{"id":978,"date":"2023-07-28T02:45:23","date_gmt":"2023-07-28T02:45:23","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d1%81%d0%be%d1%80%d1%82%d0%b8%d1%80%d1%83%d1%8e%d1%82-%d0%bf%d0%be-%d0%b4%d0%b0%d1%82%d0%b5\/"},"modified":"2023-07-28T02:45:23","modified_gmt":"2023-07-28T02:45:23","slug":"%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d1%81%d0%be%d1%80%d1%82%d0%b8%d1%80%d1%83%d1%8e%d1%82-%d0%bf%d0%be-%d0%b4%d0%b0%d1%82%d0%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%bf%d0%b0%d0%bd%d0%b4%d1%8b-%d1%81%d0%be%d1%80%d1%82%d0%b8%d1%80%d1%83%d1%8e%d1%82-%d0%bf%d0%be-%d0%b4%d0%b0%d1%82%d0%b5\/","title":{"rendered":"\u041a\u0430\u043a \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445 pandas \u043f\u043e \u0434\u0430\u0442\u0435 (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438)"},"content":{"rendered":"

<\/p>\n

\n

\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 \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c DataFrame pandas \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u0430, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0435\u0433\u043e \u0434\u0430\u0442\u044b. \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\u0438 sort_values()<\/strong><\/a> .<\/span><\/p>\n

\u0412 \u044d\u0442\u043e\u043c \u0443\u0440\u043e\u043a\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e \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\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438.<\/span><\/p>\n

\u041f\u0440\u0438\u043c\u0435\u0440 1. \u0421\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u043f\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0443 \u0434\u0430\u0442\u044b<\/strong><\/span><\/h3>\n

