{"id":2662,"date":"2023-07-21T07:08:01","date_gmt":"2023-07-21T07:08:01","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e5%88%86%e7%bb%84%e7%9b%b8%e5%85%b3%e6%80%a7\/"},"modified":"2023-07-21T07:08:01","modified_gmt":"2023-07-21T07:08:01","slug":"pandas-%e5%88%86%e7%bb%84%e7%9b%b8%e5%85%b3%e6%80%a7","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e5%88%86%e7%bb%84%e7%9b%b8%e5%85%b3%e6%80%a7\/","title":{"rendered":"\u5982\u4f55\u5728 pandas \u4e2d\u6309\u7ec4\u8ba1\u7b97\u76f8\u5173\u6027"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5728 pandas \u4e2d\u6309\u7ec4\u8ba1\u7b97\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u6027\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">group_var<\/span> ')[[' <span style=\"color: #ff0000;\">values1<\/span> ',' <span style=\"color: #ff0000;\">values2<\/span> ']]. <span style=\"color: #3366ff;\">corr<\/span> (). <span style=\"color: #3366ff;\">unstack<\/span> (). <span style=\"color: #3366ff;\">iloc<\/span> [:, <span style=\"color: #008000;\">1<\/span> ]\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u8bed\u6cd5\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u6309 Pandas \u4e2d\u7684\u7ec4\u8ba1\u7b97\u76f8\u5173\u6027<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [2, 7, 9, 3, 12, 10, 14, 21]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)<\/strong><\/span><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6765\u8ba1\u7b97<strong>\u5f97\u5206<\/strong>\u548c<strong>\u52a9\u653b<\/strong>\u4e4b\u95f4\u7684\u76f8\u5173\u6027\uff08\u6309<strong>\u7403\u961f<\/strong>\u5206\u7ec4\uff09\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate correlation between points and assists, grouped by team\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">team<\/span> ')[[' <span style=\"color: #ff0000;\">points<\/span> ',' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">corr<\/span> (). <span style=\"color: #3366ff;\">unstack<\/span> (). <span style=\"color: #3366ff;\">iloc<\/span> [:, <span style=\"color: #008000;\">1<\/span> ]\n\nteam\nAt 0.603053\nB 0.981798\nName: (points, assists), dtype: float64<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">A \u961f\u7684\u5f97\u5206\u548c\u52a9\u653b\u4e4b\u95f4\u7684\u76f8\u5173\u7cfb\u6570\u4e3a<strong>0.603053<\/strong> \u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">B \u961f\u5f97\u5206\u4e0e\u52a9\u653b\u4e4b\u95f4\u7684\u76f8\u5173\u7cfb\u6570\u4e3a<strong>0.981798<\/strong> \u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u76f8\u5173\u7cfb\u6570\u5747\u4e3a\u6b63\uff0c\u8fd9\u8868\u660e\u4e24\u652f\u7403\u961f\u7684\u5f97\u5206\u548c\u52a9\u653b\u4e4b\u95f4\u5b58\u5728\u6b63\u76f8\u5173\u5173\u7cfb\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e5f\u5c31\u662f\u8bf4\uff0c\u503e\u5411\u4e8e\u5f97\u5206\u66f4\u591a\u7684\u7403\u5458\u4e5f\u503e\u5411\u4e8e\u8bb0\u5f55\u66f4\u591a\u7684\u52a9\u653b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong><a href=\"https:\/\/statorials.org\/cn\" target=\"_blank\" rel=\"noopener\">\u4ec0\u4e48\u88ab\u8ba4\u4e3a\u662f\u201c\u5f3a\u201d\u76f8\u5173\u6027\uff1f<\/a><\/span><\/p>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4e0d\u4f7f\u7528<strong>unstack<\/strong>\u548c<strong>iloc<\/strong>\u51fd\u6570\u6765\u7f29\u77ed\u8bed\u6cd5\uff0c\u4f46\u7ed3\u679c\u4f1a\u66f4\u96be\u770b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">team<\/span> ')[[' <span style=\"color: #ff0000;\">points<\/span> ',' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">corr<\/span> ()\n\n\t\tassist points\nteam\t\t\t\nA points 1.000000 0.603053\n        assists 0.603053 1.000000\nB points 1.000000 0.981798\n        assists 0.981798 1.000000<\/span>\n<\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8fd9\u79cd\u8bed\u6cd5\u4e3a\u4e24\u4e2a\u56e2\u961f\u751f\u6210\u4e00\u4e2a\u76f8\u5173\u77e9\u9635\uff0c\u4e3a\u6211\u4eec\u63d0\u4f9b\u4e86\u591a\u4f59\u7684\u4fe1\u606f\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u64cd\u4f5c\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/pandas-groupby-\u603b\u548c\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u6267\u884c GroupBy \u6c42\u548c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/pandas-\u6309\u60c5\u8282\u5206\u7ec4\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u4f7f\u7528 Groupby \u548c Plot<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/pandas-groupby-\u8ba1\u6570\u552f\u4e00\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u4f7f\u7528 GroupBy \u8ba1\u7b97\u552f\u4e00\u503c<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5728 pandas \u4e2d\u6309\u7ec4\u8ba1\u7b97\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u6027\uff1a df. groupby (&#8216; gro [&hellip;]<\/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-2662","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u8ba1\u7b97 pandas \u4e2d\u7684\u7ec4\u76f8\u5173\u6027 \u2013 Statorials<\/title>\n<meta name=\"description\" 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