{"id":1169568,"date":"2025-01-15T16:12:15","date_gmt":"2025-01-15T08:12:15","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1169568.html"},"modified":"2025-01-15T16:12:17","modified_gmt":"2025-01-15T08:12:17","slug":"python%e5%a6%82%e4%bd%95%e8%bf%9b%e8%a1%8c%e8%a1%a8%e8%bf%9e%e6%8e%a5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1169568.html","title":{"rendered":"python\u5982\u4f55\u8fdb\u884c\u8868\u8fde\u63a5"},"content":{"rendered":"

\"python\u5982\u4f55\u8fdb\u884c\u8868\u8fde\u63a5\"<\/p>\n

Python\u8fdb\u884c\u8868\u8fde\u63a5\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u4e2d\u7684merge\u51fd\u6570\u3001join\u51fd\u6570\u3001concat\u51fd\u6570<\/strong>\u3002\u5176\u4e2d\uff0cmerge\u51fd\u6570\u662f\u6700\u5e38\u7528\u7684\uff0c\u5b83\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u5217\u540d\u6216\u7d22\u5f15\u6765\u5b9e\u73b0\u5185\u8fde\u63a5\u3001\u5de6\u8fde\u63a5\u3001\u53f3\u8fde\u63a5\u548c\u5916\u8fde\u63a5\u3002merge\u51fd\u6570\u53ef\u4ee5\u7528\u6765\u5c06\u4e24\u4e2aDataFrame\u5bf9\u8c61\u6309\u67d0\u4e00\u5217\u6216\u591a\u5217\u8fdb\u884c\u8fde\u63a5<\/strong>\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u8fdb\u884c\u8868\u8fde\u63a5\u3002<\/p>\n<\/p>\n

\u4e00\u3001Pandas\u5e93\u7b80\u4ecb<\/h3>\n<\/p>\n

Pandas\u662fPython\u4e2d\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002Pandas\u4e3b\u8981\u6709\u4e24\u79cd\u6570\u636e\u7ed3\u6784\uff1aSeries\uff08\u4e00\u7ef4\u6570\u636e\uff09\u548cDataFrame\uff08\u4e8c\u7ef4\u6570\u636e\uff09\u3002DataFrame\u662f\u4e00\u4e2a\u8868\u683c\u578b\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5b83\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u5e26\u6709\u884c\u6807\u7b7e\u548c\u5217\u6807\u7b7e\u7684\u4e8c\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n

\u4e8c\u3001merge\u51fd\u6570<\/h3>\n<\/p>\n

merge\u51fd\u6570\u662fPandas\u4e2d\u7528\u6765\u8fdb\u884c\u6570\u636e\u8868\u8fde\u63a5\u7684\u4e3b\u8981\u5de5\u5177<\/strong>\u3002\u5b83\u7c7b\u4f3c\u4e8eSQL\u4e2d\u7684JOIN\u64cd\u4f5c\uff0c\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u5217\u6216\u7d22\u5f15\u6765\u5408\u5e76\u4e24\u4e2aDataFrame\u5bf9\u8c61\u3002\u4e0b\u9762\u662fmerge\u51fd\u6570\u7684\u8bed\u6cd5\uff1a<\/p>\n<\/p>\n

