{"id":4232,"date":"2023-07-12T15:37:29","date_gmt":"2023-07-12T15:37:29","guid":{"rendered":"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/"},"modified":"2023-07-12T15:37:29","modified_gmt":"2023-07-12T15:37:29","slug":"pandas-group-by-resample","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/","title":{"rendered":"Pandas: \u044f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e groupby()"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u041f\u043e\u0432\u0442\u043e\u0440\u043d\u0430 \u0432\u0438\u0431\u0456\u0440\u043a\u0430<\/strong> \u0434\u0430\u043d\u0438\u0445 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u043e\u0437\u043d\u0430\u0447\u0430\u0454 \u0430\u0433\u0440\u0435\u0433\u0443\u0432\u0430\u043d\u043d\u044f \u0434\u0430\u043d\u0438\u0445 \u0437\u0430 \u043d\u043e\u0432\u0438\u0439 \u043f\u0435\u0440\u0456\u043e\u0434.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u042f\u043a\u0449\u043e \u0432\u0438 \u0445\u043e\u0447\u0435\u0442\u0435 \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0443 pandas \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440\u0430 <strong>groupby<\/strong> , \u0432\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>group = df. <span style=\"color: #3366ff;\">groupby<\/span> ([pd. <span style=\"color: #3366ff;\">Group<\/span> (freq=' <span style=\"color: #ff0000;\">W<\/span> '), ' <span style=\"color: #ff0000;\">store<\/span> '])\n\nresult = group[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">unstack<\/span> (' <span style=\"color: #ff0000;\">store<\/span> '). <span style=\"color: #3366ff;\">fillna<\/span> (0) \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0423 \u0446\u044c\u043e\u043c\u0443 \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u0433\u0440\u0443\u043f\u0443\u044e\u0442\u044c\u0441\u044f \u0440\u044f\u0434\u043a\u0438 DataFrame \u0437\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0435\u043c <strong>\u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0443<\/strong> , \u043f\u043e\u0442\u0456\u043c \u043f\u043e\u0432\u0442\u043e\u0440\u044e\u0454\u0442\u044c\u0441\u044f \u0432\u0438\u0431\u0456\u0440\u043a\u0430 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0437\u0430 \u0442\u0438\u0436\u043d\u044f\u043c\u0438 ( <strong>freq=&#8217;W&#8217;<\/strong> ), \u0430 \u043f\u043e\u0442\u0456\u043c \u043e\u0431\u0447\u0438\u0441\u043b\u044e\u0454\u0442\u044c\u0441\u044f \u0441\u0443\u043c\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 <strong>\u043f\u0440\u043e\u0434\u0430\u0436\u0456\u0432<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u043f\u043e\u0432\u0442\u043e\u0440\u044e\u0432\u0430\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0434\u0430\u043d\u0438\u0445 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0434\u043b\u044f \u0440\u0456\u0437\u043d\u0438\u0445 \u043f\u0435\u0440\u0456\u043e\u0434\u0456\u0432 \u0447\u0430\u0441\u0443, \u0437\u043e\u043a\u0440\u0435\u043c\u0430:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>S<\/strong> : \u0421\u0435\u043a\u0443\u043d\u0434\u0438<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>min<\/strong> : \u0445\u0432\u0438\u043b\u0438\u043d\u0438<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>H<\/strong> : \u0433\u043e\u0434\u0438\u043d\u0438<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u0414\u0436<\/strong> : \u0414\u0435\u043d\u044c<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>W<\/strong> : \u0422\u0438\u0436\u0434\u0435\u043d\u044c<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u041c<\/strong> : \u041c\u0456\u0441\u044f\u0446\u044c<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u041f<\/strong> : \u0427\u0432\u0435\u0440\u0442\u044c<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>A<\/strong> : \u0420\u0456\u043a<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0432\u0435\u0434\u0435\u043d\u043e\u043c\u0443 \u043d\u0438\u0436\u0447\u0435 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u044f\u043a \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456 \u043f\u043e\u0432\u0442\u043e\u0440\u0438\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0434\u0430\u043d\u0438\u0445 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 <strong>groupby<\/strong> .