r - Pass column name to function from mutate_each -

i'd apply transformation columns via dplyr::mutate_each, e.g.

library(dplyr) mult <- function(x,m) return(x*m) mtcars %>% mutate_each(funs(mult(.,2)))    # multiply columns factor of 2 

however, transformation should have parameters depending on column name. therefore, column name should passed function additional argument

named.mult <- function(x,colname) return(x*param.a[[colname]]) 

example: multiply every column different factor:

param.a <- c() param.a[names(mtcars)] <- seq(length(names(mtcars))) param.a # mpg  cyl disp   hp drat   wt qsec   vs   gear carb  #   1    2    3    4    5    6    7    8    9   10   11  

since column name gets lost during mutate_each, work around passing list lazy evalution mutate_ (the se version):

library(lazyeval) named.mutate <- function(fun, cols) sapply(cols, function(n) interp(~fun(col, n), fun=fun, col=as.name(n))) mtcars %>% mutate_(.dots=named.mutate(named.mult, names(.))) 

works, there special variable .name contains column name of . each colwise execution? like

mtcars %>% mutate_each(funs(named.mult(.,.name))) 

i'd suggest taking different approach. instead of using mutate_each combination of dplyr::mutate tidyr::gather , tidyr::spread can achieve same result.

for example:

library(dplyr) library(tidyr)  data(mtcars)  # multiple each column different interger mtcars %>%    dplyr::tbl_df() %>%   dplyr::mutate(make_and_model = rownames(mtcars)) %>%   tidyr::gather(key, value, -make_and_model) %>%    dplyr::mutate(m = as.integer(factor(key)),   # multiplication factor dependent on column name                 value = value * m) %>%    dplyr::select(-m) %>%   tidyr::spread(key, value)  # compare original data mtcars[order(rownames(mtcars)), order(names(mtcars))]  # muliplicative values used. mtcars %>%    tidyr::gather() %>%    dplyr::mutate(m = as.integer(factor(key))) %>%    dplyr::select(-value) %>%   dplyr::distinct()