Controlling decimal places displayed in a tibble. Understanding what pillar.sigfig does

Question

I have a csv file weight.csv with the following contents.

weight,weight_selfreport
81.5,81.66969147005445
72.6,72.59528130671505
92.9,93.01270417422867
79.4,79.4010889292196
94.6,96.64246823956442
80.2,79.4010889292196
116.2,113.43012704174228
95.4,95.73502722323049
99.5,99.8185117967332

If I do

library(readr)
Df <- read_csv('weight.csv')
Df

I get

# A tibble: 9 x 2
  weight weight_selfreport
   <dbl>             <dbl>
1   81.5              81.7
2   72.6              72.6
3   92.9              93.0
4   79.4              79.4
5   94.6              96.6
6   80.2              79.4
7  116.              113. 
8   95.4              95.7
9   99.5              99.8

If I convert that tibble to a normal data frame, I'll see more digits.

as.data.frame(Df)
  weight weight_selfreport
1   81.5          81.66969
2   72.6          72.59528
3   92.9          93.01270
4   79.4          79.40109
5   94.6          96.64247
6   80.2          79.40109
7  116.2         113.43013
8   95.4          95.73503
9   99.5          99.81851

Initially I thought that if I wanted to get this type of display for the tibble, I thought I would do options(pillar.sigfig = 5).

However, that's not what it does.

options(pillar.sigfig = 5)
Df
# A tibble: 9 x 2
   weight weight_selfreport
    <dbl>             <dbl>
1  81.5              81.670
2  72.600            72.595
3  92.9              93.013
4  79.4              79.401
5  94.6              96.642
6  80.2              79.401
7 116.2             113.43 
8  95.4              95.735
9  99.5              99.819

And so I see that pillar.sigfig is about controlling significant digits not decimals places.

Fine but

• Why is (row 2, col 1) 72.6 being displayed as 72.600?
• What can I do, or can I do anything, to get five decimals places?

Answer 1

This might come a little late...3 years late, but it might help others looking for answers.

The issue lies with tibble. It has a very opinionated way of representing dfs. I presume, you often do not feel the need to look at your data in this way, but if you do, there are two options I frequently use that potentially are just another workaround.

Option 1: Use num()

This neat function enforces decimals. So you can mutate() all columns you want to format with the following:

library(tidyverse)

data <- tribble(
~ weight, ~ weight_selfreport,
81.5,81.66969147005445,
72.6,72.59528130671505,
92.9,93.01270417422867,
79.4,79.4010889292196,
94.6,96.64246823956442,
80.2,79.4010889292196,
116.2,113.43012704174228,
95.4,95.73502722323049,
99.5,99.8185117967332
)

data <-
  data %>%
  mutate(across(where(is.numeric), ~ num(., digits = 3)))

data
#> # A tibble: 9 × 2
#>      weight weight_selfreport
#>   <num:.3!>         <num:.3!>
#> 1    81.500            81.670
#> 2    72.600            72.595
#> 3    92.900            93.013
#> 4    79.400            79.401
#> 5    94.600            96.642
#> 6    80.200            79.401
#> 7   116.200           113.430
#> 8    95.400            95.735
#> 9    99.500            99.819

Option 2: Use table packages

Usually, when I inspect a tibble it is because it contains results I want to report. Thus, I use one of the many table-generator packages, e.g.

• flextable,
• gt,
• formattable,
• reactable,
• etc.

Here is an example you can try using flextable:

library(tidyverse)

data <- tribble(
  
~ weight, ~ weight_selfreport,
81.5,81.66969147005445,
72.6,72.59528130671505,
92.9,93.01270417422867,
79.4,79.4010889292196,
94.6,96.64246823956442,
80.2,79.4010889292196,
116.2,113.43012704174228,
95.4,95.73502722323049,
99.5,99.8185117967332
)

flextable::flextable(data)

I assume Option 1 might have been what you were looking for.

Answer 2

I have the same issue. Using pillar.sigfig helps. You can also use it with round() and you have more control. But if the last figure is 0 it will not display it.

The "trick" I used was to save the results in a variable and then use print.data.frame(). Then it works fine. But maybe there is an easier solution...