How to save each named tibble in a list, as a separate tibble or dataframe in one run-CodePudding

This question is related to this How to loop over the columns in a dataframe, apply spread, and create a new dataframe in R?

I have a list with 3 tibbles:

$Peter
# A tibble: 3 x 4
  date       Peter   Ben  Mary
  <chr>      <dbl> <dbl> <dbl>
1 2020-03-30   0.4  NA    NA  
2 2020-10-14  NA     0.6  NA  
3 2020-12-06  NA    NA     0.7

$Ben
# A tibble: 3 x 4
  date       Peter   Ben  Mary
  <chr>      <dbl> <dbl> <dbl>
1 2020-03-30   0.5  NA    NA  
2 2020-10-14  NA     0.4  NA  
3 2020-12-06  NA    NA     0.2

$Mary
# A tibble: 3 x 4
  date       Peter   Ben  Mary
  <chr>      <dbl> <dbl> <dbl>
1 2020-03-30   0.2  NA    NA  
2 2020-10-14  NA     0.1  NA  
3 2020-12-06  NA    NA     0.9

mylistdf <- list(Peter = structure(list(date = c("2020-03-30", "2020-10-14", 
"2020-12-06"), Peter = c(0.4, NA, NA), Ben = c(NA, 0.6, NA), 
    Mary = c(NA, NA, 0.7)), row.names = c(NA, -3L), class = c("tbl_df", 
"tbl", "data.frame")), Ben = structure(list(date = c("2020-03-30", 
"2020-10-14", "2020-12-06"), Peter = c(0.5, NA, NA), Ben = c(NA, 
0.4, NA), Mary = c(NA, NA, 0.2)), row.names = c(NA, -3L), class = c("tbl_df", 
"tbl", "data.frame")), Mary = structure(list(date = c("2020-03-30", 
"2020-10-14", "2020-12-06"), Peter = c(0.2, NA, NA), Ben = c(NA, 
0.1, NA), Mary = c(NA, NA, 0.9)), row.names = c(NA, -3L), class = c("tbl_df", 
"tbl", "data.frame")))

How can I save all this 3 tibbles as an own tibble in the global environment:

Expected output would be kind of having Peter, Ben, Mary as tibbles or dataframes in the global environment.

I know we could do:

Peter <- mylistdf$Peter
Ben <- mylistdf$Ben
Mary <- mylistdf$Mary

But I whish to do it in one run with map or similar like:

mylistdf %>%
  .....

CodePudding user response：

You can do this:

list2env(mylistdf,envir = .GlobalEnv)

but it is often recommended to keep your frames/tibbles in the original list.

CodePudding user response：

We could use %=%

library(collapse)
names(mylistdf) %=% mylistdf

-checking

> Peter
# A tibble: 3 × 4
  date       Peter   Ben  Mary
  <chr>      <dbl> <dbl> <dbl>
1 2020-03-30   0.4  NA    NA  
2 2020-10-14  NA     0.6  NA  
3 2020-12-06  NA    NA     0.7
> Mary
# A tibble: 3 × 4
  date       Peter   Ben  Mary
  <chr>      <dbl> <dbl> <dbl>
1 2020-03-30   0.2  NA    NA  
2 2020-10-14  NA     0.1  NA  
3 2020-12-06  NA    NA     0.9