Make automatic reports

Being inserted in automatic reporting is the ultimate goal of crosstables.

There are two cases to consider:

  • You have a lot of tables and little text? You probably should use officer.
  • You have a lot of text and a few tables? You probably should use Rmarkdown.

As I only find myself in the first case, this vignette will only talk about officer.

Create reports with officer

Output example

The real power of crosstable comes out when used with David Gohel’s awesome package officer, which allows to automatically create MS Word documents.

For the example, let’s try to create a document like this: officer example

You can also download this example here.

Code

This code will produce the example above.

First, we create 3 crosstables using available datasets, along with a ggplot. Then, we start a document (using officer::read_docx()), add some titles and paragraphs, incorporate our tables and our plot, along with legends, and add some page breaks. Note that the legends have a bookmark argument that can be referred to in the text for automatic numbering.

library(officer)
library(ggplot2)

ct1=crosstable(iris, by=Species, test=TRUE)
ct2=crosstable(mtcars2, c(mpg,cyl,disp), by=am, effect=TRUE, 
               total="both", showNA="always")
ct3=crosstable(esoph)
crosstable_options(
  crosstable_fontsize_body=8,
  crosstable_padding_v=0,
  crosstable_units="cm"
)
my_plot = ggplot(data = iris ) +
  geom_point(mapping = aes(Sepal.Length, Petal.Length))

doc = read_docx() %>% #default template
  body_add_title("Dataset iris (nrow={nrow(iris)})", 1) %>%
  body_add_title("Not compacted", 2) %>%
  body_add_normal("Table \\@ref(table_autotest) is an example. However, automatic 
                  testing is **bad** and I should feel **bad**.") %>%
  body_add_crosstable(ct1) %>%
  body_add_table_legend("Automatic testing is bad", bookmark="table_autotest") %>%
  body_add_normal() %>%  
  body_add_normal("Let's add a figure as well. <br> You can see in Figure \\@ref(fig_iris) 
                  that sepal length is somehow correlated with petal length.") %>%
  body_add_figure_legend("Relation between Petal length and Sepal length", 
                         bookmark="fig_iris") %>% 
  body_add_gg2(my_plot, w=14, h=10, scale=1.5) %>% 
  body_add_break() %>%
  
  body_add_title("Compacted", 2) %>%
  body_add_normal("When compacting, you might want to remove the test names.") %>%
  body_add_crosstable(ct1, compact=TRUE, show_test_name=FALSE) %>%
  body_add_break() %>%
  
  body_add_title("Dataset mtcars2", 1) %>%
  body_add_normal("This dataset has {nrow(ct3)} rows and {x} columns.", 
                  x=ncol(ct3)) %>%
  body_add_normal("Look, there are labels!") %>%
  body_add_crosstable(ct2, compact=TRUE)

For demonstration purposes, I tried to cover as many features as possible, so it contains multiple syntaxes for the same result. Of course, you should use whatever syntax you are most comfortable with.

Output

To see the resulting Word document, use:

write_and_open(doc, "vignette_officer.docx")

While you are still working on your code, you might want to omit the name so that you open the docx file in a temporary file for a quick peek (write_and_open(doc)). This will prevent the errors that happen when the file is already open.

You can also use print(doc, "vignette_officer.docx") if you don’t want the file to open right away.

Functions

Here is a brief description of the functions used in this example:

  • officer::read_docx(): creates a bare MS Word document
  • body_add_title(): adds a title paragraph of any level
  • body_add_normal(): adds a normal style paragraph. You can also incorporate variables using the syntax {nrow(ct3)} and references using the syntax \\@ref(my_bookmark). It also support Markdown syntax for bold, italics, colored text… See help(body_add_normal) to see the details.
  • body_add_crosstable(): adds a crosstable
  • body_add_figure_legend() and body_add_table_legend(): adds a figure/table legend. The bookmark is the key that can be added elsewhere in body_add_normal().
  • body_add_gg2(): adds a ggplot. Unlike officer::body_add_gg(), you can change the unit using the units argument or the options options(crosstable_units="cm").

{crosstable} comes with many officer-like functions to help you create your report, see the full list in the references.

Also, browse https://davidgohel.github.io/officer/ for more insight about how you can use {officer}.

Styles

Crosstable uses Word styles extensively.

Here, I used the default template of officer::read_docx() that comes with default styles. In your own custom template, you can edit all styles (for instance you can make “Normal” have a bold font of size 8) and add your own. See the official documentation on how to use templates.

The best example here is body_add_list(), which is supposed to add a bullet list. Unfortunately, the default template does not come with list styles so you will have to add one to your custom template before using it:

doc = read_docx("my_template.docx) %>% #your custom template
  body_add_list(c("this is item 1", "this is item 2"), style="bullet")

#alternatively, you can define the style globally and use the ordered parameter
options(crosstable_style_list_unordered="bullet")
options(crosstable_style_list_ordered="numbered")
doc = read_docx("my_template.docx) %>%
  body_add_list(c("this is item 1", "this is item 2"), ordered=FALSE)

See ?crosstable_options for a list of all styles you can specify globally and use officer::styles_info(doc) to see which one are available in your template.

Note that you might sometimes encounter the error “Error: could not match any style named ‘xxx’” if you are not careful.

Post-production for table/figure legends

If you added some legends or TOC titles, MS Word might ask you to “update the fields”, to which you should answer “Yes”. This will trigger the automatic numbering of tables and references.

Autofit macro for large tables

Auto-fitting from outside MS Word has its limits, and large tables might still overflow your document.

If so, you can use MS Word inner autofit tools on each table one by one (Table Tools > Layout > AutoFit > AutoFit Window), which can be really tedious.

But fear not! You can also use a MS Word macro to do the job for you. Here is how:

  • In the R console, run generate_autofit_macro() to generate the file crosstable_autofit.bas in your working directory.

  • In MS Word, press Alt+F11 to open the VB Editor.

  • In the Editor, go to File > Import or press Ctrl+M to open the import dialog, and import crosstable_autofit.bas. There should now be a “CrosstableMacros” module in the “Normal” project.

  • Run the macro, either from the VB Editor or from View > Macros > View Macros > Run.

This process will make the macro accessible from any Word file on this computer. Note that, in the Editor, you can also drag the module to your document project to make the macro accessible only from this file. The file will have to be named with the docm extension though.