Looping through data frames in global environment and passing a function to all to create new list-CodePudding

I have 125 89x89 dataframes in my global environment and need to turn each into a into 1 x 7921 (i.e., 89^2) dataframe and then bind them into a single 125 x 7921 DataFrame. I'm having success getting the dataframes from independent objects in the global environment into a list using mget:

For example,

dfs_list <- Filter(function(x) is(x, "data.frame"), mget(ls()))

returns a list of 125 89x89 dataframes in df_list.

Where I might be messing up and where I've struggled the most is writing a function for the lapply call. I'm trying to use

list1 <- lapply(mget(ls()), f1)

where f1 is the function I need to call to transform the data from long to wide for each DataFrame.

The function I am trying to use is

f1 <- function(data.frame) {
   . %>%
   dplyr::mutate(dplyr::mutate(row = row_number()) %>% 
   tidyr::pivot_wider(names_from = row, values_from = -row)
}

which stems from a previous question I asked here. The code within the function works perfectly when I pass just one DataFrame at a time, but seeing as this is a large dataset that is going to continue to expand and need to be pivoted, it would be nice to have a function to automate the process.

The output of running list1 <- lapply(mget(ls()), f1) on the objects in my global environment is a list of 125 functions. What I am trying to get is an output list length of 125 with the wide dataframes.

Thanks for any help.

CodePudding user response：

I've figured out the issue was with my function f1 and mget(ls()) in lapply. Here's what worked to solve the problem:

dfs_list <- Filter(function(x) is(x, "data.frame"), mget(ls()))

f1 <- function(df) { 
   df %>% 
     dplyr::mutate(dplyr::mutate(row = row_number()) %>% 
     tidyr::pivot_wider(names_from = row, values_from = -row)
}

lst1 <- lapply(dfs_list, f1)