How to do summarise_all with values filter irrespective to the column

Question

I have 5 columns in which I'd like to group by a column and then summarize as mean per columns. However, in the process, I'd like to only calculate the mean for values between a certain range for all the columns. Is this possible? Not excluding the rows themselves but the values to be aggregated.

Current code:

a <- b %>% group_by(c) %>% summarise_all(funs(mean(., na.rm=T)))

Answer 1

If you want to use only a subset of data to compute the mean on, you can use a lambda function inside summarise() .

However, if the subset is based on only one variable, you should simply use filter() .

Also, note that summarise_all() is retired and we should use summarise(across()) instead.

Here is an example where the mean is computed with only values included between 2 and 3 .

library(tidyverse)
iris %>% 
  group_by(Species) %>% 
  summarise(across(everything(), ~mean(.x, na.rm=TRUE)))
#> # A tibble: 3 x 5
#>   Species    Sepal.Length Sepal.Width Petal.Length Petal.Width
#>   <fct>             <dbl>       <dbl>        <dbl>       <dbl>
#> 1 setosa             5.01        3.43         1.46       0.246
#> 2 versicolor         5.94        2.77         4.26       1.33 
#> 3 virginica          6.59        2.97         5.55       2.03

my_range = c(inf=2, sup=3)
iris %>% 
  group_by(Species) %>% 
  summarise(across(everything(), ~.x[.x>my_range["inf"] & .x<my_range["sup"]] %>% mean(na.rm=TRUE)))
#> # A tibble: 3 x 5
#>   Species    Sepal.Length Sepal.Width Petal.Length Petal.Width
#>   <fct>             <dbl>       <dbl>        <dbl>       <dbl>
#> 1 setosa              NaN        2.60          NaN      NaN   
#> 2 versicolor          NaN        2.63          NaN      NaN   
#> 3 virginica           NaN        2.69          NaN        2.27

^{Created on 2021-05-12 by the reprex package (v2.0.0)}