<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434: \u043f\u0435\u0440\u0435\u0432\u0438\u0431\u0456\u0440\u043a\u0430 \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Groupby \u0432 Pandas<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 Frame DataFrame pandas, \u044f\u043a\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0456 \u043f\u0440\u043e\u0434\u0430\u0436\u0456 \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0434\u043d\u044f \u0432 \u0434\u0432\u043e\u0445 \u0440\u0456\u0437\u043d\u0438\u0445 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0430\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <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;\">sales<\/span> ': [13, 14, 17, 17, 16, 22, 28, 10, 17, 10, 11],\n                   ' <span style=\"color: #ff0000;\">store<\/span> ': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B', 'B']} ,\n                   index=pd. <span style=\"color: #3366ff;\">date_range<\/span> ('2023-01-06', '2023-01-16', freq='d'))\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n            sales store\n2023-01-06 13 A\n2023-01-07 14 A\n2023-01-08 17 A\n2023-01-09 17 A\n2023-01-10 16A\n2023-01-11 22 B\n2023-01-12 28 B\n2023-01-13 10 B\n2023-01-14 17 B\n2023-01-15 10 B\n2023-01-16 11 B<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u043c\u0438 \u0445\u043e\u0447\u0435\u043c\u043e \u0437\u0433\u0440\u0443\u043f\u0443\u0432\u0430\u0442\u0438 \u0440\u044f\u0434\u043a\u0438 \u0437\u0430 <strong>\u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0430\u043c\u0438<\/strong> , \u043f\u043e\u0442\u0456\u043c \u043f\u043e\u0432\u0442\u043e\u0440\u0438\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0437\u0430 \u0442\u0438\u0436\u043d\u044f\u043c\u0438, \u0430 \u043f\u043e\u0442\u0456\u043c \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 \u0441\u0443\u043c\u0443 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 <strong>\u043f\u0440\u043e\u0434\u0430\u0436\u0456\u0432<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0414\u043b\u044f \u0446\u044c\u043e\u0433\u043e \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#group by store and resample time series by week<\/span>\ngroup = df. <span style=\"color: #3366ff;\">groupby<\/span> ([pd. <span style=\"color: #3366ff;\">Group<\/span> (freq=' <span style=\"color: #ff0000;\">W<\/span> '), ' <span style=\"color: #ff0000;\">store<\/span> '])\n\n<span style=\"color: #008080;\">#calculate sum of sales each week by store\n<\/span>result = group[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">unstack<\/span> (' <span style=\"color: #ff0000;\">store<\/span> '). <span style=\"color: #3366ff;\">fillna<\/span> (0)\n\n<span style=\"color: #008080;\">#view results<\/span>\n<span style=\"color: #008000;\">print<\/span> (result)\n\nstore AB\n2023-01-08 14.0 0.0\n2023-01-15 16.5 17.0\n2023-01-22 0.0 11.0\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0417 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0443 \u043c\u0438 \u0431\u0430\u0447\u0438\u043c\u043e:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0421\u0443\u043c\u0430 \u043f\u0440\u043e\u0434\u0430\u0436\u0456\u0432 \u0437\u0430 \u0442\u0438\u0436\u0434\u0435\u043d\u044c, \u0449\u043e \u0437\u0430\u043a\u0456\u043d\u0447\u0438\u0432\u0441\u044f 01\/08\/2023 \u0443 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0456 \u0410, \u0434\u043e\u0440\u0456\u0432\u043d\u044e\u0454 <strong>14<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0421\u0443\u043c\u0430 \u043f\u0440\u043e\u0434\u0430\u0436\u0456\u0432 \u0437\u0430 \u0442\u0438\u0436\u0434\u0435\u043d\u044c, \u0449\u043e \u0437\u0430\u043a\u0456\u043d\u0447\u0438\u0432\u0441\u044f 01\/08\/2023 \u0443 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0456 B, \u0434\u043e\u0440\u0456\u0432\u043d\u044e\u0454 <strong>0<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0406 \u0442\u0430\u043a \u0434\u0430\u043b\u0456.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0417\u0432\u0435\u0440\u043d\u0456\u0442\u044c \u0443\u0432\u0430\u0433\u0443, \u0449\u043e \u0432 \u0446\u044c\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043c\u0438 \u0432\u0438\u0440\u0456\u0448\u0438\u043b\u0438 \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 \u0441\u0443\u043c\u0443 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 <strong>\u043f\u0440\u043e\u0434\u0430\u0436\u0456\u0432<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0434\u043d\u0430\u043a \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u043f\u043e\u043a\u0430\u0437\u043d\u0438\u043a\u0438, \u0442\u0430\u043a\u0456 \u044f\u043a \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c, \u0441\u0435\u0440\u0435\u0434\u043d\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f, \u043c\u0435\u0434\u0456\u0430\u043d\u0430, \u043c\u0456\u043d\u0456\u043c\u0430\u043b\u044c\u043d\u0438\u0439, \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u0438\u0439 \u0442\u043e\u0449\u043e.