a5\uff08right join\uff09\u548c\u5916\u8fde\u63a5\uff08outer join\uff09\u3002<\/p>\n<\/p>\n
# \u5185\u8fde\u63a5<\/p>\n
result = pd.merge(df1, df2, on='key_column', how='inner')<\/p>\n
\u5de6\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(df1, df2, on='key_column', how='left')<\/p>\n
\u53f3\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(df1, df2, on='key_column', how='right')<\/p>\n
\u5916\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(df1, df2, on='key_column', how='outer')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u4f7f\u7528join()\u51fd\u6570<\/h2>\n<\/p>\n
join()<\/code>\u51fd\u6570\u7528\u4e8e\u5c06\u4e24\u4e2aDataFrame\u7684\u884c\u7d22\u5f15\u5bf9\u9f50\u5e76\u5408\u5e76\uff0c\u9002\u7528\u4e8e\u57fa\u4e8e\u7d22\u5f15\u7684\u5408\u5e76\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
# \u57fa\u4e8e\u7d22\u5f15\u5408\u5e76<\/p>\n
result = df1.join(df2, lsuffix='_left', rsuffix='_right')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bbe\u7f6e\u7d22\u5f15<\/h3>\n<\/p>\n
\u5982\u679c\u8868\u4e2d\u6ca1\u6709\u5171\u540c\u7684\u7d22\u5f15\uff0c\u53ef\u4ee5\u5148\u8bbe\u7f6e\u7d22\u5f15\uff0c\u7136\u540e\u518d\u8fdb\u884c\u5408\u5e76\u3002<\/p>\n<\/p>\n
# \u8bbe\u7f6e\u7d22\u5f15<\/p>\n
df1.set_index('key_column', inplace=True)<\/p>\n
df2.set_index('key_column', inplace=True)<\/p>\n
\u5408\u5e76<\/strong><\/h2>\n
result = df1.join(df2)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h2>\n<\/p>\n
\u5408\u5e76\u591a\u5f20\u8868\u540e\uff0c\u53ef\u80fd\u4f1a\u51fa\u73b0\u7f3a\u5931\u503c\uff08NaN\uff09\uff0c\u9700\u8981\u8fdb\u884c\u5904\u7406\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u5904\u7406\u7f3a\u5931\u503c\u7684\u65b9\u6cd5\uff0c\u5305\u62ec\u586b\u5145\u3001\u5220\u9664\u548c\u66ff\u6362\u3002<\/p>\n<\/p>\n
# \u586b\u5145\u7f3a\u5931\u503c<\/p>\n
result.fillna(0, inplace=True)<\/p>\n
\u5220\u9664\u7f3a\u5931\u503c<\/strong><\/h2>\n
result.dropna(inplace=True)<\/p>\n
\u66ff\u6362\u7f3a\u5931\u503c<\/strong><\/h2>\n
result.fillna(method='ffill', inplace=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u5176\u4ed6\u6ce8\u610f\u4e8b\u9879<\/h2>\n<\/p>\n
\u6570\u636e\u7c7b\u578b\u4e00\u81f4\u6027<\/h3>\n<\/p>\n
\u5728\u5408\u5e76\u8868\u4e4b\u524d\uff0c\u786e\u4fdd\u6570\u636e\u7c7b\u578b\u4e00\u81f4\u3002\u5982\u679c\u6570\u636e\u7c7b\u578b\u4e0d\u4e00\u81f4\uff0c\u53ef\u80fd\u4f1a\u5bfc\u81f4\u5408\u5e76\u5931\u8d25\u6216\u6570\u636e\u9519\u8bef\u3002<\/p>\n<\/p>\n
# \u68c0\u67e5\u6570\u636e\u7c7b\u578b<\/p>\n
print(df1.dtypes)<\/p>\n
print(df2.dtypes)<\/p>\n
\u8f6c\u6362\u6570\u636e\u7c7b\u578b<\/strong><\/h2>\n
