Rsky
December 13, 2021, 7:45am
1
How to specify a column name as a non-character in a function like tidyverse::select.
I'm trying to create a function.
I want to select a specific column in a function.
data %>%
mutate(fct=factor(col_name)) %>%
pull(col_name)
I have tried to create my own function, but I get an error.
ex <- function(data,select) {
data %>%
mutate(fct=factor(col_name)) %>%
pull(col_name)
}
ex(data,col_name)
> x object 'col_name' not found
ex(data,"col_name")
> length(f) == length(.x) is not TRUE
How can I fix it?
ex(data,col_name)
thank you!
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
mtcars %>%
mutate(fct=factor(cyl)) %>%
pull(cyl)
#> [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
ex <- function(DATA,SELECT) {
DATA %>%
mutate(fct=factor(SELECT)) %>%
pull(SELECT)
}
ex(mtcars,"cyl")
#> [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
I have a question even about your original intent, before you move to contain it in a function.
You convert col_name to a factor called fct, and return only the original col_name. It seems therefore that the entire mutate is superfluous, a calculation for no purpose ?
Rsky
December 13, 2021, 10:44am
4
@nirgrahamuk @technocrat
There was a spelling mistake.
data(ames)
my_data <- ames %>%
mutate(chr_Lot_Frontage = as.character(Lot_Frontage))
pull_column <- function(data,col){
data %>%
mutate(int=as.integer(col)) %>%
mutate(col_name = fct_reorder(col,int)) %>%
pull(col_name)
}
pull_column(my_data,chr_Lot_Frontage)
This will result in an error.
Error: Problem with `mutate()` column `int`.
i `int = as.integer(col)`.
x object 'chr_Lot_Frontage' not found
pull_column(my_data,chr_"Lot_Frontage")
Error: Problem with `mutate()` column `col_name`.
i `col_name = fct_reorder(col, int)`.
x length(f) == length(.x)
this code can move collect.
my_data %>%
mutate(int=as.integer(chr_Lot_Frontage)) %>%
mutate(col_name = fct_reorder(chr_Lot_Frontage,int)) %>%
pull(col_name)
library(tidyverse)
library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#> method from
#> required_pkgs.model_spec parsnip
data(ames)
my_data <- ames %>%
mutate(chr_Lot_Frontage = as.character(Lot_Frontage))
pull_column <- function(data,col){
data %>%
mutate(int=as.integer({{col}})) %>%
mutate(col_name = fct_reorder({{col}},int)) %>%
pull(col_name)
}
pull_column(my_data,chr_Lot_Frontage)
#> [1] 141 80 81 93 74 78 41 43 39 60 75 0 63 85 0 47 152 88
#> [19] 140 85 105 85 0 0 0 65 70 70 26 21 21 21 53 24 24 24
#> [37] 102 98 83 94 95 90 79 70 100 44 110 105 61 41 36 100 43 43
#> [55] 67 0 63 0 0 108 60 59 98 92 58 56 73 92 72 75 100 84
#> [73] 76 70 0 50 70 55 50 0 81 70 70 68 88 65 0 75 0 39
#> [91] 107 85 88 25 39 30 30 24 24 0 0 0 24 0 57 68 30 40
#> [109] 0 80 0 80 0 0 80 78 80 80 0 77 90 88 0 0 80 98
#> [127] 68 68 120 50 55 80 80 78 75 80 0 137 70 70 0 70 70 73
#> [145] 0 73 87 80 60 60 119 70 68 65 60 85 74 78 64 0 96 60
#> [163] 75 71 60 87 81 80 70 60 55 56 56 69 60 47 60 50 50 69
#> [181] 0 68 60 60 60 50 100 90 60 60 60 53 0 50 50 50 53 50
#> [199] 52 52 51 50 57 60 52 110 70 76 0 100 72 60 65 0 60 54
#> [217] 72 72 75 0 70 0 65 80 65 0 86 0 80 0 94 60 0 0
#> [235] 124 85 65 68 50 75 83 44 0 60 77 83 87 80 73 64 64 94
#> [253] 64 90 82 80 82 0 70 38 0 75 68 80 0 44 75 48 0 0
#> [271] 48 70 65 67 68 75 60 89 65 94 64 80 52 60 68 67 66 45
#> [289] 50 0 60 51 50 78 78 66 100 85 35 35 100 40 58 50 60 66
#> [307] 66 66 44 85 74 129 0 0 0 88 73 73 92 80 85 89 85 93
#> [325] 94 0 0 31 36 21 21 21 21 50 0 76 70 63 68 76 74 74
#> [343] 85 75 88 0 60 42 0 28 40 61 57 57 74 60 59 0 0 58
#> [361] 0 65 0 0 99 0 63 80 124 85 94 48 85 0 0 80 0 0
