map glimpse to list containing dataframes-CodePudding

I have two tibbles and I am trying to apply the glimpse() function to each tibble. It can be done easily using for loops. But I am wondering how to do it using map() or other similar functions.

df1 <- tibble(A = c(1,1,1), B = c(2,2,2))  
df2 <- tibble(C = c(3,3,3), D = c(4,4,4))

dfs = list(df1, df2)

I want this:

for (df in dfs) {
  glimpse(df)
}

# Rows: 3
# Columns: 2
# $ A <dbl> 1, 1, 1
# $ B <dbl> 2, 2, 2
# Rows: 3
# Columns: 2
# $ C <dbl> 3, 3, 3
# $ D <dbl> 4, 4, 4

But map does this:

map(dfs, glimpse)

# Rows: 3
# Columns: 2
# $ A <dbl> 1, 1, 1
# $ B <dbl> 2, 2, 2
# Rows: 3
# Columns: 2
# $ C <dbl> 3, 3, 3
# $ D <dbl> 4, 4, 4
# [[1]]
# # A tibble: 3 × 2
# A     B
# <dbl> <dbl>
#   1     1     2
# 2     1     2
# 3     1     2
# 
# [[2]]
# # A tibble: 3 × 2
# C     D
# <dbl> <dbl>
#   1     3     4
# 2     3     4
# 3     3     4

CodePudding user response：

map() always returns a list, even if the applied function returns silently or NULL. walk() is like map() but only executes the supplied function for side effects:

library(tidyverse)
df1 <- tibble(A = c(1,1,1), B = c(2,2,2))  
df2 <- tibble(C = c(3,3,3), D = c(4,4,4))

dfs = list(df1, df2)


walk(dfs, glimpse)
#> Rows: 3
#> Columns: 2
#> $ A <dbl> 1, 1, 1
#> $ B <dbl> 2, 2, 2
#> Rows: 3
#> Columns: 2
#> $ C <dbl> 3, 3, 3
#> $ D <dbl> 4, 4, 4

^{Created on 2022-07-31 by the reprex package (v2.0.1)}

CodePudding user response：

Why not

library(dplyr)

dfs %>% 
  glimpse()

List of 2
 $ : tibble [3 x 2] (S3: tbl_df/tbl/data.frame)
  ..$ A: num [1:3] 1 1 1
  ..$ B: num [1:3] 2 2 2
 $ : tibble [3 x 2] (S3: tbl_df/tbl/data.frame)
  ..$ C: num [1:3] 3 3 3
  ..$ D: num [1:3] 4 4 4