Rounding selected columns of data.table in R

If you don't mind overwriting your original mydf:

cols <- names(mydf)[1:2]
mydf[,(cols) := round(.SD,1), .SDcols=cols]
mydf

#   vnum1 vnum2 vch1
#1:   0.6   0.7    B
#2:  -1.4   0.5    E
#3:   0.7   0.9    A
#4:  -0.3   0.8    C
#5:  -0.8   0.6    C

Using dplyr

If you want to round multiple columns at once:

mydf %>% mutate_at(vars(vnum1, vnum2), funs(round(., 1)))

Or, if you want to change all columns except "vch1":

mydf %>% mutate_at(vars(-vch1), funs(round(., 1)))

Or, if you want to change all columns starting with "vnum":

mydf %>% mutate_at(vars(starts_with("vnum")), funs(round(., 1)))

Or, if you want to change only numeric columns:

mydf %>% mutate_if(is.numeric, ~round(., 1))

You get:

  vnum1 vnum2 vch1
1   0.6   0.7    B
2  -1.4   0.5    E
3   0.7   0.9    A
4  -0.3   0.8    C
5  -0.8   0.6    C

dplyr works on data.table objects! dplyr::mutate (as of dplyr 1.0.0 major update) incorporates flexible specification of columns and functions for modifying the data, using across.

To specify all columns that have numeric data:

• mydf %>% mutate(across(where(is.numeric), round, 1))
  • which is the same as mydf %>% mutate(across(where(is.numeric), ~round(., 1)))

To specify all columns with names that start with "vnum":

• mydf %>% mutate(across(starts_with("vnum"), round, 1))

It is slightly more wordy than the previous mutate_if (which still works but is retired) but it is consistent with other possible specifications and allows for more variations.

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Old answer

You can use mutate_if with the added benefit of rounding a column only if it is numeric

mydf %>% mutate_if(is.numeric, round, 1)