{"id":2929,"date":"2023-07-20T01:28:28","date_gmt":"2023-07-20T01:28:28","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e5%90%88%e5%b9%b6%e5%a4%9a%e4%b8%aa%e6%95%b0%e6%8d%ae%e6%a1%86\/"},"modified":"2023-07-20T01:28:28","modified_gmt":"2023-07-20T01:28:28","slug":"pandas-%e5%90%88%e5%b9%b6%e5%a4%9a%e4%b8%aa%e6%95%b0%e6%8d%ae%e6%a1%86","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e5%90%88%e5%b9%b6%e5%a4%9a%e4%b8%aa%e6%95%b0%e6%8d%ae%e6%a1%86\/","title":{"rendered":"\u5982\u4f55\u5728 pandas \u4e2d\u5408\u5e76\u591a\u4e2a dataframe\uff08\u793a\u4f8b\uff09"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5728 pandas \u4e2d\u4e00\u6b21\u5408\u5e76\u591a\u4e2a DataFrame\uff1a<\/span><\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\nfrom<\/span> functools import<\/span> reduce\n\n#define list of DataFrames\n<\/span>dfs = [df1, df2, df3]\n\n#merge all DataFrames into one\n<\/span>final_df = reduce(lambda left,right: pd.merge<\/span> (left,right,on=[' column_name<\/span> '],\n                                            how=' outer<\/span> '), dfs)<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u8bed\u6cd5\uff1a<\/span><\/p>\n
\u793a\u4f8b\uff1a\u5408\u5e76<\/span>Pandas \u4e2d\u7684\u591a\u4e2a DataFrame<\/strong><\/h2>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u4e09\u4e2a panda DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u6765\u81ea\u4e0d\u540c\u7403\u961f\u7684\u7bee\u7403\u8fd0\u52a8\u5458\u7684\u4fe1\u606f\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrames\n<\/span>df1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D'],\n                    ' points<\/span> ': [18, 22, 19, 14]})\n\ndf2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C'],\n                    ' assists<\/span> ': [4, 9, 14]})\n\ndf3 = pd. DataFrame<\/span> ({' team<\/span> ': ['C', 'D', 'E', 'F'],\n                    ' rebounds<\/span> ': [10, 17, 11, 10]})\n\n#view DataFrames\n<\/span>print<\/span> (df1)\n\n  team points\n0 to 18\n1 B 22\n2 C 19\n3 D 14\n\nprint<\/span> (df2)\n\n  team assists\n0 to 4\n1 B 9\n2 C 14\n\nprint<\/span> (df3)\n\n  team rebounds\n0 C 10\n1 D 17\n2 E 11\n3 F 10\n<\/strong><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5c06\u4e09\u4e2a DataFrame \u5408\u5e76\u4e3a\u4e00\u4e2a\uff1a<\/span><\/p>\n
 from<\/span> functools import<\/span> reduce\n\n#define list of DataFrames\n<\/span>dfs = [df1, df2, df3]\n\n#merge all DataFrames into one\n<\/span>final_df = reduce(lambda left,right: pd.merge<\/span> (left,right,on=[' team<\/span> '],\n                                            how=' outer<\/span> '), dfs)\n\n#view merged DataFrame\n<\/span>print<\/span> (final_df)\n\n  team points assists rebounds\n0 A 18.0 4.0 NaN\n1 B 22.0 9.0 NaN\n2 C 19.0 14.0 10.0\n3 D 14.0 NaN 17.0\n4 E NaN NaN 11.0\n5 F NaN NaN 10.0<\/strong><\/span><\/pre>\n
\u6700\u7ec8\u7ed3\u679c\u662f\u4e00\u4e2a\u5305\u542b\u6240\u6709\u4e09\u4e2a DataFrame \u4fe1\u606f\u7684 DataFrame\u3002<\/span><\/span><\/p>\n
\u8bf7\u6ce8\u610f\uff0c NaN<\/strong>\u503c\u7528\u4e8e\u586b\u5145\u6700\u7ec8 DataFrame \u4e2d\u7684\u7a7a\u5355\u5143\u683c\u3002<\/span><\/p>\n
\u8981\u4f7f\u7528NaN<\/strong>\u4ee5\u5916\u7684\u503c\u586b\u5145\u7a7a\u5355\u5143\u683c\uff0c\u53ef\u4ee5\u4f7f\u7528fillna()<\/strong>\u51fd\u6570\uff1a<\/span><\/p>\n
 from<\/span> functools import<\/span> reduce\n\n#define list of DataFrames\n<\/span>dfs = [df1, df2, df3]\n\n#merge all DataFrames into one\n<\/span>final_df = reduce(lambda left,right: pd.merge<\/span> (left,right,on=[' team<\/span> '],\n                                            how=' outer<\/span> '), dfs). fillna<\/span> (' none<\/span> ')\n\n#view merged DataFrame\n<\/span>print<\/span> (final_df)\n\n  team points assists rebounds\n0 A 18.0 4.0 none\n1 B 22.0 9.0 none\n2 C 19.0 14.0 10.0\n3 D 14.0 none 17.0\n4 E none none 11.0\n5 F none none 10.0<\/strong><\/span><\/pre>\n
\u73b0\u5728\uff0c\u6bcf\u4e2a\u7a7a\u5355\u5143\u683c\u90fd\u7528\u201c none<\/strong> \u201d\u800c\u4e0d\u662fNaN<\/strong>\u586b\u5145\u3002<\/span><\/p>\n
\u6ce8\u610f<\/strong>\uff1a\u60a8\u53ef\u4ee5\u5728\u6b64\u5904<\/a>\u627e\u5230 pandas \u4e2d\u5408\u5e76<\/strong>\u529f\u80fd\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u64cd\u4f5c\uff1a<\/span><\/p>\n
\u5982\u4f55\u5408\u5e76\u7d22\u5f15\u4e0a\u7684\u4e24\u4e2a Pandas DataFrame
\u5982\u4f55\u8de8\u591a\u5217\u5408\u5e76 Pandas DataFrame<\/a>
 \u5982\u4f55\u5806\u53e0\u591a\u4e2a Pandas DataFrame<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5728 pandas \u4e2d\u4e00\u6b21\u5408\u5e76\u591a\u4e2a DataFrame\uff1a import pandas as p […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2929","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 Pandas \u4e2d\u5408\u5e76\u591a\u4e2a DataFrame\uff08\u9644\u793a\u4f8b\uff09 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u5c06\u591a\u4e2a DataFrame \u5408\u5e76\u4e3a\u4e00\u4e2a\uff0c\u5305\u62ec\u4e00\u4e2a\u793a\u4f8b\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/pandas-\u5408\u5e76\u591a\u4e2a\u6570\u636e\u6846\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u5728 Pandas \u4e2d\u5408\u5e76\u591a\u4e2a DataFrame\uff08\u9644\u793a\u4f8b\uff09 - 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