{"id":2044,"date":"2023-07-23T22:48:45","date_gmt":"2023-07-23T22:48:45","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b0%d0%b1%d0%be\/"},"modified":"2023-07-23T22:48:45","modified_gmt":"2023-07-23T22:48:45","slug":"%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b0%d0%b1%d0%be","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b0%d0%b1%d0%be\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e where() \u0443 pandas (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438)"},"content":{"rendered":"

<\/p>\n

\n

\u0424\u0443\u043d\u043a\u0446\u0456\u044e Where()<\/strong> \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u0430\u043c\u0456\u043d\u0438 \u043f\u0435\u0432\u043d\u0438\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 pandas DataFrame.<\/span><\/p>\n

\u0426\u044f \u0444\u0443\u043d\u043a\u0446\u0456\u044f \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441:<\/span><\/p>\n

 df. where<\/span> (cond, other=nan)\n<\/strong><\/pre>\n
 \u0414\u043b\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 pandas DataFrame, \u0434\u0435 cond<\/strong> \u043c\u0430\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f True, \u0437\u0431\u0435\u0440\u0456\u0433\u0430\u0454\u0442\u044c\u0441\u044f \u0432\u0438\u0445\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f.<\/span><\/p>\n
 \u0414\u043b\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f, \u0434\u0435 cond<\/strong> \u043c\u0430\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f False, \u0432\u0438\u0445\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0437\u0430\u043c\u0456\u043d\u044e\u0454\u0442\u044c\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f\u043c, \u0443\u043a\u0430\u0437\u0430\u043d\u0438\u043c \u0456\u043d\u0448\u0438\u043c<\/strong> \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u043e\u043c.<\/span><\/p>\n
 \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u0435\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456 \u0437 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u043c\u0438 pandas DataFrame:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#define DataFrame\ndf = pd. DataFrame<\/span> ({' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})<\/span>\n\n#view DataFrame<\/span>\ndf\n\npoints assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0417\u0430\u043c\u0456\u043d\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0432\u0441\u044c\u043e\u043c\u0443 DataFrame<\/strong><\/span><\/h3>\n
 \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e Where()<\/strong> \u0434\u043b\u044f \u0437\u0430\u043c\u0456\u043d\u0438 \u0432\u0441\u0456\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u044c, \u044f\u043a\u0456 \u043d\u0435 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0430\u044e\u0442\u044c \u043f\u0435\u0432\u043d\u0456\u0439 \u0443\u043c\u043e\u0432\u0456, \u0443 \u0446\u0456\u043b\u043e\u043c\u0443 pandas DataFrame \u043d\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f NaN.<\/span><\/p>\n
 #keep values that are greater than 7, but replace all others with NaN<\/span>\ndf. where<\/span> (df>7)\n\n\tpoints assists rebounds\n0 25 NaN 11.0\n1 12 NaN 8.0\n2 15 NaN 10.0\n3 14 9.0 NaN\n4 19 12.0 NaN\n5 23 9.0 NaN\n6 25 9.0 9.0\n7 29 NaN 12.0\n<\/strong><\/pre>\n
 \u041c\u0438 \u0442\u0430\u043a\u043e\u0436 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0438\u0439<\/strong> \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442, \u0449\u043e\u0431 \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0447\u0438\u043c\u043e\u0441\u044c \u0456\u043d\u0448\u0438\u043c, \u043d\u0456\u0436 NaN.<\/span><\/p>\n
 #keep values that are greater than 7, but replace all others with 'low'<\/span>\ndf. where<\/span> (df>7, other=' low<\/span> ')\n\n\tpoints assists rebounds\n0 25 low 11\n1 12 low 8\n2 15 low 10\n3 14 9 low\n4 19 12 low\n5 23 9 low\n6 25 9 9\n7 29 low 12\n<\/strong><\/pre>\n
 \u041f\u0440\u0438\u043a\u043b\u0430\u0434 2: \u0417\u0430\u043c\u0456\u043d\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u043f\u0435\u0432\u043d\u043e\u043c\u0443 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 DataFrame<\/strong><\/span><\/h3>\n
 \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e Where()<\/strong> \u0434\u043b\u044f \u0437\u0430\u043c\u0456\u043d\u0438 \u0432\u0441\u0456\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u044c, \u044f\u043a\u0456 \u043d\u0435 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0430\u044e\u0442\u044c \u043f\u0435\u0432\u043d\u0456\u0439 \u0443\u043c\u043e\u0432\u0456, \u0443 \u043f\u0435\u0432\u043d\u043e\u043c\u0443 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 DataFrame.<\/span><\/p>\n
