{"id":2585,"date":"2023-07-21T15:00:36","date_gmt":"2023-07-21T15:00:36","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8%e1%84%87%e1%85%a7%e1%86%af-dplyr-%e1%84%8c%e1%85%b5%e1%84%8b%e1%85%a7%e1%86%ab\/"},"modified":"2023-07-21T15:00:36","modified_gmt":"2023-07-21T15:00:36","slug":"%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8%e1%84%87%e1%85%a7%e1%86%af-dplyr-%e1%84%8c%e1%85%b5%e1%84%8b%e1%85%a7%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b3%e1%84%85%e1%85%ae%e1%86%b8%e1%84%87%e1%85%a7%e1%86%af-dplyr-%e1%84%8c%e1%85%b5%e1%84%8b%e1%85%a7%e1%86%ab\/","title":{"rendered":"Dplyr\uc744 \uc0ac\uc6a9\ud558\uc5ec \uadf8\ub8f9\ub2f9 \uc624\ud504\uc14b\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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dplyr<\/a> \ud328\ud0a4\uc9c0\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc5d0\uc11c \uadf8\ub8f9 \uc774\ub3d9 \uac12\uc744 \uacc4\uc0b0\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 df %>%\n  group_by(var1) %>%\n  mutate(lag1_value = lag(var2, n= 1<\/span> , order_by=var1))\n<\/strong><\/pre>\n
 \ucc38\uace0<\/strong> : mutate()<\/a> \ud568\uc218\ub294 \uc9c0\uc5f0\ub41c \uac12\uc774 \ud3ec\ud568\ub41c \ub370\uc774\ud130 \ud504\ub808\uc784\uc5d0 \uc0c8 \ubcc0\uc218\ub97c \ucd94\uac00\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc: dplyr\uc744 \uc0ac\uc6a9\ud558\uc5ec \uadf8\ub8f9\ubcc4\ub85c \uc774\ub3d9\ub41c \uac12 \uacc4\uc0b0<\/strong><\/span><\/h3>\n
 \uc11c\ub85c \ub2e4\ub978 \ub0a0\uc9dc\uc5d0 \uc11c\ub85c \ub2e4\ub978 \ub450 \ub9e4\uc7a5\uc758 \ub9e4\ucd9c\uc744 \ubcf4\uc5ec\uc8fc\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \ub370\uc774\ud130 \ud504\ub808\uc784\uc774 R\uc5d0 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (store=c('A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'),\n                 sales=c(7, 12, 10, 9, 9, 11, 18, 23))\n\n#view data frame\n<\/span>df\n\n  blind sales\n1 to 7\n2 B 12\n3 to 10\n4 B 9\n5 to 9\n6 B 11\n7 to 18\n8 B 23<\/strong><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac01 \ub9e4\uc7a5\uc758 \uc9c0\uc5f0\ub41c \ud310\ub9e4 \uac12\uc744 \ud45c\uc2dc\ud558\ub294 \uc0c8 \uc5f4\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 library<\/span> (dplyr)<\/span>\n\n#calculate lagged sales by group\n<\/span>df %>%\n  group_by(store) %>%\n  mutate(lag1_sales = lag(sales, n= 1<\/span> , order_by=store))\n\n# A tibble: 8 x 3\n# Groups: store[2]\n  store sales lag1_sales\n1 to 7 NA\n2 B 12 NA\n3 to 10 7\n4 B 9 12\n5 to 9 10\n6 B 11 9\n7 to 18 9\n8 B 23 11<\/strong><\/pre>\n
 \uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n