df1['key_column'] = df1['key_column'].astype(str)<\/p>\n
df2['key_column'] = df2['key_column'].astype(str)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6392\u5e8f<\/h3>\n<\/p>\n
\u5408\u5e76\u540e\uff0c\u53ef\u4ee5\u5bf9\u7ed3\u679c\u8868\u8fdb\u884c\u6392\u5e8f\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u67e5\u770b\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n
# \u6309\u67d0\u4e00\u5217\u6392\u5e8f<\/p>\n
result.sort_values(by='key_column', inplace=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u91cd\u547d\u540d\u5217<\/h3>\n<\/p>\n
\u5982\u679c\u5408\u5e76\u540e\u7684\u8868\u4e2d\u6709\u91cd\u590d\u7684\u5217\u540d\uff0c\u53ef\u4ee5\u91cd\u547d\u540d\u8fd9\u4e9b\u5217\u4ee5\u907f\u514d\u6df7\u6dc6\u3002<\/p>\n<\/p>\n
# \u91cd\u547d\u540d\u5217<\/p>\n
result.rename(columns={'old_name': 'new_name'}, inplace=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4fdd\u5b58\u7ed3\u679c<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u53ef\u4ee5\u5c06\u5408\u5e76\u540e\u7684\u7ed3\u679c\u8868\u4fdd\u5b58\u5230\u6587\u4ef6\u4e2d\uff0c\u65b9\u4fbf\u540e\u7eed\u4f7f\u7528\u3002<\/p>\n<\/p>\n
# \u4fdd\u5b58\u4e3aCSV\u6587\u4ef6<\/p>\n
result.to_csv('result.csv', index=False)<\/p>\n
\u4fdd\u5b58\u4e3aExcel\u6587\u4ef6<\/strong><\/h2>\n
result.to_excel('result.xlsx', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516b\u3001\u5b9e\u9645\u6848\u4f8b<\/h2>\n<\/p>\n
\u6848\u4f8b\u4e00\uff1a\u5408\u5e76\u9500\u552e\u6570\u636e<\/h3>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e09\u5f20\u8868\u683c\uff0c\u5206\u522b\u8bb0\u5f55\u4e86\u4e0d\u540c\u6708\u4efd\u7684\u9500\u552e\u6570\u636e\uff0c\u6211\u4eec\u5e0c\u671b\u5c06\u8fd9\u4e9b\u8868\u683c\u5408\u5e76\u4e3a\u4e00\u4e2a\u603b\u7684\u9500\u552e\u6570\u636e\u8868\u3002<\/p>\n<\/p>\n
# \u8bfb\u53d6\u6570\u636e<\/p>\n
jan_sales = pd.read_csv('january_sales.csv')<\/p>\n
feb_sales = pd.read_csv('february_sales.csv')<\/p>\n
mar_sales = pd.read_csv('march_sales.csv')<\/p>\n
\u5408\u5e76\u6570\u636e<\/strong><\/h2>\n
total_sales = pd.concat([jan_sales, feb_sales, mar_sales], axis=0)<\/p>\n
\u5904\u7406\u7f3a\u5931\u503c<\/strong><\/h2>\n
total_sales.fillna(0, inplace=True)<\/p>\n
\u6392\u5e8f<\/strong><\/h2>\n
total_sales.sort_values(by='sale_date', inplace=True)<\/p>\n
\u4fdd\u5b58\u7ed3\u679c<\/strong><\/h2>\n
total_sales.to_csv('total_sales.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6848\u4f8b\u4e8c\uff1a\u5408\u5e76\u5ba2\u6237\u4fe1\u606f<\/h3>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e24\u5f20\u8868\u683c\uff0c\u5206\u522b\u8bb0\u5f55\u4e86\u5ba2\u6237\u7684\u57fa\u672c\u4fe1\u606f\u548c\u8d2d\u4e70\u4fe1\u606f\uff0c\u6211\u4eec\u5e0c\u671b\u5c06\u8fd9\u4e9b\u8868\u683c\u5408\u5e76\uff0c\u4ee5\u4fbf\u66f4\u5168\u9762\u5730\u4e86\u89e3\u5ba2\u6237\u3002<\/p>\n<\/p>\n
