{"id":981,"date":"2023-07-28T02:29:34","date_gmt":"2023-07-28T02:29:34","guid":{"rendered":"https:\/\/statorials.org\/ru\/pandas-groupby-%d0%be%d0%b1%d1%8a%d0%b5%d0%b4%d0%b8%d0%bd%d1%8f%d0%b5%d1%82-%d0%bd%d0%b5%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%ba%d0%be-%d1%81%d1%82%d0%be%d0%bb%d0%b1%d1%86%d0%be%d0%b2\/"},"modified":"2023-07-28T02:29:34","modified_gmt":"2023-07-28T02:29:34","slug":"pandas-groupby-%d0%be%d0%b1%d1%8a%d0%b5%d0%b4%d0%b8%d0%bd%d1%8f%d0%b5%d1%82-%d0%bd%d0%b5%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%ba%d0%be-%d1%81%d1%82%d0%be%d0%bb%d0%b1%d1%86%d0%be%d0%b2","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/pandas-groupby-%d0%be%d0%b1%d1%8a%d0%b5%d0%b4%d0%b8%d0%bd%d1%8f%d0%b5%d1%82-%d0%bd%d0%b5%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%ba%d0%be-%d1%81%d1%82%d0%be%d0%bb%d0%b1%d1%86%d0%be%d0%b2\/","title":{"rendered":"Pandas: \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0427\u0430\u0441\u0442\u043e \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 DataFrame pandas.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041a \u0441\u0447\u0430\u0441\u0442\u044c\u044e, \u044d\u0442\u043e \u043b\u0435\u0433\u043a\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 pandas <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.groupby.html\" target=\"_blank\" rel=\"noopener noreferrer\">.groupby()<\/a> \u0438 <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.agg.html\" target=\"_blank\" rel=\"noopener noreferrer\">.agg()<\/a> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u0432 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u044d\u0442\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 1. \u0421\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u0439\u0442\u0435 \u043f\u043e \u0434\u0432\u0443\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0438 \u043d\u0430\u0439\u0434\u0438\u0442\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435.<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'B', 'B', 'B', 'B', 'M', 'M', 'M'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #993300;\">print<\/span> (df)\n\n  team position assists rebounds\n0 AG 5 11\n1 BG 7 8\n2 BF 7 10\n3 BG 8 6\n4 BF 5 6\n5 MF 7 9\n6 MC 6 6\n7 MC 9 10\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u00ab\u043a\u043e\u043c\u0430\u043d\u0434\u0430\u00bb \u0438 \u00ab\u043f\u043e\u0437\u0438\u0446\u0438\u044f\u00bb \u0438 \u043d\u0430\u0445\u043e\u0434\u0438\u0442\u044c \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0435\u0440\u0435\u0434\u0430\u0447:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'assists': ['mean']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n\n        team position assists\n                          mean\n0 A G 5.0\n1 B F 6.0\n2 B G 7.5\n3 M C 7.5\n4M F 7.0\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u044b\u0432\u043e\u0434 \u0433\u043e\u0432\u043e\u0440\u0438\u0442 \u043d\u0430\u043c:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0421\u0440\u0435\u0434\u043d\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0435\u0440\u0435\u0434\u0430\u0447 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 G \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0410 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>5,0<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0421\u0440\u0435\u0434\u043d\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0435\u0440\u0435\u0434\u0430\u0447 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 F \u0432 \u043a\u043e\u043c\u0430\u043d\u0434\u0435 B \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>6,0<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0421\u0440\u0435\u0434\u043d\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0435\u0440\u0435\u0434\u0430\u0447 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 G \u043a\u043e\u043c\u0430\u043d\u0434\u044b B \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>7,5<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0418 \u0442\u0430\u043a \u0434\u0430\u043b\u0435\u0435.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0438\u0440\u0443\u044e\u0449\u0435\u0433\u043e DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#group by team and position and find mean assists<\/span>\nnew = df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'assists': ['mean']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n<span style=\"color: #008080;\">#rename columns<\/span>\nnew.columns = ['team', 'pos', 'mean_assists']\n\n<span style=\"color: #008080;\">#view DataFrame<\/span>\n<span style=\"color: #993300;\">print<\/span> (new)\n\n\tteam pos mean_assists\n0 A G 5.0\n1 B F 6.0\n2 B G 7.5\n3 M C 7.5\n4M F 7.0<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 2. \u0413\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0430 \u043f\u043e \u0434\u0432\u0443\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0438 \u043f\u043e\u0438\u0441\u043a \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0434\u0430\u043d\u043d\u044b\u0445.<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u043c\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c \u0442\u043e\u0442 \u0436\u0435 DataFrame pandas, \u0447\u0442\u043e \u0438 \u0432 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'B', 'B', 'B', 'B', 'M', 'M', 'M'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u043a\u0430\u043a \u043d\u0430\u0439\u0442\u0438 \u043c\u0435\u0434\u0438\u0430\u043d\u043d\u043e\u0435 \u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u043e\u0432, \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u0445 \u00ab\u043a\u043e\u043c\u0430\u043d\u0434\u0430\u00bb \u0438 \u00ab\u043f\u043e\u0437\u0438\u0446\u0438\u044f\u00bb:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'rebounds': ['median', 'max']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n\n        team position rebounds\n                         median max\n0 A G 11 11\n1 B F 8 10\n2 B G 7 8\n3 M C 8 10\n4 M F 9 