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u043e\u0441\u0442\u043e \u0437\u0430\u043c\u0456\u043d\u0456\u0442\u044c <strong>sum()<\/strong> \u0443 \u043a\u043e\u0434\u0456 \u0432\u0438\u0449\u0435 \u043d\u0430 <strong>count()<\/strong> , <strong>Mean()<\/strong> , <strong>Median()<\/strong> \u0442\u043e\u0449\u043e. \u0449\u043e\u0431 \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 \u043c\u0435\u0442\u0440\u0438\u043a\u0443 \u0437\u0430 \u0432\u0430\u0448\u0438\u043c \u0432\u0438\u0431\u043e\u0440\u043e\u043c.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0430\u0445 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u0442\u0438\u043f\u043e\u0432\u0456 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 \u0432 Python:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/uk\/\u0447\u0430\u0441\u043e\u0432\u0438\u0438-\u0440\u044f\u0434-matplotlib\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0443 Matplotlib<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043c\u043e\u0440\u0441\u044c\u043a\u0430-\u0448\u043a\u0430\u043b\u0430-\u0447\u0430\u0441\u0443\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043f\u043e\u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0443 Seaborn<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043a\u0430\u0440\u0442\u0430-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0440\u043e\u0437\u0440\u0430\u0445\u0443\u0432\u0430\u0442\u0438 MAPE \u0437\u0430 \u0447\u0430\u0441\u043e\u0432\u0438\u043c\u0438 \u0440\u044f\u0434\u0430\u043c\u0438 \u0432 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u041f\u043e\u0432\u0442\u043e\u0440\u043d\u0430 \u0432\u0438\u0431\u0456\u0440\u043a\u0430 \u0434\u0430\u043d\u0438\u0445 \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u043e\u0437\u043d\u0430\u0447\u0430\u0454 \u0430\u0433\u0440\u0435\u0433\u0443\u0432\u0430\u043d\u043d\u044f \u0434\u0430\u043d\u0438\u0445 \u0437\u0430 \u043d\u043e\u0432\u0438\u0439 \u043f\u0435\u0440\u0456\u043e\u0434. \u042f\u043a\u0449\u043e \u0432\u0438 \u0445\u043e\u0447\u0435\u0442\u0435 \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0443 pandas \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043e\u043f\u0435\u0440\u0430\u0442\u043e\u0440\u0430 groupby , \u0432\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441: group = df. groupby ([pd. Group (freq=&#8217; W &#8216;), &#8216; store &#8216;]) result = group[&#8216; sales &#8216;]. sum (). unstack (&#8216; store &#8216;). fillna (0) [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas: \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e groupby() \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 \u0432 pandas \u043f\u0456\u0434 \u0447\u0430\u0441 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 groupby, \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0447\u0438 \u043f\u0440\u0438\u043a\u043b\u0430\u0434.\" \/>\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\/uk\/pandas-group-by-resample\/\" \/>\n<meta property=\"og:locale\" content=\"uk_UA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e groupby() \u2013 Statorials\" \/>\n<meta property=\"og:description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 \u0432 pandas \u043f\u0456\u0434 \u0447\u0430\u0441 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 groupby, \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0447\u0438 \u043f\u0440\u0438\u043a\u043b\u0430\u0434.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-12T15:37:29+00:00\" \/>\n<meta name=\"author\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u0431\u043b. \u0447\u0430\u0441 \u0447\u0438\u0442\u0430\u043d\u043d\u044f\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u0445\u0432\u0438\u043b\u0438\u043d\u0430\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/\",\"url\":\"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/\",\"name\":\"Pandas: \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e groupby() \u2013 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\u043f\u0440\u0438\u043a\u043b\u0430\u0434.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/uk\/pandas-group-by-resample\/","og_locale":"uk_UA","og_type":"article","og_title":"Pandas: \u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e groupby() \u2013 Statorials","og_description":"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0432\u0438\u0431\u0456\u0440\u043a\u0443 \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 \u0432 pandas \u043f\u0456\u0434 \u0447\u0430\u0441 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f 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