Most of objects encountered throughout the easystats packages are “tables”, i.e., a 2D matrix with columns and rows. In R, these objects are often, at their core, data frames. Let’s create one to use as an example:
library(insight)
library(dplyr)
df <- data.frame(
Variable = c(1, 3, 5, 3, 1),
Group = c("A", "A", "A", "B", "B"),
CI = c(0.95, 0.95, 0.95, 0.95, 0.95),
CI_low = c(3.35, 2.425, 6.213, 12.1, 1.23),
CI_high = c(4.23, 5.31, 7.123, 13.5, 3.61),
p = c(0.001, 0.0456, 0.45, 0.0042, 0.34)
)
df
#> Variable Group CI CI_low CI_high p
#> 1 1 A 0.95 3.350 4.230 0.0010
#> 2 3 A 0.95 2.425 5.310 0.0456
#> 3 5 A 0.95 6.213 7.123 0.4500
#> 4 3 B 0.95 12.100 13.500 0.0042
#> 5 1 B 0.95 1.230 3.610 0.3400
When I display in in the console (calling an object - e.g. df
- is actually equivalent to calling print(df)
), the output looks alright, but it could be improved. Some packages, such as knitr, have functions to create a nicer output. For instance, in markdown, so that it can be nicely rendered in markdown documents when copied:
Variable | Group | CI | CI_low | CI_high | p |
---|---|---|---|---|---|
1 | A | 0.95 | 3.350 | 4.230 | 0.0010 |
3 | A | 0.95 | 2.425 | 5.310 | 0.0456 |
5 | A | 0.95 | 6.213 | 7.123 | 0.4500 |
3 | B | 0.95 | 12.100 | 13.500 | 0.0042 |
1 | B | 0.95 | 1.230 | 3.610 | 0.3400 |
Or HTML, which again makes it look great in HTML files. For instance, this code:
Will be rendered like this:
Variable | Group | CI | CI_low | CI_high | p |
---|---|---|---|---|---|
1 | A | 0.95 | 3.350 | 4.230 | 0.0010 |
3 | A | 0.95 | 2.425 | 5.310 | 0.0456 |
5 | A | 0.95 | 6.213 | 7.123 | 0.4500 |
3 | B | 0.95 | 12.100 | 13.500 | 0.0042 |
1 | B | 0.95 | 1.230 | 3.610 | 0.3400 |
The insight package also contains function to improve the “printing”, or rendering, of tables. Its design dissociates two separate and independent steps: formatting and exporting.
The purpose of formatting is to improve a given table, while still keeping it as a regular R data frame, so that it can be for instance further modified by the user.
format_table(df)
#> Variable Group 95% CI p
#> 1 1.00 A [ 3.35, 4.23] 0.001
#> 2 3.00 A [ 2.42, 5.31] 0.046
#> 3 5.00 A [ 6.21, 7.12] 0.450
#> 4 3.00 B [12.10, 13.50] 0.004
#> 5 1.00 B [ 1.23, 3.61] 0.340
As you can see, format_table()
modifies columns, turning number into characters (so that it has the same amount of digits), and detecting confidence intervals. This is usually combined with column-specific formatting functions, like format_p()
:
The next step is exporting, which takes a data frame and renders it in a given format, so that it looks good in the console, or in markdown, HTML or latex.
For text output, we need to cat()
the returned result to get nice output in the console.
cat(export_table(df))
#> Variable | Group | CI | CI_low | CI_high | p
#> -----------------------------------------------------
#> 1 | A | 0.95 | 3.35 | 4.23 | 1.00e-03
#> 3 | A | 0.95 | 2.42 | 5.31 | 0.05
#> 5 | A | 0.95 | 6.21 | 7.12 | 0.45
#> 3 | B | 0.95 | 12.10 | 13.50 | 4.20e-03
#> 1 | B | 0.95 | 1.23 | 3.61 | 0.34
For markdown or HTML, simply use the format
argument.
Variable | Group | CI | CI_low | CI_high | p |
---|---|---|---|---|---|
1 | A | 0.95 | 3.35 | 4.23 | 1.00e-03 |
3 | A | 0.95 | 2.42 | 5.31 | 0.05 |
5 | A | 0.95 | 6.21 | 7.12 | 0.45 |
3 | B | 0.95 | 12.10 | 13.50 | 4.20e-03 |
1 | B | 0.95 | 1.23 | 3.61 | 0.34 |
…or HTML.
Variable | CI | CI_low | CI_high | p |
---|---|---|---|---|
A | ||||
1 | 0.95 | 3.35 | 4.23 | 1.00e-03 |
3 | 0.95 | 2.42 | 5.31 | 0.05 |
5 | 0.95 | 6.21 | 7.12 | 0.45 |
B | ||||
3 | 0.95 | 12.10 | 13.50 | 4.20e-03 |
1 | 0.95 | 1.23 | 3.61 | 0.34 |
This can be combined with format_table()
.
Variable | 95% CI | p |
---|---|---|
A | ||
1.00 | ( 3.35, 4.23) | 0.001 |
3.00 | ( 2.42, 5.31) | 0.046 |
5.00 | ( 6.21, 7.12) | 0.450 |
B | ||
3.00 | (12.10, 13.50) | 0.004 |
1.00 | ( 1.23, 3.61) | 0.340 |
TODO: What about display?