Change the class from factor to numeric of many columns in a data frame

Question

What is the quickest best way to change a large number of columns to numeric from factor    I used the following code but it appears to have re-ordered my data    gt  head stats  1 2     rk                 team 1  1 Washington Capitals  2  2     San Jose Sharks  3  3  Chicago Blackhawks  4  4     Phoenix Coyotes  5  5   New Jersey Devils  6  6   Vancouver Canucks   for i in c 1 3 ncol stats          stats  i   lt - as numeric stats  i       gt  head stats  1 2     rk                 team 1  2 Washington Capitals  2 13     San Jose Sharks  3 24  Chicago Blackhawks  4 26     Phoenix Coyotes  5 27   New Jersey Devils  6 28   Vancouver Canucks    What is the best way  short of naming every column as in   df colname  lt - as numeric ds colname

User · Answer

lapply is pretty much designed for this  unfactorize lt -c  colA   colB   df  unfactorize  lt -lapply unfactorize  function x  as numeric as character df  x

User · Answer

I would like to point out that if you have NAs in any column  simply using subscripts will not work  If there are NAs in the factor  you must use the apply script provided by Ramnath   E g   Df  lt - data frame    x   c NA as factor sample 1 5 30 r T       y   c NA as factor sample 1 5 30 r T       z   c NA as factor sample 1 5 30 r T       w   c NA as factor sample 1 5 30 r T       Df  c 1 4    lt - as numeric as character Df  c 1 4       Returns the following   Warning message  NAs introduced by coercion        gt  head Df         x  y  z  w     1 NA NA NA NA     2 NA NA NA NA     3 NA NA NA NA     4 NA NA NA NA     5 NA NA NA NA     6 NA NA NA NA   But   Df  c 1 4    apply Df  c 1 4    2  function x  as numeric as character x      Returns    gt  head Df     x  y  z  w 1 NA NA NA NA 2  2  3  4  1 3  1  5  3  4 4  2  3  4  1 5  5  3  5  5 6  4  2  4  4

User · Answer

This can be done in one line  there s no need for a loop  be it a for-loop or an apply  Use unlist   instead      testdata Df  lt - data frame    x   as factor sample 1 5 30 r TRUE      y   as factor sample 1 5 30 r TRUE      z   as factor sample 1 5 30 r TRUE      w   as factor sample 1 5 30 r TRUE         Df  c  y   w     lt - as numeric as character unlist Df  c  y   w        str Df    Edit   for your code  this becomes    id  lt - c 1 3 ncol stats     stats  id   lt - as numeric as character unlist stats  id       Obviously  if you have a one-column data frame and you don t want the automatic dimension reduction of R to convert it to a vector  you ll have to add the drop FALSE argument

User · Answer

Here are some dplyr options     by column type  df   gt      mutate if is factor   as numeric as character         by specific columns  df   gt      mutate at vars x  y  z    as numeric as character          all columns  df   gt      mutate all  as numeric as character

User · Answer

df colname  lt - as numeric df colname   I tried this way for changing one column type and I think it is better than many other versions  if you are not going to change all column types  df colname  lt - as character df colname   for the vice versa

User · Answer

You have to be careful while changing factors to numeric  Here is a line of code that would change a set of columns from factor to numeric  I am assuming here that the columns to be changed to numeric are 1  3  4 and 5 respectively  You could change it accordingly  cols   c 1  3  4  5       df  cols    apply df  cols   2  function x  as numeric as character x

User · Answer

I know this question is long resolved  but I recently had a similar issue and think I ve found a little more elegant and functional solution  although it requires the magrittr package   library magrittr  cols   c 1  3  4  5  df  cols    lt  gt   lapply function x  as numeric as character x      The   lt  gt   operator pipes and reassigns  which is very useful for keeping data cleaning and transformation simple  Now the list apply function is much easier to read  by only specifying the function you wish to apply

User · Answer

I think that ucfagls found why your loop is not working   In case you still don t want use a loop here is solution with lapply   factorToNumeric  lt - function f  as numeric levels f   as integer f    cols  lt - c 1  3 ncol stats   stats cols   lt - lapply stats cols   factorToNumeric      Edit  I found simpler solution  It seems that as matrix convert to character  So  stats cols   lt - as numeric as matrix stats cols      should do what you want

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I found this function on a couple other duplicate threads and have found it an elegant and general way to solve this problem  This thread shows up first on most searches on this topic  so I am sharing it here to save folks some time  I take no credit for this just so see the original posts here and here for details   df  lt - data frame x   1 10                   y   rep 1 2  5                    k   rnorm 10  5 2                    z   rep c 2010  2012  2011  2010  1999   2                    j   c rep c  a    b    c    3    d     convert magic  lt - function obj  type     FUN1  lt - switch type                   character   as character                   numeric   as numeric                   factor   as factor    out  lt - lapply obj  FUN1    as data frame out     str df  str convert magic df   character    str convert magic df   factor    df   c  x    y     lt - convert magic df   c  x    y      factor

User · Answer

That s what s worked for me  The apply   function tries to coerce df to matrix and it returns NA s   numeric df  lt - as data frame sapply df  2  as numeric

User · Answer

Based on  SDahm s answer  this was an  optimal  solution for my tibble   data   lt  gt   lapply type convert    gt   as data table     This requires dplyr and magrittr

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I tried a bunch of these on a similar problem and kept getting NAs  Base R has some really irritating coercion behaviors  which are generally fixed in Tidyverse packages  I used to avoid them because I didn t want to create dependencies  but they make life so much easier that now I don t even bother trying to figure out the Base R solution most of the time   Here s the Tidyverse solution  which is extremely simple and elegant   library purrr   mydf  lt - data frame    x1   factor c 3  5  4  2  1      x2   factor c  A    C    B    D    E       x3   c 10  8  6  4  2    map df mydf  as numeric

User · Answer

you can use unfactor   function from  varhandle  package form CRAN   library  varhandle    my iris  lt - data frame Sepal Length   factor iris Sepal Length                         sample id   factor 1 nrow iris     my iris  lt - unfactor my iris

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I like this code because it s pretty handy     data    lt - lapply data  function x  type convert as character x   as is   TRUE    change all vars to their best fitting data type   It is not exactly what was asked for  convert to numeric   but in many cases even more appropriate

User · Answer

Further to Ramnath s answer  the behaviour you are experiencing is that due to as numeric x  returning the internal  numeric representation of the factor x at the R level  If you want to preserve the numbers that are the levels of the factor  rather than their internal representation   you need to convert to character via as character   first as per Ramnath s example   Your for loop is just as reasonable as an apply call and might be slightly more readable as to what the intention of the code is  Just change this line   stats  i   lt - as numeric stats  i     to read  stats  i   lt - as numeric as character stats  i      This is FAQ 7 10 in the R FAQ   HTH

User · Answer

I had problems converting all columns to numeric with an apply   call   apply data  2  as numeric    The problem turns out to be because some of the strings had a comma in them -- e g   1 024 63  instead of  1024 63  -- and R does not like this way of formatting numbers  So I removed them and then ran as numeric     data   as data frame apply data  2  function x      y   str replace all x            remove commas   return as numeric y    then convert       Note that this requires the stringr package to be loaded

[r] Change the class from factor to numeric of many columns in a data frame

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