Crosstable is a package centered on a single function,
crosstable
, which easily computes descriptive statistics on
datasets. It can use the tidyverse
syntax and is interfaced
with the package officer
to create automatized reports.
# Install last version available on CRAN
install.packages("crosstable")
# Install development version on Github
::install_github("DanChaltiel/crosstable", build_vignettes=TRUE)
devtools
# Install specific commit or tagged version (for reproducibility purpose)
::install_github("DanChaltiel/crosstable@ee012f6", build_vignettes=TRUE)
devtools::install_github("DanChaltiel/crosstable@0.6.1", build_vignettes=TRUE) devtools
Note that, for reproducibility purpose, an even better solution would
be to use renv
.
Here are 2 examples to try and show you the main features of
crosstable
. See the documentation
website for more.
Dear crosstable, using the
mtcars2
dataset, please describe columnsdisp
andvs
depending on the levels of columnam
, with totals in both rows and columns, and with proportions formatted with group size, percent on row and percent on column, with no decimals.
library(crosstable)
= crosstable(mtcars2, c(disp, vs), by=am, total="both",
ct1 percent_pattern="{n} ({p_row}/{p_col})", percent_digits=0) %>%
as_flextable()
ct1
With only a few arguments, we did select which column to describe
(c(disp, vs)
), define a grouping variable
(by=am
), set the percentage calculation in row/column
(percent_pattern=
), and ask for totals
(total=
).
Since mtcars2
is a dataset with labels, they are
displayed instead of the variable name (see here
for how to add some).
As crosstable()
is returning a data.frame
,
we use as_flextable()
to output a beautiful HTML table.
This one can even be exported to MS Word with a few more lines of code
(see here
to learn how).
Here is a more advanced example.
Dear crosstable, using the
mtcars2
dataset again, please describe all columns whose name starts with “cy” and those whose name ends with “at”, depending on the levels of both columnsam
andvs
, without considering labels, applyingmean()
andquantile()
as summary function, withprobs
25% and 75% defined for this latter function, and with 3 decimals for numeric variables:
= crosstable(mtcars2, c(starts_with("cy"), ends_with("at")), by=c(am, vs),
ct2 label=FALSE, num_digits=3, funs=c(mean, quantile),
funs_arg=list(probs=c(.25,.75))) %>%
as_flextable(compact=TRUE, header_show_n=1:2)
ct2
Here, the variables were selected using tidyselect
helpers and the summary functions mean
and
quantile
were specified, along with argument
probs
for the latter. Using label=FALSE
allowed to see which variables were selected but it is best to keep the
labels in the final table.
In as_flextable()
, the compact=TRUE
option
yields a longer output, which may be more suited in some contexts (for
instance for publication), and header_show_n=1:2
adds the
group sizes for both rows of the header.
You can find the whole documentation on the dedicated website:
vignette("crosstable")
for a first step-by-step guide
on how to use crosstable
(link)vignette("crosstable-report")
for more on creating MS
Word reports using either {officer}
or
Rmarkdown
(link)vignette("pertent_pattern")
for more on how to use
percent_pattern
(link)vignette("crosstable-selection")
for more on variable
selection (link),
although you should better read https://tidyselect.r-lib.org/articles/syntax.html.There are lots of other features you can learn about there, for instance (non-exhaustive list):
is.numeric
(link)sqrt(mpg)
or Surv(time, event)
(link)If you have a question about how to use crosstable
,
please ask on StackOverflow
with the tag crosstable
. You can @DanChaltiel
in a comment if you are struggling to get answers. Don’t forget to add a
minimal reproducible example to your
question, ideally using the reprex package.
If you miss any feature that you think would belong in
crosstable
, please fill a Feature
Request issue.
If you encounter an unexpected error while using
crosstable
, please fill a Bug
Report issue. In case of any installation problem, try the solutions
proposed in this
article first.
In its earliest development phase, crosstable
was based
on the awesome package biostat2
written by David Hajage. Thanks David!