Replacing values across a data frame's variables from a list of nested data frames












1















Let's presume I have the following dataframe:



df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))


And I would like to replace the values in the variables by their corresponding data frame and variable names in the following list:



replace_df <- list(x = data.frame(x = 1:10), 
y = data.frame(y = 11:20),
z = data.frame(z = 21:30))


How would I do that using dplyr?



I feel like my issue is related to this Q&A, but I haven't been able to implement the answers to that question correctly to my situation.



I've attempted the below, among others, without success:



library(tidyverse)
variables <- c("x", "y", "z")

df %>%
mutate_at(vars(variables), funs(replace_df[[.]][[.]]))


The "dumb" way would be the following:



df %>% 
mutate(x = replace_df[["x"]][["x"]],
y = replace_df[["y"]][["y"]],
z = replace_df[["z"]][["z"]])









share|improve this question



























    1















    Let's presume I have the following dataframe:



    df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))


    And I would like to replace the values in the variables by their corresponding data frame and variable names in the following list:



    replace_df <- list(x = data.frame(x = 1:10), 
    y = data.frame(y = 11:20),
    z = data.frame(z = 21:30))


    How would I do that using dplyr?



    I feel like my issue is related to this Q&A, but I haven't been able to implement the answers to that question correctly to my situation.



    I've attempted the below, among others, without success:



    library(tidyverse)
    variables <- c("x", "y", "z")

    df %>%
    mutate_at(vars(variables), funs(replace_df[[.]][[.]]))


    The "dumb" way would be the following:



    df %>% 
    mutate(x = replace_df[["x"]][["x"]],
    y = replace_df[["y"]][["y"]],
    z = replace_df[["z"]][["z"]])









    share|improve this question

























      1












      1








      1








      Let's presume I have the following dataframe:



      df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))


      And I would like to replace the values in the variables by their corresponding data frame and variable names in the following list:



      replace_df <- list(x = data.frame(x = 1:10), 
      y = data.frame(y = 11:20),
      z = data.frame(z = 21:30))


      How would I do that using dplyr?



      I feel like my issue is related to this Q&A, but I haven't been able to implement the answers to that question correctly to my situation.



      I've attempted the below, among others, without success:



      library(tidyverse)
      variables <- c("x", "y", "z")

      df %>%
      mutate_at(vars(variables), funs(replace_df[[.]][[.]]))


      The "dumb" way would be the following:



      df %>% 
      mutate(x = replace_df[["x"]][["x"]],
      y = replace_df[["y"]][["y"]],
      z = replace_df[["z"]][["z"]])









      share|improve this question














      Let's presume I have the following dataframe:



      df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))


      And I would like to replace the values in the variables by their corresponding data frame and variable names in the following list:



      replace_df <- list(x = data.frame(x = 1:10), 
      y = data.frame(y = 11:20),
      z = data.frame(z = 21:30))


      How would I do that using dplyr?



      I feel like my issue is related to this Q&A, but I haven't been able to implement the answers to that question correctly to my situation.



      I've attempted the below, among others, without success:



      library(tidyverse)
      variables <- c("x", "y", "z")

      df %>%
      mutate_at(vars(variables), funs(replace_df[[.]][[.]]))


      The "dumb" way would be the following:



      df %>% 
      mutate(x = replace_df[["x"]][["x"]],
      y = replace_df[["y"]][["y"]],
      z = replace_df[["z"]][["z"]])






      r dplyr rlang






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 21 '18 at 21:35









      PhilPhil

      1,774628




      1,774628
























          1 Answer
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          2














          You need to use expr! I am not sure if the subsetting will work as you tried above, but I was able to get the correct output by making a simple function and passing in an argument that was wrapped in expr()



          df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))

          replace_df <- list(x = data.frame(x = 1:10),
          y = data.frame(y = 11:20),
          z = data.frame(z = 21:30))

          my_func <- function(string) {

          return(
          replace_df[[string]][[string]]
          )

          }

          df %>%
          mutate_at(vars(x, y, z), funs(my_func(expr(.))))





          share|improve this answer























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            1 Answer
            1






            active

            oldest

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            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            2














            You need to use expr! I am not sure if the subsetting will work as you tried above, but I was able to get the correct output by making a simple function and passing in an argument that was wrapped in expr()



            df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))

            replace_df <- list(x = data.frame(x = 1:10),
            y = data.frame(y = 11:20),
            z = data.frame(z = 21:30))

            my_func <- function(string) {

            return(
            replace_df[[string]][[string]]
            )

            }

            df %>%
            mutate_at(vars(x, y, z), funs(my_func(expr(.))))





            share|improve this answer




























              2














              You need to use expr! I am not sure if the subsetting will work as you tried above, but I was able to get the correct output by making a simple function and passing in an argument that was wrapped in expr()



              df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))

              replace_df <- list(x = data.frame(x = 1:10),
              y = data.frame(y = 11:20),
              z = data.frame(z = 21:30))

              my_func <- function(string) {

              return(
              replace_df[[string]][[string]]
              )

              }

              df %>%
              mutate_at(vars(x, y, z), funs(my_func(expr(.))))





              share|improve this answer


























                2












                2








                2







                You need to use expr! I am not sure if the subsetting will work as you tried above, but I was able to get the correct output by making a simple function and passing in an argument that was wrapped in expr()



                df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))

                replace_df <- list(x = data.frame(x = 1:10),
                y = data.frame(y = 11:20),
                z = data.frame(z = 21:30))

                my_func <- function(string) {

                return(
                replace_df[[string]][[string]]
                )

                }

                df %>%
                mutate_at(vars(x, y, z), funs(my_func(expr(.))))





                share|improve this answer













                You need to use expr! I am not sure if the subsetting will work as you tried above, but I was able to get the correct output by making a simple function and passing in an argument that was wrapped in expr()



                df <- data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10))

                replace_df <- list(x = data.frame(x = 1:10),
                y = data.frame(y = 11:20),
                z = data.frame(z = 21:30))

                my_func <- function(string) {

                return(
                replace_df[[string]][[string]]
                )

                }

                df %>%
                mutate_at(vars(x, y, z), funs(my_func(expr(.))))






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 21 '18 at 22:31









                buchmaynebuchmayne

                10917




                10917
































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