{"id":4176,"date":"2023-07-13T02:02:15","date_gmt":"2023-07-13T02:02:15","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%b5\/"},"modified":"2023-07-13T02:02:15","modified_gmt":"2023-07-13T02:02:15","slug":"r%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%b5\/","title":{"rendered":"R\uc5d0\uc11c \ub370\uc774\ud130 \uc815\ub9ac\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

\ub370\uc774\ud130 \ud074\ub9ac\ub2dd(Data Cleaning)\uc740<\/strong> \uc6d0\uc2dc \ub370\uc774\ud130\ub97c<\/a> \ubd84\uc11d\uc774\ub098 \ubaa8\ub378 \uad6c\ucd95\uc5d0 \uc801\ud569\ud55c \ub370\uc774\ud130\ub85c \ubcc0\ud658\ud558\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n

\ub300\ubd80\ubd84\uc758 \uacbd\uc6b0 \ub370\uc774\ud130 \uc138\ud2b8\ub97c “\uc815\ub9ac”\ud558\ub824\uba74 \ub204\ub77d\ub41c \uac12\uacfc \uc911\ubcf5 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n

R\uc5d0\uc11c \ub370\uc774\ud130 \uc138\ud2b8\ub97c “\uc815\ub9ac”\ud558\ub294 \uac00\uc7a5 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ubc29\ubc95 1: \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589 \uc81c\uac70<\/strong><\/span><\/p>\n

