r - Rename column of dataframes inside a list with its dataframe name -

i have multiple dataframes/tibbles same exact structure, different contents. name way can differentiate them. objective merge them 1 dataframe, factor column. original dataframes have 1 column each hour/measurement, first want gather everything.

imagine columns 5 11 of mtcars df hour columns.

mt1 <- mtcars mt2 <- mtcars mt3 <- mtcars mt4 <- mtcars  mtlist <- list(m1 = mt1,                m2 = mt2,                m3 = mt3,                m4 = mt4)  require(tidyverse)  mtlist_tidy <- lapply(mtlist, function(x){   df <- x %>%     gather(exp, temp_name, 5:11)    return(df) }) 

now i'm stuck. need rename "temp_name" column in each of dfs inside mtlist_tidy name of df i.e. m1, m2, etc:

> head(mtlist_tidy$m1)    mpg cyl disp  hp  exp temp_name 1 21.0   6  160 110 drat      3.90 2 21.0   6  160 110 drat      3.90 3 22.8   4  108  93 drat      3.85 4 21.4   6  258 110 drat      3.08 5 18.7   8  360 175 drat      3.15 6 18.1   6  225 105 drat      2.76 

should become

> head(mtlist_tidy$m1)    mpg cyl disp  hp  exp      m1 1 21.0   6  160 110 drat      3.90 2 21.0   6  160 110 drat      3.90 3 22.8   4  108  93 drat      3.85 4 21.4   6  258 110 drat      3.08 5 18.7   8  360 175 drat      3.15 6 18.1   6  225 105 drat      2.76 

then purrr::reduce(mtlist_tidy, full_join) work, completing task.

i guess there must solution using purrr , skipping lapply, i'm not familiar yet package.

a couple of ideas:

first, approach problem current use map2 loop through both list , names of list simultaneously. can name new columns go list names via gather_(for standard evaluation).

map2(mtlist, names(mtlist), ~gather_(.x, "exp", .y, names(.x)[5:11]) ) 

note next version of purrr have imap short-cut looping through list , names of list. also, next version of tidyr use tidyeval , gather_ deprecated.

second, keep things in long format using map_df looping instead of lapply. map_df uses bind_rows @ end under hood, , can include grouping variable each list via .id argument.

mtlist %>%     map_df(~.x %>% gather("exp", "temp_name", 5:11), .id = "name" ) 

to put dataset in wide format here can use spread. takes little more work in example because of identifying variables hp , disp have same value across multiple rows.

mtlist %>%     map_df(~.x %>% gather("exp", "temp_name", 5:11), .id = "name" ) %>%     group_by(name) %>%     mutate( rows = 1:n() ) %>%     spread(name, temp_name)