{"id":2092,"date":"2023-07-23T17:39:42","date_gmt":"2023-07-23T17:39:42","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%92%e1%85%a7%e1%86%ab%e1%84%8c%e1%85%a1%e1%86%bc%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%89%e1%85%b5%e1%86%ab%e1%84%8e\/"},"modified":"2023-07-23T17:39:42","modified_gmt":"2023-07-23T17:39:42","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%92%e1%85%a7%e1%86%ab%e1%84%8c%e1%85%a1%e1%86%bc%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%89%e1%85%b5%e1%86%ab%e1%84%8e","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%92%e1%85%a7%e1%86%ab%e1%84%8c%e1%85%a1%e1%86%bc%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%89%e1%85%b5%e1%86%ab%e1%84%8e\/","title":{"rendered":"Pandas apply()\ub97c \uc81c\uc790\ub9ac\uc5d0\uc11c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

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pandas apply()<\/a> \ud568\uc218\ub294 pandas DataFrame\uc758 \ud589\uc774\ub098 \uc5f4\uc5d0 \ud568\uc218\ub97c \uc801\uc6a9\ud558\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud568\uc218\ub294 inplace \uc778\uc218\ub97c \uc81c\uacf5\ud558\ub294 drop()<\/strong> \ubc0f replacement()<\/strong> \uc640 \uac19\uc740 \ub2e4\ub978 \ud568\uc218\uc640 \ub2e4\ub985\ub2c8\ub2e4.<\/span><\/p>\n

 df. drop<\/span> ([' column1<\/span> '], inplace= True<\/span> )\n\ndf. rename<\/span> ({' old_column<\/span> ': ' new_column<\/span> '}, inplace= True<\/span> )\n<\/strong><\/pre>\n
 apply()<\/strong> \ud568\uc218\uc5d0\ub294 \ub0b4\ubd80 \uc778\uc218\uac00 \uc5c6\uc73c\ubbc0\ub85c \ub0b4\ubd80 DataFrame\uc744 \ubcc0\ud658\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n
 df = df. apply<\/span> ( lambda<\/span> x: x* 2<\/span> )<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\ub294 \ub2e4\uc74c pandas DataFrame\uc5d0\uc11c \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = 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]})\n\n#view DataFrame\n<\/span>df\n\n        points 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\n<\/strong><\/pre>\n
 \uc608 1: \uc5f4\uc5d0 apply() \uc0ac\uc6a9<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 apply()\ub97c<\/strong> \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \ud504\ub808\uc784 \uc5f4\uc744 \uc81c\uc790\ub9ac\uc5d0\uc11c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #multiply all values in 'points' column by 2 in place\n<\/span>df. loc<\/span> [:, ' points<\/span> '] = df. points<\/span> . apply<\/span> ( lambda<\/span> x: x* 2<\/span> )\n\n#view updated DataFrame<\/span>\ndf\n\npoints assists rebounds\n0 50 5 11\n1 24 7 8\n2 30 7 10\n3 28 9 6\n4 38 12 6\n5 46 9 5\n6 50 9 9\n7 58 4 12\n<\/strong><\/pre>\n
 \uc608 2: \uc5ec\ub7ec \uc5f4\uc5d0 \ub300\ud574 \uc801\uc6a9() \uc0ac\uc6a9<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 apply()\ub97c<\/strong> \uc0ac\uc6a9\ud558\uc5ec \uc5ec\ub7ec \ub370\uc774\ud130 \ud504\ub808\uc784 \uc5f4\uc744 \uc81c\uc790\ub9ac\uc5d0\uc11c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 multiply all values in 'points' and 'rebounds' column by 2 in place<\/span>\ndf[[' points<\/span> ', ' rebounds<\/span> ']] = df[[' points<\/span> ', ' rebounds<\/span> ']]. apply<\/span> ( lambda<\/span> x: x* 2<\/span> )\n\n#view updated DataFrame\n<\/span>df\n\n\tpoints assists rebounds\n0 50 5 22\n1 24 7 16\n2 30 7 20\n3 28 9 12\n4 38 12 12\n5 46 9 10\n6 50 9 18\n7 58 4 24\n<\/strong><\/pre>\n
 \uc608 3: \ubaa8\ub4e0 \uc5f4\uc5d0 \ub300\ud574 \uc801\uc6a9() \uc0ac\uc6a9<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 apply()\ub97c<\/strong> \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \ud504\ub808\uc784\uc758 \ubaa8\ub4e0 \uc5f4\uc744 \uc81c\uc790\ub9ac\uc5d0\uc11c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #multiply values in all columns by 2\n<\/span>df = df. apply<\/span> ( lambda<\/span> x: x* 2<\/span> )\n\n#view updated DataFrame<\/span>\ndf\n\n\tpoints assists rebounds\n0 50 10 22\n1 24 14 16\n2 30 14 20\n3 28 18 12\n4 38 24 12\n5 46 18 10\n6 50 18 18\n7 58 8 24\n<\/strong><\/pre>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uae30\ub2a5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas\uc5d0\uc11c \uc5f4\uc758 \ud569\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas\uc5d0\uc11c \uc5f4\uc758 \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas\uc5d0\uc11c \uc5f4\uc758 \ucd5c\ub300\uac12\uc744 \ucc3e\ub294 \ubc29\ubc95<\/p>\n","protected":false},"excerpt":{"rendered":"
pandas apply() \ud568\uc218\ub294 pandas DataFrame\uc758 \ud589\uc774\ub098 \uc5f4\uc5d0 \ud568\uc218\ub97c \uc801\uc6a9\ud558\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ud568\uc218\ub294 inplace \uc778\uc218\ub97c \uc81c\uacf5\ud558\ub294 drop() \ubc0f replacement() \uc640 \uac19\uc740 \ub2e4\ub978 \ud568\uc218\uc640 \ub2e4\ub985\ub2c8\ub2e4. df. drop ([‘ column1 ‘], inplace= True ) df. rename ({‘ old_column ‘: ‘ new_column ‘}, inplace= True ) apply() \ud568\uc218\uc5d0\ub294 \ub0b4\ubd80 \uc778\uc218\uac00 \uc5c6\uc73c\ubbc0\ub85c \ub0b4\ubd80 DataFrame\uc744 \ubcc0\ud658\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-2092","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas 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