#> [379] 80 80 82 80 0 70 75 0 0 0 78 85 78 0 60 0 61 0
#> [397] 0 60 60 70 70 60 21 24 21 21 21 21 0 24 24 24 24 24
#> [415] 24 24 24 24 65 0 96 110 104 105 108 110 98 95 96 95 94 97
#> [433] 105 107 95 129 59 87 87 76 77 102 74 107 85 90 79 103 110 96
#> [451] 70 47 34 34 80 34 100 117 44 48 129 48 48 36 63 57 149 122
#> [469] 53 51 43 43 43 43 71 0 59 62 0 61 0 0 34 0 0 0
#> [487] 61 60 42 62 0 0 0 64 82 174 106 0 98 79 0 90 79 0
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#> [559] 0 0 80 60 65 0 0 32 40 30 0 0 34 34 35 24 0 61
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#> [595] 80 70 80 0 0 60 65 70 0 0 85 100 85 115 0 0 0 80
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#> [631] 73 70 0 66 80 66 70 70 80 120 74 76 53 79 67 60 75 80
#> [649] 60 75 107 78 60 50 53 60 60 80 52 60 60 60 90 90 60 60
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#> [1261] 70 78 76 0 0 313 74 60 60 70 80 80 70 60 64 59 60 113
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#> [1315] 60 60 60 35 50 0 75 60 60 65 81 70 52 55 0 50 0 50
#> [1333] 50 59 50 50 50 50 50 50 60 99 52 0 52 52 51 51 60 60
#> [1351] 50 64 60 60 0 55 57 0 63 0 60 60 0 60 62 0 49 60
#> [1369] 60 60 60 82 55 115 80 62 0 70 80 0 68 57 0 0 0 60
#> [1387] 60 0 0 94 88 0 0 85 60 0 63 0 0 83 82 73 0 124
#> [1405] 50 85 75 85 66 120 68 50 50 50 70 68 60 60 86 0 80 0
#> [1423] 85 65 65 91 91 59 0 0 79 65 75 57 0 0 68 68 57 93
#> [1441] 88 80 75 68 0 65 0 0 0 40 88 60 60 75 75 0 0 73
#> [1459] 75 0 0 0 0 65 41 72 96 70 37 0 75 83 70 65 75 65
#> [1477] 64 85 85 74 63 0 0 0 0 67 67 75 75 64 65 63 90 60
#> [1495] 0 72 60 123 313 35 65 65 92 74 56 60 57 68 70 60 59 62
#> [1513] 67 67 45 55 0 60 60 60 55 51 64 66 79 63 63 52 54 51
#> [1531] 0 60 74 0 0 79 100 0 0 70 56 0 24 24 50 60 40 0
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#> [1585] 0 85 79 85 97 78 77 32 150 0 0 41 21 21 0 21 21 100
#> [1603] 59 37 60 60 60 75 74 0 0 85 85 95 95 0 0 0 57 56
#> [1621] 41 0 0 63 63 60 0 0 0 0 160 0 0 38 35 86 98 52
#> [1639] 195 61 60 85 81 0 0 78 78 93 61 92 0 0 79 80 80 80
#> [1657] 128 70 90 0 64 80 70 0 0 63 66 61 70 0 0 60 34 33
#> [1675] 26 21 21 21 24 24 0 24 24 65 96 90 93 91 93 110 107 107
#> [1693] 110 105 109 107 110 105 98 110 118 59 134 76 82 86 94 99 99 110
#> [1711] 93 0 70 71 92 61 34 34 41 34 34 44 48 60 68 48 48 59
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#> [1801] 84 84 84 100 85 102 63 63 60 65 70 0 65 0 50 50 0 60
#> [1819] 64 80 70 0 85 40 84 0 0 0 0 44 0 43 0 85 45 80
#> [1837] 32 47 40 30 35 35 24 34 0 24 0 0 24 66 73 0 106 50
#> [1855] 80 0 90 40 80 80 94 0 0 78 80 0 130 108 80 78 0 88
#> [1873] 80 80 70 0 79 0 0 0 0 0 80 65 70 74 0 0 76 70
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#> [1909] 79 79 63 0 100 70 78 0 73 65 60 70 75 80 90 70 80 72
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#> [2053] 65 0 70 99 0 70 86 0 66 109 71 0 81 99 0 70 91 85
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#> [2791] 0 45 0 0 70 0 67 0 90 90 75 70 37 37 120 70 41 70
#> [2809] 74 70 84 89 65 68 65 65 67 134 67 38 35 73 62 75 90 35
#> [2827] 35 35 24 24 24 24 32 56 72 62 58 60 60 60 45 45 60 60
#> [2845] 76 0 60 60 58 43 96 69 60 54 54 84 51 60 66 0 80 80
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#> [2899] 0 85 95 88 88 125 78 32 32 90 41 41 42 58 0 21 21 80
#> [2917] 21 21 21 21 21 55 63 80 160 37 0 62 77 74
#> 129 Levels: 0 21 22 24 25 26 28 30 31 32 33 34 35 36 37 38 39 40 41 42 43 ... 313
Created on 2021-12-13 by the reprex package (v2.0.1)
Look at rlang:
1 Like
system
January 3, 2022, 12:20pm
6
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