9\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u044b\u0432\u043e\u0434 \u0433\u043e\u0432\u043e\u0440\u0438\u0442 \u043d\u0430\u043c:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0421\u0440\u0435\u0434\u043d\u0435\u0435 \u0447\u0438\u0441\u043b\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u043e\u0432 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 G \u0432 \u043a\u043e\u043c\u0430\u043d\u0434\u0435 \u0410 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>11<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u043e\u0432 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 G \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0410 \u2014 <strong>11<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0421\u0440\u0435\u0434\u043d\u0435\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u043e\u0432 \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 F \u043a\u043e\u043c\u0430\u043d\u0434\u044b B \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>8<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u043e\u0432 \u0434\u043b\u044f \u0438\u0433\u0440\u043e\u043a\u043e\u0432 \u043d\u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 F \u043a\u043e\u043c\u0430\u043d\u0434\u044b B \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 <strong>10<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0418 \u0442\u0430\u043a \u0434\u0430\u043b\u0435\u0435.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ru\/pandas-\u0444\u0438\u043b\u044c\u0442\u0440\u0443\u0435\u0442-\u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e-\u0443\u0441\u043b\u043e\u0432\u0438\u0438\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u0444\u0438\u043b\u044c\u0442\u0440\u043e\u0432\u0430\u0442\u044c DataFrame Pandas \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0443\u0441\u043b\u043e\u0432\u0438\u044f\u043c<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u043f\u0430\u043d\u0434\u044b-\u043f\u043e\u0434\u0441\u0447\u0438\u0442\u044b\u0432\u0430\u044e\u0442-\u043f\u0440\u043e\u043f\u0443\u0449\u0435\u043d\u043d\u044b\u0435-\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u043f\u043e\u0434\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u043f\u0440\u043e\u043f\u0443\u0449\u0435\u043d\u043d\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0432 DataFrame Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u0442\u0435\u043a-\u0444\u0440\u0435\u0438\u043c\u043e\u0432-\u0434\u0430\u043d\u043d\u044b\u0445-pandas\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0438\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043a\u0430\u0434\u0440\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445 Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0427\u0430\u0441\u0442\u043e \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 DataFrame pandas. \u041a \u0441\u0447\u0430\u0441\u0442\u044c\u044e, \u044d\u0442\u043e \u043b\u0435\u0433\u043a\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 pandas .groupby() \u0438 .agg() . \u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u0432 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u044d\u0442\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439. \u041f\u0440\u0438\u043c\u0435\u0440 1. \u0421\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u0439\u0442\u0435 \u043f\u043e \u0434\u0432\u0443\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0438 \u043d\u0430\u0439\u0434\u0438\u0442\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435. \u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas: import pandas as pd [&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-981","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>Pandas: \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c<\/title>\n<meta name=\"description\" content=\"\u041f\u0440\u043e\u0441\u0442\u043e\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0442\u043e\u0433\u043e, \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 DataFrame pandas, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u043f\u0440\u0438\u043c\u0435\u0440\u044b.\" \/>\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\/ru\/pandas-groupby-\u043e\u0431\u044a\u0435\u0434\u0438\u043d\u044f\u0435\u0442-\u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e-\u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c\" \/>\n<meta property=\"og:description\" content=\"\u041f\u0440\u043e\u0441\u0442\u043e\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0442\u043e\u0433\u043e, \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 DataFrame pandas, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u043f\u0440\u0438\u043c\u0435\u0440\u044b.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ru\/pandas-groupby-\u043e\u0431\u044a\u0435\u0434\u0438\u043d\u044f\u0435\u0442-\u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e-\u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T02:29:34+00:00\" \/>\n<meta name=\"author\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e \u0430\u0432\u0442\u043e\u0440\u043e\u043c\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u043c\u0435\u0440\u043d\u043e\u0435 \u0432\u0440\u0435\u043c\u044f \u0434\u043b\u044f \u0447\u0442\u0435\u043d\u0438\u044f\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u043c\u0438\u043d\u0443\u0442\u0430\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ru\/pandas-groupby-%d0%be%d0%b1%d1%8a%d0%b5%d0%b4%d0%b8%d0%bd%d1%8f%d0%b5%d1%82-%d0%bd%d0%b5%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%ba%d0%be-%d1%81%d1%82%d0%be%d0%bb%d0%b1%d1%86%d0%be%d0%b2\/\",\"url\":\"https:\/\/statorials.org\/ru\/pandas-groupby-%d0%be%d0%b1%d1%8a%d0%b5%d0%b4%d0%b8%d0%bd%d1%8f%d0%b5%d1%82-%d0%bd%d0%b5%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%ba%d0%be-%d1%81%d1%82%d0%be%d0%bb%d0%b1%d1%86%d0%be%d0%b2\/\",\"name\":\"Pandas: \u043a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0438 \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c 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