FCT_Collapse 使用范围
FCT_Collapse using a range
我正在尝试使用范围 (160:280) 而不是“160”、“161”等。我该怎么做?
group_by(disp = fct_collapse(as.character(disp), Group1 = c(160:280), Group2 = c(281:400)) %>%
summarise(meanHP = mean(hp)))
Error: Problem adding computed columns in `group_by()`.
x Problem with `mutate()` column `disp`.
i `disp = `%>%`(...)`.
x Each input to fct_recode must be a single named string. Problems at positions: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 17```
对于值的范围,最好使用 cut
,您可以在其中定义 breaks
和 labels
。
library(dplyr)
library(forcats)
mtcars %>%
group_by(disp = cut(disp, c(0, 160, 280, 400, Inf), paste0('Group', 1:4))) %>%
summarise(meanHP = mean(hp))
# disp meanHP
# <fct> <dbl>
#1 Group1 93.1
#2 Group2 143
#3 Group3 217.
#4 Group4 217.
所以这里0-160变成了'Group1'
,160-280变成了'Group2'
等等。
使用 fct_collapse
你可以做到 -
mtcars %>%
group_by(disp = fct_collapse(as.character(disp), Group1 = as.character(160:280), Group2 = as.character(281:400))) %>%
summarise(meanHP = mean(hp)) %>%
suppressWarnings()
但是,这仅适用于存在的确切值,因此 160 将在 group1 中,但不是 160.1。
我们也可以
library(dplyr)
library(stringr)
mtcars %>%
group_by(disp = cut(disp, c(0, 160, 280, 400, Inf), strc('Group', 1:4))) %>%
summarise(meanHP = mean(hp))
我正在尝试使用范围 (160:280) 而不是“160”、“161”等。我该怎么做?
group_by(disp = fct_collapse(as.character(disp), Group1 = c(160:280), Group2 = c(281:400)) %>%
summarise(meanHP = mean(hp)))
Error: Problem adding computed columns in `group_by()`.
x Problem with `mutate()` column `disp`.
i `disp = `%>%`(...)`.
x Each input to fct_recode must be a single named string. Problems at positions: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 17```
对于值的范围,最好使用 cut
,您可以在其中定义 breaks
和 labels
。
library(dplyr)
library(forcats)
mtcars %>%
group_by(disp = cut(disp, c(0, 160, 280, 400, Inf), paste0('Group', 1:4))) %>%
summarise(meanHP = mean(hp))
# disp meanHP
# <fct> <dbl>
#1 Group1 93.1
#2 Group2 143
#3 Group3 217.
#4 Group4 217.
所以这里0-160变成了'Group1'
,160-280变成了'Group2'
等等。
使用 fct_collapse
你可以做到 -
mtcars %>%
group_by(disp = fct_collapse(as.character(disp), Group1 = as.character(160:280), Group2 = as.character(281:400))) %>%
summarise(meanHP = mean(hp)) %>%
suppressWarnings()
但是,这仅适用于存在的确切值,因此 160 将在 group1 中,但不是 160.1。
我们也可以
library(dplyr)
library(stringr)
mtcars %>%
group_by(disp = cut(disp, c(0, 160, 280, 400, Inf), strc('Group', 1:4))) %>%
summarise(meanHP = mean(hp))