\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

 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd.DataFrame({'sales': [4, 11, 13, 9],\n                   'customers': [2, 6, 9, 7],\n                   'date': ['2020-01-25', '2020-01-18', '2020-01-22', '2020-01-21']})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   sales customers date\n0 4 2 2020-01-25\n1 11 6 2020-01-18\n2 13 9 2020-01-22\n3 9 7 2020-01-21\n<\/strong><\/pre>\n
 \u0412\u043e-\u043f\u0435\u0440\u0432\u044b\u0445, \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e to_datetime()<\/strong> \u0434\u043b\u044f \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u0430 date \u0432 \u043e\u0431\u044a\u0435\u043a\u0442 datetime:<\/span><\/p>\n
 df[' date<\/span> '] = pd. to_datetime<\/span> (df[' date<\/span> '])\n<\/strong><\/pre>\n
 \u0414\u0430\u043b\u0435\u0435 \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c DataFrame \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u00ab\u0434\u0430\u0442\u0430\u00bb, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u044e sort_values()<\/strong> :<\/span><\/p>\n
 df. sort_values<\/span> (by=' date<\/span> ')\n\n        sales customers date\n1 11 6 2020-01-18\n3 9 7 2020-01-21\n2 13 9 2020-01-22\n0 4 2 2020-01-25\n<\/strong><\/pre>\n
 \u041f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u044d\u0442\u0430 \u0444\u0443\u043d\u043a\u0446\u0438\u044f \u0441\u043e\u0440\u0442\u0438\u0440\u0443\u0435\u0442 \u0434\u0430\u0442\u044b \u0432 \u043f\u043e\u0440\u044f\u0434\u043a\u0435 \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u0430\u043d\u0438\u044f. \u041e\u0434\u043d\u0430\u043a\u043e \u0432\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0443\u043a\u0430\u0437\u0430\u0442\u044c \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u0430\u043d\u0438\u0435=False<\/strong> \u0434\u043b\u044f \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0438 \u0432 \u043f\u043e\u0440\u044f\u0434\u043a\u0435 \u0443\u0431\u044b\u0432\u0430\u043d\u0438\u044f:<\/span><\/p>\n
 df. sort_values<\/span> (by=' date<\/span> ', ascending= False<\/span> )\n\n\tsales customers date\n0 4 2 2020-01-25\n2 13 9 2020-01-22\n3 9 7 2020-01-21\n1 11 6 2020-01-18<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043c\u0435\u0440 2: \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0434\u0430\u0442<\/strong><\/span><\/h3>\n
 \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
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd.DataFrame({'person': ['A', 'B', 'C', 'D'],\n                   'order_date': ['2020-01-15', '2020-01-15', '2020-01-20', '2020-01-20'],\n                   'receive_date': ['2020-01-25', '2020-01-18', '2020-01-22', '2020-01-21']})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  person order_date receive_date\n0 A 2020-01-15 2020-01-25\n1 B 2020-01-15 2020-01-18\n2 C 2020-01-20 2020-01-22\n3 D 2020-01-20 2020-01-21<\/strong><\/pre>\n
 \u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e sort_values<\/strong> \u0434\u043b\u044f \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0438 DataFrame \u043f\u043e \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c, \u043f\u0440\u043e\u0441\u0442\u043e \u0443\u043a\u0430\u0437\u0430\u0432 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0438\u043c\u0435\u043d \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432:<\/span><\/p>\n
 #convert both date columns to datetime objects<\/span>\ndf[['order_date','receive_date']] = df[['order_date','receive_date']]. apply<\/span> (pd. to_datetime<\/span> )\n\n#sort DateFrame by order_date, then by receive_date\n<\/span>df. sort_values<\/span> (by=['order_date', 'receive_date'])\n\n        person order_date receive_date\n1 B 2020-01-15 2020-01-18\n0 A 2020-01-15 2020-01-25\n3 D 2020-01-20 2020-01-21\n2 C 2020-01-20 2020-01-22<\/strong><\/pre>\n
 DataFrame \u0442\u0435\u043f\u0435\u0440\u044c \u0441\u043e\u0440\u0442\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u043f\u043e\u0440\u044f\u0434\u043a\u0435 \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u0430\u043d\u0438\u044f \u043f\u043e \u0434\u0430\u0442\u0435 \u0437\u0430\u043a\u0430\u0437\u0430, \u0430 \u0437\u0430\u0442\u0435\u043c \u0432 \u043f\u043e\u0440\u044f\u0434\u043a\u0435 \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u0430\u043d\u0438\u044f \u043f\u043e \u0434\u0430\u0442\u0435 \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044f.<\/span><\/p>\n
 \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
 \u041a\u0430\u043a \u0444\u0438\u043b\u044c\u0442\u0440\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u0440\u043e\u043a\u0438 Pandas DataFrame \u043f\u043e \u0434\u0430\u0442\u0435
 \u041a\u0430\u043a \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u044c DateTime \u0432 \u0434\u0430\u0442\u0443 \u0432 Pandas<\/a>
 \u041a\u0430\u043a \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u0432 DateTime \u0432 Pandas<\/a>
 \u041a\u0430\u043a \u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043f\u043e \u0438\u043d\u0434\u0435\u043a\u0441\u0443 \u0438 \u0441\u0442\u043e\u043b\u0431\u0446\u0443 \u0432 Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\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 \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c DataFrame pandas \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u0430, \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0449\u0435\u0433\u043e \u0434\u0430\u0442\u044b. \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\u0438 sort_values() . \u0412 \u044d\u0442\u043e\u043c \u0443\u0440\u043e\u043a\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e \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\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438. \u041f\u0440\u0438\u043c\u0435\u0440 1. \u0421\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u043a\u0430 \u043f\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0443 \u0434\u0430\u0442\u044b \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 #createDataFrame df = pd.DataFrame({‘sales’: [4, 11, […]<\/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-978","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u041a\u0430\u043a \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445 Pandas \u043f\u043e \u0434\u0430\u0442\u0435 (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438)<\/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 \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u0431\u0435\u0446 DataFrame pandas \u043f\u043e \u0434\u0430\u0442\u0435, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u0432.\" \/>\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\/\u043f\u0430\u043d\u0434\u044b-\u0441\u043e\u0440\u0442\u0438\u0440\u0443\u044e\u0442-\u043f\u043e-\u0434\u0430\u0442\u0435\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445 Pandas \u043f\u043e \u0434\u0430\u0442\u0435 (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438)\" \/>\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 \u043e\u0442\u0441\u043e\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u0431\u0435\u0446 DataFrame pandas \u043f\u043e \u0434\u0430\u0442\u0435, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u0432.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ru\/\u043f\u0430\u043d\u0434\u044b-\u0441\u043e\u0440\u0442\u0438\u0440\u0443\u044e\u0442-\u043f\u043e-\u0434\u0430\u0442\u0435\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T02:45:23+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\" 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