pd.merge(left, right, how='inner', on=None, left_on=None, right_on=None,<\/p>\n
         left_index=False, right_index=False, sort=False,<\/p>\n
         suffixes=('_x', '_y'), copy=True, indicator=False, validate=None)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1\u3001\u5185\u8fde\u63a5\uff08Inner Join\uff09<\/h4>\n<\/p>\n
\u5185\u8fde\u63a5\u53ea\u4fdd\u7559\u4e24\u4e2a\u8868\u4e2d\u90fd\u6709\u7684\u8bb0\u5f55\uff0c\u4e22\u5f03\u5176\u4ed6\u8bb0\u5f55\u3002\u53ef\u4ee5\u4f7f\u7528how='inner'<\/code>\u6765\u5b9e\u73b0\u5185\u8fde\u63a5\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efa\u4e24\u4e2aDataFrame<\/strong><\/h2>\n
df1 = pd.DataFrame({'key': ['A', 'B', 'C', 'D'],<\/p>\n
                    'value': [1, 2, 3, 4]})<\/p>\n
df2 = pd.DataFrame({'key': ['B', 'D', 'E', 'F'],<\/p>\n
                    'value': [5, 6, 7, 8]})<\/p>\n
\u5185\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(df1, df2, how='inner', on='key')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5de6\u8fde\u63a5\uff08Left Join\uff09<\/h4>\n<\/p>\n
\u5de6\u8fde\u63a5\u4fdd\u7559\u5de6\u8868\u4e2d\u7684\u6240\u6709\u8bb0\u5f55\uff0c\u5e76\u5c06\u53f3\u8868\u4e2d\u5339\u914d\u7684\u8bb0\u5f55\u5408\u5e76\u8fdb\u6765\u3002\u5982\u679c\u53f3\u8868\u4e2d\u6ca1\u6709\u5339\u914d\u7684\u8bb0\u5f55\uff0c\u5219\u7ed3\u679c\u4e2d\u5305\u542bNaN\u3002\u53ef\u4ee5\u4f7f\u7528how='left'<\/code>\u6765\u5b9e\u73b0\u5de6\u8fde\u63a5\u3002<\/p>\n<\/p>\n
# \u5de6\u8fde\u63a5<\/p>\n
result = pd.merge(df1, df2, how='left', on='key')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u53f3\u8fde\u63a5\uff08Right Join\uff09<\/h4>\n<\/p>\n
\u53f3\u8fde\u63a5\u4fdd\u7559\u53f3\u8868\u4e2d\u7684\u6240\u6709\u8bb0\u5f55\uff0c\u5e76\u5c06\u5de6\u8868\u4e2d\u5339\u914d\u7684\u8bb0\u5f55\u5408\u5e76\u8fdb\u6765\u3002\u5982\u679c\u5de6\u8868\u4e2d\u6ca1\u6709\u5339\u914d\u7684\u8bb0\u5f55\uff0c\u5219\u7ed3\u679c\u4e2d\u5305\u542bNaN\u3002\u53ef\u4ee5\u4f7f\u7528how='right'<\/code>\u6765\u5b9e\u73b0\u53f3\u8fde\u63a5\u3002<\/p>\n<\/p>\n
# \u53f3\u8fde\u63a5<\/p>\n
result = pd.merge(df1, df2, how='right', on='key')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5916\u8fde\u63a5\uff08Outer Join\uff09<\/h4>\n<\/p>\n
\u5916\u8fde\u63a5\u4fdd\u7559\u4e24\u4e2a\u8868\u4e2d\u7684\u6240\u6709\u8bb0\u5f55\uff0c\u5e76\u5c06\u5339\u914d\u7684\u8bb0\u5f55\u5408\u5e76\u8fdb\u6765\u3002\u5982\u679c\u67d0\u4e2a\u8868\u4e2d\u6ca1\u6709\u5339\u914d\u7684\u8bb0\u5f55\uff0c\u5219\u7ed3\u679c\u4e2d\u5305\u542bNaN\u3002\u53ef\u4ee5\u4f7f\u7528how='outer'<\/code>\u6765\u5b9e\u73b0\u5916\u8fde\u63a5\u3002<\/p>\n<\/p>\n
# \u5916\u8fde\u63a5<\/p>\n
result = pd.merge(df1, df2, how='outer', on='key')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001join\u51fd\u6570<\/h3>\n<\/p>\n
join\u51fd\u6570\u662f\u53e6\u4e00\u4e2a\u7528\u4e8e\u8868\u8fde\u63a5\u7684\u65b9\u6cd5\uff0c\u4e3b\u8981\u7528\u4e8e\u7d22\u5f15\u4e0a\u7684\u8fde\u63a5<\/strong>\u3002\u5b83\u53ef\u4ee5\u65b9\u4fbf\u5730\u5c06\u4e24\u4e2aDataFrame\u5bf9\u8c61\u6309\u7d22\u5f15\u8fdb\u884c\u8fde\u63a5\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u4e24\u4e2aDataFrame<\/p>\n
