I would like to make a custom function of this modified dplyr procedure:
randomly replacing percentage of values per group with NA in R dataframe
library(dplyr)
mtcars %>%
mutate(mpg = replace(mpg, sample(row_number(),
size = ceiling(0.3 * n()), replace = FALSE), NA))
The arguments should be:
- df = dataframe
- x = column
- y = double number (here 0.3)
My approach so far:
my_func <- function(df,x,y){
df %>%
mutate(x = replace({{x}}, sample(row_number(),
size = ceiling(y * n()), replace = FALSE), NA))
}
When applying this function:
my_func(mtcars, mtcars$mpg, 0.3)
#gives:
mpg cyl disp hp drat wt qsec vs am gear carb x
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 21.0
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 NA
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 22.8
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 21.4
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 NA
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 18.1
#....etc..
My question:
- I want to change
mpgcolumn by adding NA’s there, not adding a new columnx - Putting the first
x =in{{x}} =throws an error:
Error: unexpected '=' in:
" df %>%
mutate({{x}} ="
> size = ceiling(y * n()), replace = FALSE), NA))
Error: unexpected ',' in " size = ceiling(y * n()),"
> }
Error: unexpected '}' in "}"
>
>Solution :
This works; does it solve your problem?
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
my_func <- function(df,x,y){
df %>%
mutate({{x}} := replace({{x}}, sample(row_number(),
size = ceiling(y * n()), replace = FALSE), NA))
}
my_func(mtcars, mpg, 0.3)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 NA 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 NA 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> Merc 230 NA 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> Merc 450SE NA 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> Cadillac Fleetwood NA 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> Lincoln Continental NA 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> Chrysler Imperial NA 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona NA 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> Ford Pantera L NA 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> Maserati Bora NA 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
Created on 2021-12-18 by the reprex package (v2.0.1)
From https://adv-r.hadley.nz/quasiquotation.html?q=:=#tidy-dots :
:= is like a vestigial organ: it’s recognised by R’s parser, but it doesn’t have any code associated with it. It looks like an = but allows expressions on either side, making it a more flexible alternative to =. It is used in data.table for similar reasons.