How to group and summarise each data frame in a list of data frames

Question

I have a list of data frames:

df1 <- data.frame(one = c('red','blue','green','red','red','blue','green','green'),
                  one.1 = as.numeric(c('1','1','0','1','1','0','0','0')))

df2 <- data.frame(two = c('red','yellow','green','yellow','green','blue','blue','red'),
                  two.2 = as.numeric(c('0','1','1','0','0','0','1','1')))

df3 <- data.frame(three = c('yellow','yellow','green','green','green','white','blue','white'),
                  three.3 = as.numeric(c('1','0','0','1','1','0','0','1')))

all <- list(df1,df2,df3)

I need to group each data frame by the first column and summarise the second column. Individually I would do something like this:

library(dplyr)

df1 <- df1 %>%
  group_by(one) %>%
  summarise(sum = sum(one.1))

However I'm having trouble figuring out how to iterate over each item in the list.

I've thought of using a loop:

for(i in 1:3){
      all[i] <- all[i] %>%
      group_by_at(1) %>%
      summarise()
}

But I can't figure out how to specify a column to sum in the summarise() function (this loop is likely wrong in other ways than that anyway).

Ideally I need the output to be another list with each item being the summarised data, like so:

[[1]]
# A tibble: 3 x 2
  one     sum
  <fct> <dbl>
1 blue      1
2 green     0
3 red       3

[[2]]
# A tibble: 4 x 2
  two      sum
  <fct>  <dbl>
1 blue       1
2 green      1
3 red        1
4 yellow     1

[[3]]
# A tibble: 4 x 2
  three    sum
  <fct>  <dbl>
1 blue       0
2 green      2
3 white      1
4 yellow     1

Would really appreciate any help!

Answer 1

Using purrr::map and summarise at columns contain a letteral dot \\. using matches helper.

library(dplyr)
library(purrr)
map(all, ~.x %>%
    #group_by_at(vars(matches('one$|two$|three$'))) %>% #column ends with one, two, or three
    group_by_at(1) %>%
    summarise_at(vars(matches('\\.')),sum))
    #summarise_at(vars(matches('\\.')),list(sum=~sum))) #2nd option

[[1]]
# A tibble: 3 x 2
one   one.1
<fct> <dbl>
1 blue      1
2 green     0
3 red       3

[[2]]
# A tibble: 4 x 2
two    two.2
<fct>  <dbl>
1 blue       1
2 green      1
3 red        1
4 yellow     1

[[3]]
# A tibble: 4 x 2
three  three.3
<fct>    <dbl>
1 blue         0
2 green        2
3 white        1
4 yellow       1

Answer 2

Here's a base R solution:

lapply(all, function(DF) aggregate(list(added = DF[, 2]), by = DF[, 1, drop = F], FUN = sum))

[[1]]
    one added
1  blue     1
2 green     0
3   red     3

[[2]]
     two added
1   blue     1
2  green     1
3    red     1
4 yellow     1

[[3]]
   three added
1   blue     0
2  green     2
3  white     1
4 yellow     1

Another approach would be to bind the lists into one. Here I use data.table and avoid using the names. The only problem is that this may mess up factors but I'm not sure that's an issue in your case.

library(data.table)
rbindlist(all, use.names = F, idcol = 'id'
          )[, .(added = sum(one.1)), by = .(id, color = one)]

    id  color added
 1:  1    red     3
 2:  1   blue     1
 3:  1  green     0
 4:  2    red     1
 5:  2 yellow     1
 6:  2  green     1
 7:  2   blue     1
 8:  3 yellow     1
 9:  3  green     2
10:  3  white     1
11:  3   blue     0