{"id":2866,"date":"2023-07-20T08:29:01","date_gmt":"2023-07-20T08:29:01","guid":{"rendered":"https:\/\/statorials.org\/th\/%e0%b9%81%e0%b8%9e%e0%b8%99%e0%b8%94%e0%b9%89%e0%b8%b2%e0%b9%81%e0%b8%97%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88-inf-%e0%b8%94%e0%b9%89%e0%b8%a7%e0%b8%a2-0\/"},"modified":"2023-07-20T08:29:01","modified_gmt":"2023-07-20T08:29:01","slug":"%e0%b9%81%e0%b8%9e%e0%b8%99%e0%b8%94%e0%b9%89%e0%b8%b2%e0%b9%81%e0%b8%97%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88-inf-%e0%b8%94%e0%b9%89%e0%b8%a7%e0%b8%a2-0","status":"publish","type":"post","link":"https:\/\/statorials.org\/th\/%e0%b9%81%e0%b8%9e%e0%b8%99%e0%b8%94%e0%b9%89%e0%b8%b2%e0%b9%81%e0%b8%97%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88-inf-%e0%b8%94%e0%b9%89%e0%b8%a7%e0%b8%a2-0\/","title":{"rendered":"Pandas: \u0e27\u0e34\u0e18\u0e35\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48 inf \u0e14\u0e49\u0e27\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48\u0e04\u0e48\u0e32 inf \u0e41\u0e25\u0e30 -inf \u0e14\u0e49\u0e27\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c\u0e43\u0e19 DataFrame \u0e02\u0e2d\u0e07 pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">replace<\/span> ([np. <span style=\"color: #3366ff;\">inf<\/span> , -np. <span style=\"color: #3366ff;\">inf<\/span> ], <span style=\"color: #008000;\">0<\/span> , inplace= <span style=\"color: #008000;\">True<\/span> )\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e27\u0e34\u0e18\u0e35\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e19\u0e35\u0e49\u0e43\u0e19\u0e17\u0e32\u0e07\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07: \u0e41\u0e17\u0e19\u0e17\u0e35\u0e48 inf \u0e14\u0e49\u0e27\u0e22 Zero \u0e43\u0e19 Pandas<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0e2a\u0e21\u0e21\u0e15\u0e34\u0e27\u0e48\u0e32\u0e40\u0e23\u0e32\u0e21\u0e35 DataFrame \u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e0b\u0e36\u0e48\u0e07\u0e21\u0e35\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27\u0e01\u0e31\u0e1a\u0e1c\u0e39\u0e49\u0e40\u0e25\u0e48\u0e19\u0e1a\u0e32\u0e2a\u0e40\u0e01\u0e15\u0e1a\u0e2d\u0e25\u0e15\u0e48\u0e32\u0e07\u0e46:<\/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<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createDataFrame\n<span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [18, np. <span style=\"color: #3366ff;\">inf<\/span> , 19, np. <span style=\"color: #3366ff;\">inf<\/span> , 14, 11, 20, 28],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, np. <span style=\"color: #3366ff;\">inf<\/span> ],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [np. <span style=\"color: #3366ff;\">inf<\/span> , 8, 10, 6, 6, -np. <span style=\"color: #3366ff;\">inf<\/span> , 9, 12]})<\/span>\n\n#view DataFrame\n<span style=\"color: #000000;\">df\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<p> <span style=\"color: #000000;\">\u0e42\u0e1b\u0e23\u0e14\u0e17\u0e23\u0e32\u0e1a\u0e27\u0e48\u0e32\u0e21\u0e35\u0e04\u0e48\u0e32 inf \u0e41\u0e25\u0e30 -inf \u0e2b\u0e25\u0e32\u0e22\u0e04\u0e48\u0e32\u0e43\u0e19 DataFrame<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0e40\u0e23\u0e32\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48\u0e04\u0e48\u0e32 inf \u0e41\u0e25\u0e30 -inf \u0e40\u0e2b\u0e25\u0e48\u0e32\u0e19\u0e35\u0e49\u0e14\u0e49\u0e27\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#replace inf and -inf with zero\n<\/span>df. <span style=\"color: #3366ff;\">replace<\/span> ([np. <span style=\"color: #3366ff;\">inf<\/span> , -np. <span style=\"color: #3366ff;\">inf<\/span> ], <span style=\"color: #008000;\">0<\/span> , inplace= <span style=\"color: #008000;\">True<\/span> )\n<\/span>\n#view updated DataFrame\n<span style=\"color: #000000;\">df\n<\/span>\n<span style=\"color: #000000;\">team points assists<\/span> <span style=\"color: #000000;\">rebounds\n0 A 18.0 5.0<\/span> <span style=\"color: #000000;\">0.0\n1 B 0.0 7.0<\/span> <span style=\"color: #000000;\">8.0\n2 C 19.0 7.0<\/span> <span style=\"color: #000000;\">10.0\n3 D 0.0 9.0<\/span> <span style=\"color: #000000;\">6.0\n4 E 14.0 12.0<\/span> <span style=\"color: #000000;\">6.0\n5 F 11.0 9.0<\/span> <span style=\"color: #000000;\">0.0\n6G 20.0 9.0<\/span> <span style=\"color: #000000;\">9.0\n7 H 28.0 0.0<\/span> <span style=\"color: #000000;\">12.0<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0e42\u0e1b\u0e23\u0e14\u0e17\u0e23\u0e32\u0e1a\u0e27\u0e48\u0e32\u0e41\u0e15\u0e48\u0e25\u0e30\u0e04\u0e48\u0e32 inf \u0e41\u0e25\u0e30 -inf \u0e16\u0e39\u0e01\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48\u0e14\u0e49\u0e27\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0e2b\u0e21\u0e32\u0e22\u0e40\u0e2b\u0e15\u0e38<\/strong> : \u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e04\u0e49\u0e19\u0e2b\u0e32\u0e40\u0e2d\u0e01\u0e2a\u0e32\u0e23\u0e09\u0e1a\u0e31\u0e1a\u0e40\u0e15\u0e47\u0e21\u0e02\u0e2d\u0e07\u0e1f\u0e31\u0e07\u0e01\u0e4c\u0e0a\u0e31\u0e19 <strong>\u0e01\u0e32\u0e23\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48<\/strong> \u0e43\u0e19\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32 <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.replace.html\" target=\"_blank\" rel=\"noopener\">\u0e44\u0e14\u0e49\u0e17\u0e35\u0e48\u0e19\u0e35\u0e48<\/a><\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0e41\u0e2b\u0e25\u0e48\u0e07\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e40\u0e15\u0e34\u0e21<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e17\u0e33\u0e07\u0e32\u0e19\u0e17\u0e31\u0e48\u0e27\u0e44\u0e1b\u0e2d\u0e37\u0e48\u0e19\u0e46 \u0e43\u0e19\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e43\u0e2a\u0e48\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e2b\u0e32\u0e22\u0e44\u0e1b\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e43\u0e2a\u0e48\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e2b\u0e32\u0e22\u0e44\u0e1b\u0e43\u0e19\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e19\u0e31\u0e1a\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e2b\u0e32\u0e22\u0e44\u0e1b\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e19\u0e31\u0e1a\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e2b\u0e32\u0e22\u0e44\u0e1b\u0e43\u0e19\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e2b\u0e21\u0e35\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e21\u0e35\u0e04\u0e48\u0e32\u0e40\u0e09\u0e25\u0e35\u0e48\u0e22\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e40\u0e15\u0e34\u0e21\u0e04\u0e48\u0e32 NaN \u0e14\u0e49\u0e27\u0e22\u0e04\u0e48\u0e32\u0e40\u0e09\u0e25\u0e35\u0e48\u0e22\u0e43\u0e19\u0e2b\u0e21\u0e35\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48\u0e04\u0e48\u0e32 inf \u0e41\u0e25\u0e30 -inf [&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":[],"class_list":["post-2866","post","type-post","status-publish","format-standard","hentry","category-3"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas: \u0e27\u0e34\u0e18\u0e35\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48 inf \u0e14\u0e49\u0e27\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e41\u0e17\u0e19\u0e17\u0e35\u0e48\u0e04\u0e48\u0e32 inf \u0e14\u0e49\u0e27\u0e22 0 \u0e43\u0e19 pandas DataFrame \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\" \/>\n<meta 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