{"id":2918,"date":"2023-07-20T02:44:20","date_gmt":"2023-07-20T02:44:20","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e5%88%86%e7%bb%84%e5%88%97%e8%a1%a8\/"},"modified":"2023-07-20T02:44:20","modified_gmt":"2023-07-20T02:44:20","slug":"pandas-%e5%88%86%e7%bb%84%e5%88%97%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e5%88%86%e7%bb%84%e5%88%97%e8%a1%a8\/","title":{"rendered":"Pandas\uff1a\u5982\u4f55\u4f7f\u7528 groupby \u5bf9\u5217\u8868\u4e2d\u7684\u884c\u8fdb\u884c\u5206\u7ec4"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u5c06 DataFrame \u884c\u5206\u7ec4\u5230 pandas \u4e2d\u7684 GroupBy \u5217\u8868\u4e2d\uff1a<\/span><\/p>\n

\u65b9\u6cd5 1\uff1a\u5c06\u5217\u8868\u4e2d\u7684\u884c\u5206\u7ec4\u4e3a\u4e00\u5217<\/strong><\/span><\/p>\n

 df. groupby<\/span> (' group_var<\/span> ')[' values_var<\/span> ']. agg<\/span> ( list<\/span> ). reset_index<\/span> (name=' values_var<\/span> ')\n<\/strong><\/pre>\n
\u65b9\u6cd5 2\uff1a\u5c06\u5217\u8868\u4e2d\u7684\u884c\u5206\u7ec4\u4e3a\u591a\u5217<\/strong><\/span><\/p>\n
 df. groupby<\/span> (' team<\/span> '). agg<\/span> (list)<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u4ee5\u4e0b pandas DataFrame \u7684\u6bcf\u79cd\u65b9\u6cd5\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'C', 'C', 'C'],\n                   ' points<\/span> ': [10, 10, 12, 15, 19, 23, 20, 20, 26],\n                   ' assists<\/span> ': [6, 8, 9, 11, 13, 8, 8, 15, 10]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists\n0 to 10 6\n1 to 10 8\n2 to 12 9\n3 to 15 11\n4 B 19 13\n5 B 23 8\n6 C 20 8\n7 C 20 15\n8 C 26 10\n<\/strong><\/pre>\n
\u793a\u4f8b 1\uff1a\u5c06\u5217\u8868\u4e2d\u7684\u884c\u5206\u7ec4\u4e3a\u4e00\u5217<\/strong><\/span><\/h3>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u6309\u56e2\u961f<\/strong>\u5217\u5bf9\u884c\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u751f\u6210\u70b9<\/strong>\u5217\u503c\u7684\u5217\u8868\uff1a<\/span><\/p>\n
 #group points values into list by team<\/span>\ndf.<\/span> groupby<\/span> (' team<\/span> ')[' points<\/span> '].<\/span> agg<\/span> ( list<\/span> ).<\/span> reset_index<\/span> (name=' points<\/span> ')\n\n     team points\n0 A [10, 10, 12, 15]\n1 B [19, 23]\n2 C [20, 20, 26]<\/span><\/strong><\/span><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0cDataFrame \u4e2d\u4e3a\u6bcf\u4e2a\u72ec\u7279\u7684\u56e2\u961f\u751f\u6210\u4e86\u4e00\u4e2a\u70b9\u503c\u5217\u8868\u3002<\/span><\/p>\n
\u793a\u4f8b 2\uff1a\u5c06\u5217\u8868\u4e2d\u7684\u884c\u5206\u7ec4\u4e3a\u591a\u5217<\/strong><\/span><\/h3>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u6309\u56e2\u961f<\/strong>\u5217\u5bf9\u884c\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u751f\u6210\u70b9<\/strong>\u548c\u8f85\u52a9<\/strong>\u5217\u7684\u503c\u5217\u8868\uff1a<\/span><\/p>\n
 #group points and assists values into lists by team<\/span>\ndf. groupby<\/span> (' team<\/span> '). agg<\/span> ( list<\/span> )\n\n\tassist points\nteam\t\t\nA [10, 10, 12, 15] [6, 8, 9, 11]\nB [19, 23] [13, 8]\nC [20, 20, 26] [8, 15, 10]<\/strong><\/span><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0cDataFrame \u4e2d\u4e3a\u6bcf\u4e2a\u72ec\u7279\u7684\u56e2\u961f\u751f\u6210\u4e86\u4e00\u4e2a\u5206\u503c\u5217\u8868\u548c\u4e00\u4e2a\u8f85\u52a9\u503c\u5217\u8868\u3002<\/span><\/p>\n
\u6ce8\u610f<\/strong>\uff1a\u60a8\u53ef\u4ee5\u5728\u6b64\u5904<\/a>\u627e\u5230 pandas \u4e2d GroupBy \u64cd\u4f5c\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
 Pandas\uff1a\u5982\u4f55\u8ba1\u7b97\u6bcf\u7ec4\u7684\u7d2f\u8ba1\u548c<\/a>
Pandas\uff1a\u5982\u4f55\u6309\u7ec4\u8ba1\u7b97\u552f\u4e00\u503c<\/a>
Pandas\uff1a\u5982\u4f55\u6309\u7ec4\u8ba1\u7b97\u4f17\u6570<\/a>
Pandas\uff1a\u5982\u4f55\u6309\u7ec4\u8ba1\u7b97\u76f8\u5173\u6027<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u5c06 DataFrame \u884c\u5206\u7ec4\u5230 pandas \u4e2d\u7684 GroupBy \u5217\u8868\u4e2d\uff1a \u65b9\u6cd5 1\uff1a\u5c06 […]<\/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-2918","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\nPandas\uff1a\u5982\u4f55\u4f7f\u7528 GroupBy \u5bf9\u5217\u8868\u4e2d\u7684\u884c\u8fdb\u884c\u5206\u7ec4 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 GroupBy \u5bf9 pandas DataFrame \u4e2d\u7684\u5217\u8868\u4e2d\u7684\u884c\u8fdb\u884c\u5206\u7ec4\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-\u5206\u7ec4\u5217\u8868\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas\uff1a\u5982\u4f55\u4f7f\u7528 GroupBy \u5bf9\u5217\u8868\u4e2d\u7684\u884c\u8fdb\u884c\u5206\u7ec4 - 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