{"id":3272,"date":"2023-07-18T08:56:43","date_gmt":"2023-07-18T08:56:43","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%af%8f%e7%bb%84%e6%9c%80%e5%b0%91%e7%86%8a%e7%8c%ab%e6%95%b0\/"},"modified":"2023-07-18T08:56:43","modified_gmt":"2023-07-18T08:56:43","slug":"%e6%af%8f%e7%bb%84%e6%9c%80%e5%b0%91%e7%86%8a%e7%8c%ab%e6%95%b0","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%af%8f%e7%bb%84%e6%9c%80%e5%b0%91%e7%86%8a%e7%8c%ab%e6%95%b0\/","title":{"rendered":"\u5982\u4f55\u627e\u5230 pandas \u4e2d\u6bcf\u7ec4\u7684\u6700\u5c0f\u503c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u6765\u67e5\u627e pandas DataFrame \u4e2d\u6bcf\u7ec4\u7684\u6700\u5c0f\u503c\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 1\uff1a\u6309\u81f3\u5c11\u4e00\u5217\u5206\u7ec4<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">group_column<\/span> ')[' <span style=\"color: #ff0000;\">values_column<\/span> ']. <span style=\"color: #3366ff;\">min<\/span> ()\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 2\uff1a\u6309\u6700\u5c0f\u503c\u5bf9\u591a\u5217\u8fdb\u884c\u5206\u7ec4<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">group_column<\/span> ')[' <span style=\"color: #ff0000;\">values_column1<\/span> ', ' <span style=\"color: #ff0000;\">values_column2<\/span> ']. <span style=\"color: #3366ff;\">min<\/span> ()<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\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<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd<\/span>\n\n#create pandas DataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'C', 'C'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ':[24, 23, 27, 11, 14, 8, 13],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 7, 6, 6, 5, 12]})\n\n<span style=\"color: #008080;\">#display DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points rebounds\n0 to 24 11\n1 to 23 8\n2 B 27 7\n3 B 11 6\n4 B 14 6\n5 C 8 5\n6 C 13 12<\/strong><\/pre>\n<h2><strong>\u793a\u4f8b 1\uff1a\u6309\u81f3\u5c11\u4e00\u5217\u8fdb\u884c\u5206\u7ec4<\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u67e5\u627e\u6309<strong>\u56e2\u961f<\/strong>\u5217\u5206\u7ec4\u7684<strong>\u5206\u6570<\/strong>\u5217\u7684\u6700\u5c0f\u503c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find minimum value of points, grouped by team<\/span>\ndf. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">team<\/span> ')[' <span style=\"color: #ff0000;\">points<\/span> ']. <span style=\"color: #3366ff;\">min<\/span> () \n\nteam\nAt 23\nB 11\nC 8\nName: points, dtype: int64\n<\/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;\"><span style=\"color: #000000;\">A \u961f\u7684\u6700\u4f4e\u5206\u503c\u662f<strong>23<\/strong> \u3002<\/span><\/span><\/li>\n<li> <span style=\"color: #000000;\">B \u961f\u7684\u6700\u4f4e\u5206\u503c\u662f<strong>11<\/strong> \u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">C \u961f\u7684\u6700\u4f4e\u5206\u503c\u662f<strong>8<\/strong> \u3002<\/span><\/li>\n<\/ul>\n<h2><strong>\u793a\u4f8b 2\uff1a<\/strong><strong>\u6309\u6700\u5c11\u51e0\u5217\u8fdb\u884c\u5206\u7ec4<\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u67e5\u627e\u6309<strong>\u7403\u961f<\/strong>\u5217\u5206\u7ec4\u7684<strong>\u5f97\u5206<\/strong>\u548c<strong>\u7bee\u677f<\/strong>\u5217\u7684\u6700\u5c0f\u503c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find minimum value of points and rebounds, grouped by team<\/span>\ndf. <span style=\"color: #3366ff;\">groupby<\/span> (' <span style=\"color: #ff0000;\">team<\/span> ')[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">min<\/span> () \n\n    rebound points\nteam\t\t\nAt 23 8\nB 11 6\nC 8 5\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\">A\u961f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u5206\u6570\uff1a <strong>23<\/strong><\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u7bee\u677f\u6570\uff1a <strong>8<\/strong><\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4e59\u961f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u5206\u6570\uff1a <strong>11<\/strong><\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u7bee\u677f\u6570\uff1a <strong>6<\/strong><\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">C\u961f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u5206\u6570\uff1a <strong>8<\/strong><\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5c0f\u9000\u56de\u6b21\u6570\uff1a <strong>5<\/strong><\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u6ce8\u610f<\/strong>\uff1a\u6307\u5b9a\u503c\u5217\u65f6\u4f7f\u7528\u53cc\u62ec\u53f7\u975e\u5e38\u91cd\u8981\uff0c\u5426\u5219\u53ef\u80fd\u4f1a\u6536\u5230\u9519\u8bef\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u7684 panda \u4efb\u52a1\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/\u662f\u718a\u732b\u67f1\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u8ba1\u7b97 Pandas \u4e2d\u7684\u5217\u603b\u548c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u5e73\u5747\u718a\u732b\u5217\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u8ba1\u7b97 Pandas \u4e2d\u5217\u7684\u5e73\u5747\u503c<\/a><br \/>\u5982\u4f55\u627e\u5230 Pandas \u4e2d\u5217\u7684\u6700\u5927\u503c<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u6765\u67e5\u627e pandas DataFrame \u4e2d\u6bcf\u7ec4\u7684\u6700\u5c0f\u503c\uff1a \u65b9\u6cd5 1\uff1a\u6309\u81f3\u5c11\u4e00\u5217\u5206\u7ec4 df. 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