{"id":986,"date":"2023-07-28T02:09:42","date_gmt":"2023-07-28T02:09:42","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%80%e1%85%a8%e1%84%8e%e1%85%b3%e1%86%bc%e1%84%92%e1%85%aa-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc\/"},"modified":"2023-07-28T02:09:42","modified_gmt":"2023-07-28T02:09:42","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%80%e1%85%a8%e1%84%8e%e1%85%b3%e1%86%bc%e1%84%92%e1%85%aa-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc","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%80%e1%85%a8%e1%84%8e%e1%85%b3%e1%86%bc%e1%84%92%e1%85%aa-%e1%84%89%e1%85%a2%e1%86%b7%e1%84%91%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc\/","title":{"rendered":"Pandas\uc758 \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\ub9c1(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

\uc5f0\uad6c\uc790\ub4e4\uc740 \uc885\uc885 \ubaa8\uc9d1\ub2e8\uc5d0\uc11c \ud45c\ubcf8\uc744<\/a> \ucc44\ucde8\ud558\uace0 \ud45c\ubcf8\uc758 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\uc9d1\ub2e8 \uc804\uccb4\uc5d0 \ub300\ud55c \uacb0\ub860\uc744 \ub3c4\ucd9c\ud569\ub2c8\ub2e4.<\/span><\/p>\n

\uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ub418\ub294 \uc0d8\ud50c\ub9c1 \ubc29\ubc95\uc740 \uacc4\uce35\ud654 \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1<\/strong> \uc73c\ub85c, \ubaa8\uc9d1\ub2e8\uc744 \uadf8\ub8f9\uc73c\ub85c \ub098\ub204\uace0 \uac01 \uadf8\ub8f9\uc5d0\uc11c \ud2b9\uc815 \uc218\uc758 \uad6c\uc131\uc6d0\uc744 \ubb34\uc791\uc704\ub85c \uc120\ud0dd\ud558\uc5ec \ud45c\ubcf8\uc5d0 \ud3ec\ud568\uc2dc\ud0b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \uacc4\uce35\ud654\ub41c \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ub450 \uac00\uc9c0 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n

\uc608 1: \uac1c\uc218\ub97c \uc0ac\uc6a9\ud55c \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\ub9c1<\/strong><\/h3>\n

