Comparing Column names in R across various data frames

Question

I am currently try to compare the column classes and names of various data frames in R prior to undertaking any transformations and calculations. The code I have is noted below::

library(dplyr)
m1 <-  mtcars
m2 <-  mtcars %>% mutate(cyl = factor(cyl), xxxx1 = factor(cyl))
m3 <-  mtcars %>% mutate(cyl = factor(cyl), xxxx2 = factor(cyl))

out <-  cbind(sapply(m1, class), sapply(m2, class), sapply(m3, class))

If someone can solve this for dataframes stored in a list, that would be great. All my dataframes are currently stored in a list, for easier processing.

All.list <- list(m1,m2,m3)

I am expecting that the output is displayed in a matrix form as shown in the dataframe "out". The output in "out" is not desireable as it is incorrect. I am expecting the output to be more along the following::

Answer 1

I think the easiest way would be to define a function, and then use a combination of lapply and dplyr to obtain the result you want. Here is how I did it.

library(dplyr)
m1 <-  mtcars
m2 <-  mtcars %>% mutate(cyl = factor(cyl), xxxx1 = factor(cyl))
m3 <-  mtcars %>% mutate(cyl = factor(cyl), xxxx2 = factor(cyl))

All.list <- list(m1,m2,m3)


##Define a function to get variable names and types
my_function <- function(data_frame){
  require(dplyr)
  x <- tibble(`var_name` = colnames(data_frame),
              `var_type` = sapply(data_frame, class))
  return(x)
}


target <- lapply(1:length(All.list),function(i)my_function(All.list[[i]]) %>% 
mutate(element =i)) %>%
  bind_rows() %>%
  spread(element, var_type)

target