{"id":2863,"date":"2023-07-20T08:29:01","date_gmt":"2023-07-20T08:29:01","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0\/"},"modified":"2023-07-20T08:29:01","modified_gmt":"2023-07-20T08:29:01","slug":"%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0\/","title":{"rendered":"Pandas: \u044f\u043a \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 inf \u043d\u0430 \u043d\u0443\u043b\u044c"},"content":{"rendered":"

<\/p>\n

\n

\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441, \u0449\u043e\u0431 \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u0456 -inf \u043d\u0430 \u043d\u0443\u043b\u044c \u0443 pandas DataFrame:<\/span><\/p>\n

 df. replace<\/span> ([np. inf<\/span> , -np. inf<\/span> ], 0<\/span> , inplace= True<\/span> )\n<\/strong><\/pre>\n
 \u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \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.<\/span><\/p>\n
 \u041f\u0440\u0438\u043a\u043b\u0430\u0434: \u0437\u0430\u043c\u0456\u043d\u0456\u0442\u044c inf \u043d\u0430 Zero \u0432 Pandas<\/strong><\/span><\/h3>\n
 \u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u0438\u0445 pandas, \u044f\u043a\u0438\u0439 \u043c\u0456\u0441\u0442\u0438\u0442\u044c \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u044e \u043f\u0440\u043e \u0440\u0456\u0437\u043d\u0438\u0445 \u0431\u0430\u0441\u043a\u0435\u0442\u0431\u043e\u043b\u0456\u0441\u0442\u0456\u0432:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [18, np. inf<\/span> , 19, np. inf<\/span> , 14, 11, 20, 28],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, np. inf<\/span> ],\n                   ' rebounds<\/span> ': [np. inf<\/span> , 8, 10, 6, 6, -np. inf<\/span> , 9, 12]})<\/span>\n\n#view DataFrame\ndf\n\n\tteam points assists rebounds\n0 A 18.0 5.0 lower\n1 B lower 7.0 8.0\n2 C 19.0 7.0 10.0\n3D lower 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 -low\n6G 20.0 9.0 9.0\n7H 28.0 lower 12.0\n<\/span><\/span><\/strong><\/pre>\n
 \u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u0432 DataFrame \u0454 \u043a\u0456\u043b\u044c\u043a\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u044c inf \u0456 -inf.<\/span><\/p>\n
 \u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441, \u0449\u043e\u0431 \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0446\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u0456 -inf \u043d\u0430 \u043d\u0443\u043b\u044c:<\/span><\/p>\n
 #replace inf and -inf with zero\n<\/span>df. replace<\/span> ([np. inf<\/span> , -np. inf<\/span> ], 0<\/span> , inplace= True<\/span> )\n<\/span>\n#view updated DataFrame\ndf\n<\/span>\nteam points assists<\/span> rebounds\n0 A 18.0 5.0<\/span> 0.0\n1 B 0.0 7.0<\/span> 8.0\n2 C 19.0 7.0<\/span> 10.0\n3 D 0.0 9.0<\/span> 6.0\n4 E 14.0 12.0<\/span> 6.0\n5 F 11.0 9.0<\/span> 0.0\n6G 20.0 9.0<\/span> 9.0\n7 H 28.0 0.0<\/span> 12.0<\/span><\/span><\/strong><\/pre>\n
 \u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u043a\u043e\u0436\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u0456 -inf \u0431\u0443\u043b\u043e \u0437\u0430\u043c\u0456\u043d\u0435\u043d\u043e \u043d\u0430 \u043d\u0443\u043b\u044c.<\/span><\/p>\n
 \u041f\u0440\u0438\u043c\u0456\u0442\u043a\u0430<\/strong> : \u043f\u043e\u0432\u043d\u0443 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0456\u044e \u0449\u043e\u0434\u043e \u0444\u0443\u043d\u043a\u0446\u0456\u0457 \u0437\u0430\u043c\u0456\u043d\u0438<\/strong> \u0432 pandas \u043c\u043e\u0436\u043d\u0430 \u0437\u043d\u0430\u0439\u0442\u0438 \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\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u0442\u0438\u043f\u043e\u0432\u0456 \u0437\u0430\u0432\u0434\u0430\u043d\u043d\u044f \u0432 pandas:<\/span><\/p>\n
 \u042f\u043a \u043f\u0440\u0438\u0437\u043d\u0430\u0447\u0438\u0442\u0438 \u0432\u0456\u0434\u0441\u0443\u0442\u043d\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 \u043f\u0430\u043d\u0434\u0430\u0445<\/a>
 \u042f\u043a \u043f\u043e\u0440\u0430\u0445\u0443\u0432\u0430\u0442\u0438 \u043f\u0440\u043e\u043f\u0443\u0449\u0435\u043d\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 \u043f\u0430\u043d\u0434\u0430\u0445<\/a>
 \u042f\u043a \u0437\u0430\u043f\u043e\u0432\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f NaN \u0441\u0435\u0440\u0435\u0434\u043d\u0456\u043c \u0443 pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441, \u0449\u043e\u0431 \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u0456 -inf \u043d\u0430 \u043d\u0443\u043b\u044c \u0443 pandas DataFrame: df. replace ([np. inf , -np. inf ], 0 , inplace= True ) \u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \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. \u041f\u0440\u0438\u043a\u043b\u0430\u0434: \u0437\u0430\u043c\u0456\u043d\u0456\u0442\u044c inf \u043d\u0430 Zero \u0432 Pandas \u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u0438\u0445 pandas, […]<\/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":"\nPandas: \u042f\u043a \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 inf \u043d\u0430 \u043d\u0443\u043b\u044c \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\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u043d\u0430 0 \u0443 pandas DataFrame \u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u043e\u043c.\" \/>\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-\u0437\u0430\u043c\u0456\u043d\u044e\u044e\u0442\u044c-inf-\u043d\u0430-0\/\" \/>\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\u0430\u043c\u0456\u043d\u0438\u0442\u0438 inf \u043d\u0430 \u043d\u0443\u043b\u044c \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\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u043d\u0430 0 \u0443 pandas DataFrame \u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u043e\u043c.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/\u043f\u0430\u043d\u0434\u0438-\u0437\u0430\u043c\u0456\u043d\u044e\u044e\u0442\u044c-inf-\u043d\u0430-0\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-20T08:29:01+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\" 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\u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f inf \u043d\u0430 0 \u0443 pandas DataFrame \u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u043e\u043c.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0\/#breadcrumb\"},\"inLanguage\":\"uk\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/uk\/%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8-%d0%b7%d0%b0%d0%bc%d1%96%d0%bd%d1%8e%d1%8e%d1%82%d1%8c-inf-%d0%bd%d0%b0-0\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u0434\u043e\u0434\u043e\u043c\u0443\",\"item\":\"https:\/\/statorials.org\/uk\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Pandas: \u044f\u043a \u0437\u0430\u043c\u0456\u043d\u0438\u0442\u0438 inf \u043d\u0430 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