df1 = pd.DataFrame({'value': [1, 2, 3, 4]}, index=['A', 'B', 'C', 'D'])<\/p>\n
df2 = pd.DataFrame({'value': [5, 6, 7, 8]}, index=['B', 'D', 'E', 'F'])<\/p>\n
\u4f7f\u7528join\u8fdb\u884c\u5de6\u8fde\u63a5<\/strong><\/h2>\n
result = df1.join(df2, how='left', lsuffix='_left', rsuffix='_right')<\/p>\n
print(result)<\/p>\n
\u4f7f\u7528join\u8fdb\u884c\u53f3\u8fde\u63a5<\/strong><\/h2>\n
result = df1.join(df2, how='right', lsuffix='_left', rsuffix='_right')<\/p>\n
print(result)<\/p>\n
\u4f7f\u7528join\u8fdb\u884c\u5185\u8fde\u63a5<\/strong><\/h2>\n
result = df1.join(df2, how='inner', lsuffix='_left', rsuffix='_right')<\/p>\n
print(result)<\/p>\n
\u4f7f\u7528join\u8fdb\u884c\u5916\u8fde\u63a5<\/strong><\/h2>\n
result = df1.join(df2, how='outer', lsuffix='_left', rsuffix='_right')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001concat\u51fd\u6570<\/h3>\n<\/p>\n
concat\u51fd\u6570\u7528\u4e8e\u6cbf\u7740\u6307\u5b9a\u8f74\u5c06\u591a\u4e2aDataFrame\u5bf9\u8c61\u8fdb\u884c\u5408\u5e76<\/strong>\u3002\u5b83\u53ef\u4ee5\u5b9e\u73b0\u7c7b\u4f3c\u4e8eSQL\u4e2d\u7684UNION\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u4e24\u4e2aDataFrame<\/p>\n
df1 = pd.DataFrame({'key': ['A', 'B', 'C'],<\/p>\n
                    'value1': [1, 2, 3]})<\/p>\n
df2 = pd.DataFrame({'key': ['D', 'E', 'F'],<\/p>\n
                    'value2': [4, 5, 6]})<\/p>\n
\u4f7f\u7528concat\u8fdb\u884c\u7eb5\u5411\u5408\u5e76<\/strong><\/h2>\n
result = pd.concat([df1, df2], axis=0)<\/p>\n
print(result)<\/p>\n
\u4f7f\u7528concat\u8fdb\u884c\u6a2a\u5411\u5408\u5e76<\/strong><\/h2>\n
result = pd.concat([df1, df2], axis=1)<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u793a\u4f8b\u5e94\u7528<\/h3>\n<\/p>\n
1\u3001\u94f6\u884c\u5ba2\u6237\u6570\u636e\u5206\u6790<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e24\u4e2aDataFrame\u5bf9\u8c61\uff0c\u5206\u522b\u5305\u542b\u94f6\u884c\u5ba2\u6237\u7684\u57fa\u672c\u4fe1\u606f\u548c\u4ea4\u6613\u8bb0\u5f55\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8fde\u63a5\u8fd9\u4e24\u4e2a\u8868\u6765\u5206\u6790\u5ba2\u6237\u7684\u4ea4\u6613\u884c\u4e3a\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u5ba2\u6237\u57fa\u672c\u4fe1\u606f\u8868<\/p>\n
customers = pd.DataFrame({'customer_id': [1, 2, 3, 4],<\/p>\n
                          'name': ['Alice', 'Bob', 'Charlie', 'David'],<\/p>\n
                          'age': [25, 30, 35, 40]})<\/p>\n
\u521b\u5efa\u4ea4\u6613\u8bb0\u5f55\u8868<\/strong><\/h2>\n
transactions = pd.DataFrame({'transaction_id': [101, 102, 103, 104],<\/p>\n
                             'customer_id': [1, 2, 2, 3],<\/p>\n
                             'amount': [100, 200, 150, 300]})<\/p>\n
\u5185\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(customers, transactions, how='inner', on='customer_id')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5b66\u751f\u6210\u7ee9\u5206\u6790<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e24\u4e2aDataFrame\u5bf9\u8c61\uff0c\u5206\u522b\u5305\u542b\u5b66\u751f\u7684\u4e2a\u4eba\u4fe1\u606f\u548c\u8003\u8bd5\u6210\u7ee9\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8fde\u63a5\u8fd9\u4e24\u4e2a\u8868\u6765\u5206\u6790\u5b66\u751f\u7684\u6210\u7ee9\u60c5\u51b5\u3002<\/p>\n<\/p>\n
