dplyr group_by and mutate, how to access the data frame?

Question

When using dplyr\'s \"group_by\" and \"mutate\", if I understand correctly, the data frame is split in different sub-dataframes according to the group_by argument. For examp

Answer 1

Since dplyr 0.8 you can use group_map, the . in the group_map call will represent the sub-data.frame. Its behavior has changed a bit with time, with dplyr 1.0 we can do

df <- data.frame(x=runif(10),let=rep(letters[1:5],each=2))
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
df %>%   
  group_by(let) %>%
  group_map(~mutate(., mean.by.letter = mean(x)), .keep = T) %>%  
  bind_rows()
#> # A tibble: 10 x 3
#>         x let   mean.by.letter
#>     <dbl> <chr>          <dbl>
#>  1 0.442  a              0.271
#>  2 0.0999 a              0.271
#>  3 0.669  b              0.343
#>  4 0.0167 b              0.343
#>  5 0.908  c              0.575
#>  6 0.242  c              0.575
#>  7 0.685  d              0.378
#>  8 0.0716 d              0.378
#>  9 0.883  e              0.843
#> 10 0.804  e              0.843

group_map() was introduced there (with now outdated behavior!):

https://www.tidyverse.org/articles/2019/02/dplyr-0-8-0/ https://www.tidyverse.org/articles/2018/12/dplyr-0-8-0-release-candidate/

Answer 2

We can use within do

data %>%
    group_by(let ) %>% 
    do(mutate(., mean.by.letter = mean(.$x)))