converting multiple columns from character to numeric format in r

Question

What is the most efficient way to convert multiple columns in a data frame from character to numeric format   I have a dataframe called DF with all character variables   I would like to do something like  for  i in names DF       DF i  lt - as numeric DF i      Thank you

User · Answer

type convert   Convert a data object to logical  integer  numeric  complex  character or factor as appropriate  Add the as is argument type convert df as is   T  to prevent character vectors from becoming factors when there is a non-numeric in the data set  See

User · Answer

like this   DF  lt - data frame  a    as character 0 5                 b    paste 0 5    1   sep                      c    paste 10 15                stringsAsFactors   FALSE   DF  lt - apply DF  2  as numeric    If there are  real  characters in dataframe like  a   b   c   i would recommend answer from davsjob

User · Answer

I used this code to convert all columns to numeric except the first one      library dplyr        check structure  row and column number with  glimpse df        convert to numeric e g  from 2nd column to 10th column     df  lt - df   gt         mutate at c 2 10   as numeric

User · Answer

I think I figured it out  Here s what I did  perhaps not the most elegant solution - suggestions on how to imp rove this are very much welcome    names of columns in data frame cols  lt - names DF    character variables cols char  lt - c  fx code   date    numeric variables cols num  lt - cols  cols  in  cols char   DF char  lt - DF cols char  DF num  lt - as data frame lapply DF cols num  as numeric   DF2  lt - cbind DF char  DF num

User · Answer

If you re already using the tidyverse  there are a few solution depending on the exact situation  Basic if you know it s all numbers and doesn t have NAs library dplyr     solution dataset   gt   mutate if is character as numeric   Test cases df  lt - data frame    x1   c  1   2   3      x2   c  4   5   6      x3   c  1   a   x      vector with alpha characters   x4   c  1  NA  6      numeric and NA   x5   c  1  NA  x      alpha and NA   stringsAsFactors   F     display starting structure df   gt   str    Convert all character vectors to numeric  could fail if not numeric  df   gt     select -x3    gt     this removes the alpha column if all your character columns need converted to numeric   mutate if is character as numeric    gt     str    Check if each column can be converted  This can be an anonymous function  It returns FALSE if there is a non-numeric or non-NA character somewhere  It also checks if it s a character vector to ignore factors  na omit removes original NAs before creating  quot bad quot  NAs  is all numeric  lt - function x       any is na suppressWarnings as numeric na omit x       amp  is character x    df   gt      mutate if is all numeric as numeric    gt     str    If you want to convert specific named columns  then mutate at is better  df   gt   mutate at  x1   as numeric    gt   str

User · Answer

You can use index of columns  data set  1 9   lt - sapply dataset  1 9  as character

User · Answer

Slight adjustment to answers from ARobertson and Kenneth Wilson that worked for me   Running R 3 6 0  with library tidyverse  and library dplyr  in my environment   library tidyverse  library dplyr   gt  df   lt  gt   mutate if is character  as numeric  Error in df   lt  gt   mutate if is character  as numeric       could not find function    lt  gt      I did some quick research and found this note in Hadley s  The tidyverse style guide        The magrittr package provides the   lt    operator as a shortcut for modifying an object in place  Avoid this operator     Good x  lt - x   gt              abs     gt                  sort      Bad x   lt  gt                abs     gt             sort        Solution  Based on that style guide   df clean  lt - df   gt   mutate if is character  as numeric      Working example   gt  df clean  lt - df   gt   mutate if is character  as numeric  Warning messages  1  NAs introduced by coercion  2  NAs introduced by coercion  3  NAs introduced by coercion  4  NAs introduced by coercion  5  NAs introduced by coercion  6  NAs introduced by coercion  7  NAs introduced by coercion  8  NAs introduced by coercion  9  NAs introduced by coercion  10  NAs introduced by coercion   gt  df clean   A tibble  3 599 x 17    stack datetime            volume BQT90 DBT90 DRT90 DLT90 FBT90  RT90 HTML90 RFT90 RLPP90 RAT90 SRVR90 SSL90 TCP90 group     lt dbl gt   lt dttm gt                 lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt    lt dbl gt   lt dbl gt    lt dbl gt   lt dbl gt    lt dbl gt   lt dbl gt   lt dbl gt   lt dbl gt

User · Answer

for  i in 1 names DF       DF  i    lt - as numeric DF  i       I solved this using double brackets

User · Answer

You could try  DF  lt - data frame  a    as character 0 5                     b    paste 0 5    1   sep                          c    letters 1 6                    stringsAsFactors   FALSE     Check columns classes sapply DF  class               a           b           c     character   character   character    cols num  lt - c  a   b   DF cols num   lt - sapply DF cols num  as numeric  sapply DF  class              a           b           c      numeric     numeric   character

User · Answer

You could use convert from the hablar package   library dplyr  library hablar     Sample df  stolen from the solution by Luca Braglia  df  lt - tibble  a    as character 0 5                     b    paste 0 5    1   sep                          c    letters 1 6      insert variable names in num   df   gt   convert num a  b     Which gives you     A tibble  6 x 3       a     b c        lt dbl gt   lt dbl gt   lt chr gt  1    0  0 100 a     2    1  1 10  b     3    2  2 10  c     4    3  3 10  d     5    4  4 10  e     6    5  5 10  f      Or if you are lazy  let retype   from hablar guess the right data type   df   gt   retype     which gives you     A tibble  6 x 3       a     b c        lt int gt   lt dbl gt   lt chr gt  1     0 0 100 a     2     1 1 10  b     3     2 2 10  c     4     3 3 10  d     5     4 4 10  e     6     5 5 10  f

User · Answer

I realize this is an old thread but wanted to post a solution similar to your request for a function  just ran into the similar issue myself trying to format an entire table to percentage labels    Assume you have a df with 5 character columns you want to convert  First  I create a table containing the names of the columns I want to manipulate   col to convert  lt - data frame nrow   1 5                              col   c  col1   col2   col3   col4   col5     for  i in 1 max cal to convert row           colname  lt - col to convert col i      colnum  lt - which colnames df     colname          for  j in 1 nrow df                          df j colnum   lt - as numericdf df j colnum                     This is not ideal for large tables as it goes cell by cell  but it would get the job done

[r] converting multiple columns from character to numeric format in r

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