# \u521b\u5efa\u5b66\u751f\u4e2a\u4eba\u4fe1\u606f\u8868<\/p>\n
students = pd.DataFrame({'student_id': [1, 2, 3, 4],<\/p>\n
                         'name': ['Alice', 'Bob', 'Charlie', 'David'],<\/p>\n
                         'age': [20, 21, 22, 23]})<\/p>\n
\u521b\u5efa\u8003\u8bd5\u6210\u7ee9\u8868<\/strong><\/h2>\n
scores = pd.DataFrame({'exam_id': [101, 102, 103, 104],<\/p>\n
                       'student_id': [1, 2, 3, 4],<\/p>\n
                       'score': [90, 85, 95, 80]})<\/p>\n
\u5de6\u8fde\u63a5<\/strong><\/h2>\n
result = pd.merge(students, scores, how='left', on='student_id')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u5185\u5bb9\u53ef\u4ee5\u770b\u51fa\uff0cPandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u8fdb\u884c\u8868\u8fde\u63a5\uff0c\u4e3b\u8981\u5305\u62ecmerge\u51fd\u6570\u3001join\u51fd\u6570\u548cconcat\u51fd\u6570<\/strong>\u3002\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u6ee1\u8db3\u4e0d\u540c\u573a\u666f\u4e0b\u7684\u6570\u636e\u5408\u5e76\u9700\u6c42\u3002\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u7075\u6d3b\u6027\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u8fde\u63a5\u65b9\u5f0f\uff0c\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u5de5\u5177\u6765\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u8fdb\u884c\u8868\u8fde\u63a5\uff1f<\/strong>
\u5728Python\u4e2d\uff0cPandas\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\uff0c\u5305\u62ec\u8868\u8fde\u63a5\u3002\u4f7f\u7528merge()<\/code>\u51fd\u6570\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06\u4e24\u4e2aDataFrame\u6309\u7167\u67d0\u4e00\u5217\u6216\u591a\u5217\u8fdb\u884c\u8fde\u63a5\u3002\u4f60\u53ea\u9700\u6307\u5b9a\u8fde\u63a5\u7684\u952e\u548c\u8fde\u63a5\u7684\u65b9\u5f0f\uff08\u5982\u5185\u8fde\u63a5\u3001\u5916\u8fde\u63a5\u7b49\uff09\uff0cPandas\u4f1a\u81ea\u52a8\u5904\u7406\u6570\u636e\u7684\u5408\u5e76\u3002\u4f8b\u5982\uff0c\u4f7f\u7528pd.merge(df1, df2, on='key_column', how='inner')<\/code>\u53ef\u4ee5\u5b9e\u73b0\u5185\u8fde\u63a5\u3002<\/p>\n
\u5728\u8fdb\u884c\u8868\u8fde\u63a5\u65f6\uff0c\u5982\u4f55\u5904\u7406\u91cd\u590d\u7684\u5217\u540d\uff1f<\/strong>
\u5728\u8fdb\u884c\u8868\u8fde\u63a5\u65f6\uff0c\u5982\u679c\u4e24\u4e2a\u8868\u4e2d\u5305\u542b\u76f8\u540c\u7684\u5217\u540d\uff0cPandas\u4f1a\u81ea\u52a8\u5728\u7ed3\u679cDataFrame\u4e2d\u4e3a\u8fd9\u4e9b\u5217\u540d\u6dfb\u52a0\u540e\u7f00\uff0c\u4ee5\u907f\u514d\u51b2\u7a81\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570suffixes=('_left', '_right')<\/code>\u81ea\u5b9a\u4e49\u540e\u7f00\uff0c\u786e\u4fdd\u5728\u5408\u5e76\u540e\u7684\u6570\u636e\u4e2d\u4ecd\u7136\u80fd\u6e05\u6670\u533a\u5206\u8fd9\u4e9b\u5217\u3002<\/p>\n
\u8868\u8fde\u63a5\u540e\u5982\u4f55\u68c0\u67e5\u5408\u5e76\u7ed3\u679c\u7684\u5b8c\u6574\u6027\u548c\u6b63\u786e\u6027\uff1f<\/strong>
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