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I'm using the following package version

# devtools::install_github("hadley/dplyr")
> packageVersion("dplyr")
[1] ‘0.5.0.9001’

With the following tibble:

library(dplyr)
df  <- structure(list(gene_symbol = structure(1:6, .Label = c("0610005C13Rik", 
"0610007P14Rik", "0610009B22Rik", "0610009L18Rik", "0610009O20Rik", 
"0610010B08Rik"), class = "factor"), fold_change = c(1.54037, 
1.10976, 0.785, 0.79852, 0.91615, 0.87931), pvalue = c(0.5312, 
0.00033, 0, 0.00011, 0.00387, 0.01455), ctr.mean_exp = c(0.00583, 
59.67286, 83.2847, 6.88321, 14.67696, 1.10363), tre.mean_exp = c(0.00899, 
66.22232, 65.37819, 5.49638, 13.4463, 0.97043), ctr.cv = c(5.49291, 
0.20263, 0.17445, 0.46288, 0.2543, 0.39564), tre.cv = c(6.06505, 
0.28827, 0.33958, 0.53295, 0.26679, 0.52364)), .Names = c("gene_symbol", 
"fold_change", "pvalue", "ctr.mean_exp", "tre.mean_exp", "ctr.cv", 
"tre.cv"), row.names = c(NA, -6L), class = c("tbl_df", "tbl", 
"data.frame"))

That looks like this:

> df
# A tibble: 6 × 7
    gene_symbol fold_change  pvalue ctr.mean_exp tre.mean_exp  ctr.cv  tre.cv
         <fctr>       <dbl>   <dbl>        <dbl>        <dbl>   <dbl>   <dbl>
1 0610005C13Rik     1.54037 0.53120      0.00583      0.00899 5.49291 6.06505
2 0610007P14Rik     1.10976 0.00033     59.67286     66.22232 0.20263 0.28827
3 0610009B22Rik     0.78500 0.00000     83.28470     65.37819 0.17445 0.33958
4 0610009L18Rik     0.79852 0.00011      6.88321      5.49638 0.46288 0.53295
5 0610009O20Rik     0.91615 0.00387     14.67696     13.44630 0.25430 0.26679
6 0610010B08Rik     0.87931 0.01455      1.10363      0.97043 0.39564 0.52364

I'd like to round the floats (2nd columns onward) to 3 digits. What's the way to do it with dplyr::mutate_all()

I tried this:

cols <- names(df)[2:7]
# df <- df %>% mutate_each_(funs(round(.,3)), cols)
# Warning message:
#'mutate_each_' is deprecated.
# Use 'mutate_all' instead.
# See help("Deprecated") 

df <- df %>% mutate_all(funs(round(.,3)), cols)

But get the following error:

Error in mutate_impl(.data, dots) : 
  3 arguments passed to 'round'which requires 1 or 2 arguments
neversaint
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    `df %>% mutate_at(2:7, round, 3)` – alistaire Apr 10 '17 at 02:57
  • @alistaire Thanks. How can I use the variable `cols`. I tried this with error `df %>% mutate_all(cols, round, 3)` – neversaint Apr 10 '17 at 02:59
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    `df %>% mutate_at(cols, round, 3)`. Since it's not all the columns, it's `mutate_at`, not `mutate_all`. The error message could be better. – alistaire Apr 10 '17 at 03:00
  • I do not understand why `df %>% mutate_at(cols, round (.,3))` or `df %>% mutate_at(cols, round (.,3))` fails – Captain Tyler Feb 27 '18 at 16:13
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    when you use the . operator in a pipe, you are inserting the left side into where the . is. So you are getting round(df,3) which is not what you want. – Arthur Yip Mar 20 '19 at 23:04

2 Answers2

111

While the new across() function is slightly more verbose than the previous mutate_if variant, the dplyr 1.0.0 updates make the tidyverse language and code more consistent and versatile.

This is how to round specified columns:

df %>% mutate(across(2:7, round, 3)) # columns 2-7 by position

df %>% mutate(across(cols, round, 3)) # columns specified by variable cols

This is how to round all numeric columns to 3 decimal places:

df %>% mutate(across(where(is.numeric), round, 3))

This is how to round all columns, but it won't work in this case because gene_symbol is not numeric:

df %>% mutate(across(everything(), round, 3))

Where we put where(is.numeric) in across's arguments, you could put in other column specifications such as -1 or -gene_symbol to exclude column 1. See help(tidyselect) for even more options.

Update for dplyr 1.0.0

The across() function replaces the _if/_all/_at/_each variants of dplyr verbs. https://dplyr.tidyverse.org/dev/articles/colwise.html#how-do-you-convert-existing-code

Since some columns are not numeric, you could use mutate_if with the added benefit of rounding columns iff (if and only if) it is numeric:

df %>% mutate_if(is.numeric, round, 3)

Arthur Yip
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7
packageVersion("dplyr")
[1] '0.7.6'

Try

df %>% mutate_at(2:7, funs(round(., 3)))

It works!!

Antonio Jesús Pérez Luque
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