{"id":3251,"date":"2023-07-18T11:09:02","date_gmt":"2023-07-18T11:09:02","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d0%b0-%d0%bf%d0%b0%d0%bd%d0%b4-%d0%bd%d0%b0-%d0%bd%d0%b5%d0%b4%d0%b5%d0%bb%d1%8e\/"},"modified":"2023-07-18T11:09:02","modified_gmt":"2023-07-18T11:09:02","slug":"%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d0%b0-%d0%bf%d0%b0%d0%bd%d0%b4-%d0%bd%d0%b0-%d0%bd%d0%b5%d0%b4%d0%b5%d0%bb%d1%8e","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%b3%d1%80%d1%83%d0%bf%d0%bf%d0%b0-%d0%bf%d0%b0%d0%bd%d0%b4-%d0%bd%d0%b0-%d0%bd%d0%b5%d0%b4%d0%b5%d0%bb%d1%8e\/","title":{"rendered":"\u041a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 pandas dataframe (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u0441\u0442\u0440\u043e\u043a \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 DataFrame pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert date column to datetime and subtract one week<\/span>\ndf[' <span style=\"color: #ff0000;\">date<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">date<\/span> ']) - pd. <span style=\"color: #3366ff;\">to_timedelta<\/span> (7, unit=' <span style=\"color: #ff0000;\">d<\/span> ')\n\n<span style=\"color: #008080;\">#calculate sum of values, grouped by week\n<\/span>df. <span style=\"color: #3366ff;\">groupby<\/span> ([pd. <span style=\"color: #3366ff;\">Group<\/span> (key=' <span style=\"color: #ff0000;\">date<\/span> ', freq=' <span style=\"color: #ff0000;\">W<\/span> ')])[' <span style=\"color: #ff0000;\">values<\/span> ']. <span style=\"color: #3366ff;\">sum<\/span> ()\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u042d\u0442\u0430 \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u0430\u044f \u0444\u043e\u0440\u043c\u0443\u043b\u0430 \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u0435\u0442 \u0441\u0442\u0440\u043e\u043a\u0438 \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 <strong>\u0434\u0430\u0442\u044b<\/strong> \u0438 \u0432\u044b\u0447\u0438\u0441\u043b\u044f\u0435\u0442 \u0441\u0443\u043c\u043c\u0443 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u0430 <strong>\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439<\/strong> \u0432 DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u043e\u0442 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440: \u041a\u0430\u043a \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 Pandas<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u0414\u043e\u043f\u0443\u0441\u0442\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u043f\u0440\u043e\u0434\u0430\u0436\u0438 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0438 \u0432 \u0440\u0430\u0437\u043d\u044b\u0435 \u0434\u0430\u0442\u044b:<\/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<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">date<\/span> ': pd. <span style=\"color: #3366ff;\">date_range<\/span> (start='1\/5\/2022', freq='D', periods=15),\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [6, 8, 9, 5, 4, 8, 8, 3, 5, 9, 8, 3, 4, 7, 7]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<span style=\"color: #008000;\">print<\/span><\/span> (df)\n\n         dirty date\n0 2022-01-05 6\n1 2022-01-06 8\n2 2022-01-07 9\n3 2022-01-08 5\n4 2022-01-09 4\n5 2022-01-10 8\n6 2022-01-11 8\n7 2022-01-12 3\n8 2022-01-13 5\n9 2022-01-14 9\n10 2022-01-15 8\n11 2022-01-16 3\n12 2022-01-17 4\n13 2022-01-18 7\n14 2022-01-19 7\n<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0439:<\/strong> <a href=\"https:\/\/statorials.org\/ru\/\u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d-\u0434\u0430\u0442-\u043f\u0430\u043d\u0434\u044b\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u0434\u0438\u0430\u043f\u0430\u0437\u043e\u043d \u0434\u0430\u0442 \u0432 Pandas<\/a><\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u044b \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 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0440\u0430\u0441\u0447\u0435\u0442\u0430 \u0441\u0443\u043c\u043c\u044b \u043f\u0440\u043e\u0434\u0430\u0436, \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert date column to datetime and subtract one week<\/span>\ndf[' <span style=\"color: #ff0000;\">date<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">date<\/span> ']) - pd. <span style=\"color: #3366ff;\">to_timedelta<\/span> (7, unit=' <span style=\"color: #ff0000;\">d<\/span> ')\n\n<span style=\"color: #008080;\">#calculate sum of values, grouped by week\n<\/span>df. <span style=\"color: #3366ff;\">groupby<\/span> ([pd. <span style=\"color: #3366ff;\">Group<\/span> (key=' <span style=\"color: #ff0000;\">date<\/span> ', freq=' <span style=\"color: #ff0000;\">W<\/span> ')])[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">sum<\/span> ()\n\ndate\n2022-01-02 32\n2022-01-09 44\n2022-01-16 18\nFreq: W-SUN, Name: sales, dtype: int64\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u043e\u0442 \u043a\u0430\u043a \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0412\u0441\u0435\u0433\u043e \u0437\u0430 \u043d\u0435\u0434\u0435\u043b\u044e, \u043d\u0430\u0447\u0438\u043d\u0430\u044e\u0449\u0443\u044e\u0441\u044f \u043d\u0430 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0434\u0435\u043d\u044c \u043f\u043e\u0441\u043b\u0435 02.01.2022, \u0431\u044b\u043b\u043e \u0441\u043e\u0432\u0435\u0440\u0448\u0435\u043d\u043e <b>32<\/b> \u043f\u0440\u043e\u0434\u0430\u0436\u0438.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0412\u0441\u0435\u0433\u043e \u0437\u0430 \u043d\u0435\u0434\u0435\u043b\u044e, \u043d\u0430\u0447\u0438\u043d\u0430\u044e\u0449\u0443\u044e\u0441\u044f \u043d\u0430 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0434\u0435\u043d\u044c \u043f\u043e\u0441\u043b\u0435 09.01.2022, \u0431\u044b\u043b\u043e <b>44<\/b> \u043f\u0440\u043e\u0434\u0430\u0436\u0438.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0412\u0441\u0435\u0433\u043e \u0437\u0430 \u043d\u0435\u0434\u0435\u043b\u044e, \u043d\u0430\u0447\u0438\u043d\u0430\u044f \u0441\u043e \u0434\u043d\u044f \u043f\u043e\u0441\u043b\u0435 16.01.2022, \u0431\u044b\u043b\u043e \u0441\u043e\u0432\u0435\u0440\u0448\u0435\u043d\u043e <b>18<\/b> \u043f\u0440\u043e\u0434\u0430\u0436.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u0435\u0442 \u043e\u0442\u043c\u0435\u0442\u0438\u0442\u044c, \u0447\u0442\u043e \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u043f\u0430\u043d\u0434\u044b \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u0430\u0433\u0430\u044e\u0442, \u0447\u0442\u043e \u043d\u0435\u0434\u0435\u043b\u044f \u043d\u0430\u0447\u0438\u043d\u0430\u0435\u0442\u0441\u044f \u043d\u0430 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0434\u0435\u043d\u044c \u043f\u043e\u0441\u043b\u0435 \u0432\u043e\u0441\u043a\u0440\u0435\u0441\u0435\u043d\u044c\u044f ( <strong>W-SUN<\/strong> ).<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0434\u043d\u0430\u043a\u043e, \u0441\u043e\u0433\u043b\u0430\u0441\u043d\u043e <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/user_guide\/timeseries.html\" target=\"_blank\" rel=\"noopener\">\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438<\/a> , \u0432\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0437\u043c\u0435\u043d\u0438\u0442\u044c \u044d\u0442\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 <strong>Freq<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0443\u043a\u0430\u0437\u0430\u0442\u044c <strong>Freq=W-MON,<\/strong> \u0435\u0441\u043b\u0438 \u0445\u043e\u0442\u0438\u0442\u0435, \u0447\u0442\u043e\u0431\u044b \u043a\u0430\u0436\u0434\u0430\u044f \u043d\u0435\u0434\u0435\u043b\u044f \u043d\u0430\u0447\u0438\u043d\u0430\u043b\u0430\u0441\u044c \u043d\u0430 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0434\u0435\u043d\u044c \u043f\u043e\u0441\u043b\u0435 \u043f\u043e\u043d\u0435\u0434\u0435\u043b\u044c\u043d\u0438\u043a\u0430 (\u0442. \u0435. \u0432\u0442\u043e\u0440\u043d\u0438\u043a\u0430).<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0430\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0440\u0430\u0441\u0447\u0435\u0442\u0430 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u043f\u0440\u043e\u0434\u0430\u0436, \u0441\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert date column to datetime and subtract one week<\/span>\ndf[' <span style=\"color: #ff0000;\">date<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">date<\/span> ']) - pd. <span style=\"color: #3366ff;\">to_timedelta<\/span> (7, unit=' <span style=\"color: #ff0000;\">d<\/span> ')\n\n<span style=\"color: #008080;\">#calculate max of values, grouped by week\n<\/span>df. <span