I am trying to calculate rowwise averages for a number of columns. Could somebody please explain why the code below only calculates the mean for the two variables in the code (var_1 and var_13), rather than the mean for all 13 columns?
df %>%
rowwise() %>%
mutate(varmean = mean(var_1:var_13)) -> df
Two possibilities using dplyr:
library(dplyr)
mtcars %>%
rowwise() %>%
mutate(varmean = mean(c_across(mpg:vs)))
This returns
# A tibble: 32 x 12
# Rowwise:
mpg cyl disp hp drat wt qsec vs am gear carb varmean
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 40.0
2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 40.1
3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 31.7
4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 52.8
5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 73.2
6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 47.7
7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 81.2
8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 33.1
9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 36.7
10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 42.8
# ... with 22 more rows
and without rowwise() and using base Rs rowMeans():
mtcars %>%
mutate(varmean = rowMeans(across(mpg:vs)))
returns
mpg cyl disp hp drat wt qsec vs am gear carb varmean
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 39.99750
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 40.09938
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 31.69750
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 52.76687
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 73.16375
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 47.69250
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 81.24000
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 33.12250
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 36.69625
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 42.80750