 #keep values greater than 15 in 'points' column, but replace others with 'low'<\/span>\ndf[' points<\/span> '] = df[' points<\/span> ']. where<\/span> (df[' points<\/span> ']>15, other=' low<\/span> ')\n\n#view DataFrame<\/span>\ndf\n\n\tpoints assists rebounds\n0 25 5 11\n1 low 7 8\n2 low 7 10\n3 low 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n
 \u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0437\u043d\u0430\u0439\u0442\u0438 \u043f\u043e\u0432\u043d\u0443 \u043e\u043d\u043b\u0430\u0439\u043d-\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0456\u044e \u0434\u043b\u044f \u0444\u0443\u043d\u043a\u0446\u0456\u0457 pandaswhere()<\/strong> \u0442\u0443\u0442<\/a> .<\/span><\/p>\n
 \u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n
 \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\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u043f\u043e\u0448\u0438\u0440\u0435\u043d\u0456 \u0444\u0443\u043d\u043a\u0446\u0456\u0457 \u0432 pandas:<\/span><\/p>\n
 \u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e describe() \u0443 Pandas<\/a>
 \u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e idxmax() \u0443 Pandas<\/a>
 \u042f\u043a \u0437\u0430\u0441\u0442\u043e\u0441\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e \u0434\u043e \u0432\u0438\u0431\u0440\u0430\u043d\u0438\u0445 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u0443 Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0424\u0443\u043d\u043a\u0446\u0456\u044e Where() \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u0430\u043c\u0456\u043d\u0438 \u043f\u0435\u0432\u043d\u0438\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 pandas DataFrame. \u0426\u044f \u0444\u0443\u043d\u043a\u0446\u0456\u044f \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441: df. where (cond, other=nan) \u0414\u043b\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 pandas DataFrame, \u0434\u0435 cond \u043c\u0430\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f True, \u0437\u0431\u0435\u0440\u0456\u0433\u0430\u0454\u0442\u044c\u0441\u044f \u0432\u0438\u0445\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f. \u0414\u043b\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f, \u0434\u0435 cond \u043c\u0430\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f False, \u0432\u0438\u0445\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0437\u0430\u043c\u0456\u043d\u044e\u0454\u0442\u044c\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f\u043c, \u0443\u043a\u0430\u0437\u0430\u043d\u0438\u043c \u0456\u043d\u0448\u0438\u043c \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u043e\u043c. \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 […]<\/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":"\n\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e Where() \u0443 Pandas (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) \u2013 \u0421\u0442\u0430\u0442\u043e\u043b\u043e\u0433\u0456\u044f<\/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 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e where() \u0443 pandas DataFrame, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438.\" \/>\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\/\u043f\u0430\u043d\u0434\u0438-\u0430\u0431\u043e\/\" \/>\n<meta property=\"og:locale\" content=\"uk_UA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e Where() \u0443 Pandas (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) \u2013 \u0421\u0442\u0430\u0442\u043e\u043b\u043e\u0433\u0456\u044f\" \/>\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 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e where() \u0443 pandas DataFrame, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/\u043f\u0430\u043d\u0434\u0438-\u0430\u0431\u043e\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-23T22:48:45+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\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b0%d0%b1%d0%be\/\",\"url\":\"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b0%d0%b1%d0%be\/\",\"name\":\"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e Where() \u0443 Pandas (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) \u2013 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