style=\"color: #3366ff;\">groupby<\/span> ([pd. <span style=\"color: #3366ff;\">Group<\/span> (key=' <span style=\"color: #ff0000;\">date<\/span> ', freq=' <span style=\"color: #ff0000;\">W<\/span> ')])[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">max<\/span> ()\n\ndate\n2022-01-02 9\n2022-01-09 9\n2022-01-16 7\nFreq: W-SUN, Name: sales, dtype: int64\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u043e\u0442 \u043a\u0430\u043a \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0439 \u043e\u0431\u044a\u0435\u043c \u043f\u0440\u043e\u0434\u0430\u0436 \u0437\u0430 \u0434\u0435\u043d\u044c \u0432 \u0442\u0435\u0447\u0435\u043d\u0438\u0435 \u043d\u0435\u0434\u0435\u043b\u0438, \u043d\u0430\u0447\u0438\u043d\u0430\u044e\u0449\u0435\u0439\u0441\u044f \u043f\u043e\u0441\u043b\u0435 02.01.2022, \u0441\u043e\u0441\u0442\u0430\u0432\u0438\u043b <strong>9<\/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\u0440\u043e\u0434\u0430\u0436 \u0432 \u0434\u0435\u043d\u044c \u0432 \u0442\u0435\u0447\u0435\u043d\u0438\u0435 \u043d\u0435\u0434\u0435\u043b\u0438, \u043d\u0430\u0447\u0438\u043d\u0430\u044e\u0449\u0435\u0439\u0441\u044f \u0441\u043e \u0434\u043d\u044f \u043f\u043e\u0441\u043b\u0435 09.01.2022, \u0441\u043e\u0441\u0442\u0430\u0432\u0438\u043b\u043e <strong>9<\/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\u0440\u043e\u0434\u0430\u0436 \u0432 \u0434\u0435\u043d\u044c \u0432 \u0442\u0435\u0447\u0435\u043d\u0438\u0435 \u043d\u0435\u0434\u0435\u043b\u0438, \u043d\u0430\u0447\u0438\u043d\u0430\u044e\u0449\u0435\u0439\u0441\u044f \u043f\u043e\u0441\u043b\u0435 16.01.2022, \u0441\u043e\u0441\u0442\u0430\u0432\u0438\u043b\u043e <strong>7<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435<\/strong> . \u041f\u043e\u043b\u043d\u0443\u044e \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044e \u043f\u043e \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0438 <strong>groupby<\/strong> \u0432 pandas \u043c\u043e\u0436\u043d\u043e \u043d\u0430\u0439\u0442\u0438 <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.groupby.html\" target=\"_blank\" rel=\"noopener\">\u0437\u0434\u0435\u0441\u044c<\/a> .<\/span><\/p>\n<h2> <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><\/h2>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u0434\u0440\u0443\u0433\u0438\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0438 \u0432 pandas:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u0433\u0440\u0443\u043f\u043f\u0430-\u043f\u0430\u043d\u0434-\u0432-\u043c\u0435\u0441\u044f\u0446\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043c\u0435\u0441\u044f\u0446\u0430\u043c \u0432 Pandas DataFrame<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0433\u0440\u0443\u043f\u043f\u0430-\u043f\u0430\u043d\u0434-\u0432-\u0434\u0435\u043d\u044c\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u0434\u043d\u044f\u043c \u0432 Pandas DataFrame<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/pandas-\u0433\u0440\u0443\u043f\u043f\u0438\u0440\u0443\u0435\u0442-\u043f\u043e-\u043f\u043e\u0434\u0441\u0447\u0435\u0442\u0443-\u0441-\u0443\u0441\u043b\u043e\u0432\u0438\u0435\u043c\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c Groupby \u0438 \u0443\u0441\u043b\u043e\u0432\u043d\u043e \u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0432 Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u043a\u0438 \u0441\u0442\u0440\u043e\u043a \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 DataFrame pandas: #convert date column to datetime and subtract one week df[&#8216; date &#8216;] = pd. to_datetime (df[&#8216; date &#8216;]) &#8212; pd. to_timedelta (7, unit=&#8217; d &#8216;) #calculate sum of values, grouped by week df. groupby ([pd. Group (key=&#8217; date &#8216;, freq=&#8217; W [&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-3251","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>\u041a\u0430\u043a \u0433\u0440\u0443\u043f\u043f\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u043d\u0435\u0434\u0435\u043b\u044f\u043c \u0432 Pandas DataFrame (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c) - Statorials<\/title>\n<meta name=\"description\" content=\"\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, \u043a\u0430\u043a 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