\uc11c\ub85c \ub2e4\ub978 \ub450 \ud300\uc758 \ub18d\uad6c \uc120\uc218 8\uba85\uc5d0 \ub300\ud55c \ub370\uc774\ud130\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})\n\n#view DataFrame\n<\/span>df\n\n        team position assists rebounds\n0 A G 5 11\n1 A G 7 8\n2 A F 7 10\n3 A G 8 6\n4 B F 5 6\n5 B F 7 9\n6 B C 6 6\n7 B C 9 10\n<\/strong><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc0d8\ud50c\uc5d0 \ud3ec\ud568\ud560 \uac01 \ud300\uc5d0\uc11c 2\uba85\uc758 \ud50c\ub808\uc774\uc5b4\ub97c \ubb34\uc791\uc704\ub85c \uc120\ud0dd\ud558\uc5ec \uacc4\uce35\ud654\ub41c \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 df. groupby<\/span> ('team', group_keys= False<\/span> ). apply<\/span> ( lambda<\/span> x: x.sample<\/span> (2))\n\n        team position assists rebounds\n0 A G 5 11\n3 A G 8 6\n6 B C 6 6\n5 B F 7 9\n<\/strong><\/pre>\n
 \uac01 \ud300\uc758 \ub450 \uba85\uc758 \uc120\uc218\uac00 \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\uc5d0 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608 2: \ube44\uc728\uc744 \uc0ac\uc6a9\ud55c \uce35\ud654 \uc0d8\ud50c\ub9c1<\/strong><\/h3>\n
 \uc11c\ub85c \ub2e4\ub978 \ub450 \ud300\uc758 \ub18d\uad6c \uc120\uc218 8\uba85\uc5d0 \ub300\ud55c \ub370\uc774\ud130\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \ub2e4\uc2dc \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'B', 'B', 'B', 'B'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})\n\n#view DataFrame\n<\/span>df\n\n        team position assists rebounds\n0 A G 5 11\n1 A G 7 8\n2 A F 7 10\n3 A G 8 6\n4 B F 5 6\n5 B F 7 9\n6 B C 6 6\n7 B C 9 10\n<\/strong><\/pre>\n
 DataFrame\uc758 \ud50c\ub808\uc774\uc5b4 8\uba85 \uc911 6\uba85(75%)\uc740 A\ud300\uc5d0 \uc18d\ud558\uace0 \ud50c\ub808\uc774\uc5b4 8\uba85 \uc911 2\uba85(25%)\uc740 B\ud300\uc5d0 \uc18d\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uac01 \ud300\uc758 \uc0d8\ud50c\uc5d0 \uc788\ub294 \ud50c\ub808\uc774\uc5b4 \ube44\uc728\uc774 \ub354 \ud070 DataFrame\uc5d0 \uc788\ub294 \uac01 \ud300\uc758 \ud50c\ub808\uc774\uc5b4 \ube44\uc728\uacfc \uc77c\uce58\ud558\ub3c4\ub85d \uacc4\uce35\ud654\ub41c \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> numpy as np\n\n<\/span>#define total sample size desired<\/span>\nN = 4\n\n#perform stratified random sampling<\/span>\ndf. groupby<\/span> ('team', group_keys= False<\/span> ). apply<\/span> ( lambda<\/span> x: x. sample<\/span> (int(np. rint<\/span> (N* len<\/span> (x)\/ len<\/span> (df))))). sample<\/span> (frac=1). reset_index<\/span> (drop= True<\/span> )\n\n        team position assists rebounds\n0 B F 7 9\n1 B G 8 6\n2 B C 6 6\n3 A G 7 8\n<\/strong><\/pre>\n
 \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\uc5d0\uc11c A\ud300 \ud50c\ub808\uc774\uc5b4\uc758 \ube44\uc728(25%)\uc740 \ub354 \ud070 DataFrame\uc5d0\uc11c A\ud300 \ud50c\ub808\uc774\uc5b4\uc758 \ube44\uc728\uacfc \uc77c\uce58\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub9c8\ucc2c\uac00\uc9c0\ub85c, \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\uc758 B\ud300 \ud50c\ub808\uc774\uc5b4 \ube44\uc728(75%)\uc740 \ub354 \ud070 DataFrame\uc758 B\ud300 \ud50c\ub808\uc774\uc5b4 \ube44\uc728\uacfc \uc77c\uce58\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\ub978 \uc0d8\ud50c \uc720\ud615\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas\uc5d0\uc11c \ud074\ub7ec\uc2a4\ud130 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 \ud32c\ub354\ub4e4 \uc0ac\uc774\uc5d0\uc11c \uccb4\uacc4\uc801\uc778 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\uc5f0\uad6c\uc790\ub4e4\uc740 \uc885\uc885 \ubaa8\uc9d1\ub2e8\uc5d0\uc11c \ud45c\ubcf8\uc744 \ucc44\ucde8\ud558\uace0 \ud45c\ubcf8\uc758 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\uc9d1\ub2e8 \uc804\uccb4\uc5d0 \ub300\ud55c \uacb0\ub860\uc744 \ub3c4\ucd9c\ud569\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ub418\ub294 \uc0d8\ud50c\ub9c1 \ubc29\ubc95\uc740 \uacc4\uce35\ud654 \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1 \uc73c\ub85c, \ubaa8\uc9d1\ub2e8\uc744 \uadf8\ub8f9\uc73c\ub85c \ub098\ub204\uace0 \uac01 \uadf8\ub8f9\uc5d0\uc11c \ud2b9\uc815 \uc218\uc758 \uad6c\uc131\uc6d0\uc744 \ubb34\uc791\uc704\ub85c \uc120\ud0dd\ud558\uc5ec \ud45c\ubcf8\uc5d0 \ud3ec\ud568\uc2dc\ud0b5\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \uacc4\uce35\ud654\ub41c \ubb34\uc791\uc704 \uc0d8\ud50c\ub9c1\uc744 \uc218\ud589\ud558\ub294 \ub450 \uac00\uc9c0 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. \uc608 1: \uac1c\uc218\ub97c \uc0ac\uc6a9\ud55c \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\ub9c1 \uc11c\ub85c \ub2e4\ub978 \ub450 \ud300\uc758 \ub18d\uad6c […]<\/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-986","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas\uc758 \uacc4\uce35\ud654\ub41c \uc0d8\ud50c\ub9c1(\uc608\uc81c \ud3ec\ud568) - 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