combining common columns in a list in R

I have an list object like below.

df1 <- data_frame(ID = paste0(LETTERS[1],1:4), valueA = seq(0.1,0.4,0.1), Category= "Apples", valueDEF = seq(0.1,0.4,0.1), valueDEF2 = seq(0.1,0.4,0.1) )
df2 <- data_frame(ID = paste0(LETTERS[1],5:8), valueB = seq(0.1,0.4,0.1),  Category= "Apples2")
df3 <- data_frame(ID = paste0(LETTERS[1],9:12), valueC = seq(0.1,0.4,0.1),  Category= "Apples3")

list1 <- list(df1, df2, df3);list1



  [[1]]
# A tibble: 4 × 5
  ID    valueA Category valueDEF valueDEF2
  <chr>  <dbl> <chr>       <dbl>     <dbl>
1 A1       0.1 Apples        0.1       0.1
2 A2       0.2 Apples        0.2       0.2
3 A3       0.3 Apples        0.3       0.3
4 A4       0.4 Apples        0.4       0.4

[[2]]
# A tibble: 4 × 3
  ID    valueB Category
  <chr>  <dbl> <chr>   
1 A5       0.1 Apples2 
2 A6       0.2 Apples2 
3 A7       0.3 Apples2 
4 A8       0.4 Apples2 

[[3]]
# A tibble: 4 × 3
  ID    valueC Category
  <chr>  <dbl> <chr>   
1 A9       0.1 Apples3 
2 A10      0.2 Apples3 
3 A11      0.3 Apples3 
4 A12      0.4 Apples3

And I would like to merge them into 1 data frame based on the common column names.

Expected Answer

ID Category
A1  Apples 
A2  Apples 
A3  Apples 
A4  Apples 
A5  Apples2 
A6  Apples2
A7  Apples2
A8  Apples2 
A9  Apples3 
A10 Apples3 
A11 Apples3 
A12 Apples3

How to get around this? Many thanks in advance.

Solution

We could use intersect().

For this we apply colnames to each data frame in the list with lapply().
The resulting list is then passed to Reduce() with the intersect() function.
Finally we use bind_rows() to get a single data frame:

library(dplyr) #bind_rows()

common_cols <- Reduce(intersect, lapply(list1, colnames))
df_all <- bind_rows(list1)[common_cols]

 ID    Category
   <chr> <chr>   
 1 A1    Apples  
 2 A2    Apples  
 3 A3    Apples  
 4 A4    Apples  
 5 A5    Apples2 
 6 A6    Apples2 
 7 A7    Apples2 
 8 A8    Apples2 
 9 A9    Apples3 
10 A10   Apples3 
11 A11   Apples3 
12 A12   Apples3