 library<\/span> (dplyr)\n\n#remove rows with any missing values\n<\/span>df %>% na. omit<\/span> ()\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \ub204\ub77d\ub41c \uac12\uc744 \ub2e4\ub978 \uac12\uc73c\ub85c \ub300\uccb4<\/strong><\/span><\/p>\n
 library<\/span> (dplyr)\nlibrary<\/span> (tidyr)\n\n#replace missing values in each numeric column with median value of column\n<\/span>df %>% mutate(across(where(is. numeric<\/span> ), ~replace_na(., median(., na. rm<\/span> = TRUE<\/span> ))))\n<\/strong><\/pre>\n
 \ubc29\ubc95 3: \uc911\ubcf5 \ud589 \uc81c\uac70<\/strong><\/span><\/p>\n
 library<\/span> (dplyr)\n\ndf %>% distinct(. keep_all<\/span> = TRUE<\/span> )\n<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc81c\uc5d0\uc11c\ub294 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c R\uc758 \ub2e4\uc74c \ub370\uc774\ud130 \ud504\ub808\uc784\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc2e4\uc81c\ub85c \uc774\ub7ec\ud55c \uac01 \uba54\uc11c\ub4dc\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (team=c('A', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'),\n                 points=c(4, 4, NA, 8, 6, 12, 14, 86, 13, 8),\n                 rebounds=c(9, 9, 7, 6, 8, NA, 9, 14, 12, 11),\n                 assists=c(2, 2, NA, 7, 6, 6, 9, 10, NA, 14))\n\n#view data frame\n<\/span>df\n\n   team points rebound assists\n1 to 4 9 2\n2 to 4 9 2\n3 B NA 7 NA\n4 C 8 6 7\n5 D 6 8 6\n6 E 12 NA 6\n7 F 14 9 9\n8 G 86 14 10\n9:13:12 NA\n10 I 8 11 14\n<\/strong><\/pre>\n
 \uc608 1: \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589 \uc0ad\uc81c<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \uc5f4\uc5d0\uc11c \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589\uc744 \uc81c\uac70\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 library<\/span> (dplyr)\n\n#remove rows with missing values\n<\/span>new_df <- df %>% na. omit<\/span> ()\n\n#view new data frame\n<\/span>new_df\n\n   team points rebound assists\n1 to 4 9 2\n2 to 4 9 2\n4 C 8 6 7\n5 D 6 8 6\n7 F 14 9 9\n8 G 86 14 10\n10 I 8 11 14<\/strong><\/pre>\n
 \uc0c8 \ub370\uc774\ud130 \ud504\ub808\uc784\uc5d0\ub294 \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 2: \ub204\ub77d\ub41c \uac12\uc744 \ub2e4\ub978 \uac12\uc73c\ub85c \ub300\uccb4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub204\ub77d\ub41c \uac12\uc744 \uac01 \uc5f4\uc758 \uc911\uc559\uac12\uc73c\ub85c \ubc14\uafc0 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 library<\/span> (dplyr)\nlibrary<\/span> (tidyr)\n\n#replace missing values in each numeric column with median value of column\n<\/span>new_df <-df %>% mutate(across(where(is. numeric<\/span> ),~replace_na(.,median(.,na. rm<\/span> = TRUE<\/span> )))) \n\n#view new data frame\n<\/span>new_df\n\n   team points rebound assists\n1 to 4 9 2.0\n2 to 4 9 2.0\n3 B 8 7 6.5\n4 C 8 6 7.0\n5 D 6 8 6.0\n6 E 12 9 6.0\n7 F 14 9 9.0\n8 G 86 14 10.0\n9:13 12 6.5\n10 I 8 11 14.0<\/strong><\/pre>\n
 \uac01 \uc22b\uc790 \uc5f4\uc758 \ub204\ub77d\ub41c \uac12\uc740 \uac01\uac01 \ud574\ub2f9 \uc5f4\uc758 \uc911\uc559\uac12\uc73c\ub85c \ub300\uccb4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc218\uc2dd\uc758 \uc911\uc559\uac12\uc744<\/strong> \ud3c9\uade0<\/strong> \uc73c\ub85c \ub300\uccb4\ud558\uc5ec \ub204\ub77d\ub41c \uac12\uc744 \uac01 \uc5f4\uc758 \ud3c9\uade0\uac12\uc73c\ub85c \ubc14\uafc0 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucc38\uace0<\/strong> : \uc774 \uc608\uc81c\uc5d0\uc11c\ub294 drop_na()<\/strong> \ud568\uc218\uac00 \ud574\ub2f9 \ud328\ud0a4\uc9c0\uc5d0\uc11c \uc81c\uacf5\ub418\uae30 \ub54c\ubb38\uc5d0 Tidyr<\/strong> \ud328\ud0a4\uc9c0\ub3c4 \ub85c\ub4dc\ud574\uc57c \ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 3: \uc911\ubcf5 \ud589 \uc81c\uac70<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub204\ub77d\ub41c \uac12\uc744 \uac01 \uc5f4\uc758 \uc911\uc559\uac12\uc73c\ub85c \ubc14\uafc0 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 library<\/span> (dplyr)\n\n#remove duplicate rows\n<\/span>new_df <- df %>% distinct(. keep_all<\/span> = TRUE<\/span> )\n\n#view new data frame\n<\/span>new_df\n\n  team points rebound assists\n1 to 4 9 2\n2 B NA 7 NA\n3 C 8 6 7\n4 D 6 8 6\n5 E 12 NA 6\n6 F 14 9 9\n7 G 86 14 10\n8:13:12 NA\n9 I 8 11 14<\/strong><\/pre>\n
 \ub450 \ubc88\uc9f8 \ud589\uc758 \uac01 \uac12\uc774 \uccab \ubc88\uc9f8 \ud589\uc758 \uac12\uacfc \uc911\ubcf5\ub418\uc5c8\uae30 \ub54c\ubb38\uc5d0 \ub450 \ubc88\uc9f8 \ud589\uc774 \ub370\uc774\ud130 \ud504\ub808\uc784\uc5d0\uc11c \uc81c\uac70\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucc38\uace0<\/strong> : dplyr independent()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub294 \uc5ec\uae30\uc5d0\uc11c<\/a> \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 R\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uadf8\ub8f9\ud654\ud558\uace0 \uc694\uc57d\ud558\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \uc694\uc57d \ud14c\uc774\ube14\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589\uc744 \uc0ad\uc81c\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub370\uc774\ud130 \ud074\ub9ac\ub2dd(Data Cleaning)\uc740 \uc6d0\uc2dc \ub370\uc774\ud130\ub97c \ubd84\uc11d\uc774\ub098 \ubaa8\ub378 \uad6c\ucd95\uc5d0 \uc801\ud569\ud55c \ub370\uc774\ud130\ub85c \ubcc0\ud658\ud558\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \ub300\ubd80\ubd84\uc758 \uacbd\uc6b0 \ub370\uc774\ud130 \uc138\ud2b8\ub97c “\uc815\ub9ac”\ud558\ub824\uba74 \ub204\ub77d\ub41c \uac12\uacfc \uc911\ubcf5 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud574\uc57c \ud569\ub2c8\ub2e4. R\uc5d0\uc11c \ub370\uc774\ud130 \uc138\ud2b8\ub97c “\uc815\ub9ac”\ud558\ub294 \uac00\uc7a5 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \ub204\ub77d\ub41c \uac12\uc774 \uc788\ub294 \ud589 \uc81c\uac70 library (dplyr) #remove rows with any missing values df %>% na. omit () \ubc29\ubc95 2: […]<\/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-4176","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nR\uc5d0\uc11c \ub370\uc774\ud130 \uc815\ub9ac\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 R\uc758 \ub370\uc774\ud130\uc138\ud2b8\uc5d0 \ub300\ud574 \ub370\uc774\ud130 \uc815\ub9ac\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc2dc\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\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\/ko\/r\u110b\u1174-\u1103\u1166\u110b\u1175\u1110\u1165-\u110c\u1165\u11bc\u1105\u1175\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R\uc5d0\uc11c \ub370\uc774\ud130 \uc815\ub9ac\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - 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