# \u8bfb\u53d6\u6570\u636e<\/p>\n
customer_info = pd.read_csv('customer_info.csv')<\/p>\n
purchase_info = pd.read_csv('purchase_info.csv')<\/p>\n
\u57fa\u4e8e\u5ba2\u6237ID\u5408\u5e76<\/strong><\/h2>\n
customer_data = pd.merge(customer_info, purchase_info, on='customer_id', how='inner')<\/p>\n
\u5904\u7406\u7f3a\u5931\u503c<\/strong><\/h2>\n
customer_data.fillna('Unknown', inplace=True)<\/p>\n
\u91cd\u547d\u540d\u5217<\/strong><\/h2>\n
customer_data.rename(columns={'name': 'customer_name'}, inplace=True)<\/p>\n
\u4fdd\u5b58\u7ed3\u679c<\/strong><\/h2>\n
customer_data.to_csv('customer_data.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\u548c\u6848\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u6e05\u695a\u5730\u4e86\u89e3\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u5c06\u591a\u5f20\u8868\u5408\u5e76\u4e3a\u4e00\u4e2a\u8868\u3002\u5173\u952e\u5728\u4e8e\u9009\u62e9\u5408\u9002\u7684\u5408\u5e76\u51fd\u6570\uff0c\u5e76\u5728\u5408\u5e76\u524d\u540e\u5904\u7406\u597d\u6570\u636e\u7684\u4e00\u81f4\u6027\u548c\u5b8c\u6574\u6027\u3002\u8fd9\u6837\uff0c\u624d\u80fd\u786e\u4fdd\u5408\u5e76\u540e\u7684\u6570\u636e\u8868\u51c6\u786e\u3001\u5b8c\u6574\uff0c\u4e3a\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u591a\u4e2a\u8868\u683c\u6587\u4ef6\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u8bfb\u53d6\u591a\u79cd\u683c\u5f0f\u7684\u8868\u683c\u6587\u4ef6\uff0c\u5982CSV\u3001Excel\u7b49\u3002\u901a\u8fc7pd.read_csv()<\/code>\u53ef\u4ee5\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u800cpd.read_excel()<\/code>\u5219\u53ef\u4ee5\u8bfb\u53d6Excel\u6587\u4ef6\u3002\u786e\u4fdd\u5728\u8bfb\u53d6\u65f6\u6307\u5b9a\u6b63\u786e\u7684\u6587\u4ef6\u8def\u5f84\u548c\u6587\u4ef6\u540d\uff0c\u8fd9\u6837\u624d\u80fd\u987a\u5229\u52a0\u8f7d\u6570\u636e\u3002<\/p>\n
\u5408\u5e76\u591a\u4e2a\u8868\u683c\u65f6\uff0c\u5982\u4f55\u5904\u7406\u91cd\u590d\u7684\u5217\u540d\uff1f<\/strong>
\u5408\u5e76\u591a\u4e2a\u8868\u683c\u65f6\uff0c\u5982\u679c\u5b58\u5728\u91cd\u590d\u7684\u5217\u540d\uff0cPandas\u4f1a\u81ea\u52a8\u6dfb\u52a0\u540e\u7f00\u6765\u533a\u5206\u8fd9\u4e9b\u5217\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6esuffixes<\/code>\u53c2\u6570\u6765\u5b9a\u4e49\u540e\u7f00\uff0c\u6216\u8005\u5728\u5408\u5e76\u540e\u624b\u52a8\u91cd\u547d\u540d\u91cd\u590d\u7684\u5217\u540d\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u7ba1\u7406\u6570\u636e\u3002<\/p>\n
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