pivottabler | Create Pivot Tables natively in R | Data Visualization library

It would be easier to give you a more applicable answer if you gave us a more reproducible example.

However, what I think you want is easily accomplished with functions from the dplyr package. This answer uses the built-in iris dataset. It groups by the categorical variable Species and calculates the median by Species for all numeric columns in the data frame.

Here are two potential answers:

If you're open to a tidyverse-style approach, it only takes a few lines to do the wrangling and summarising yourself. That will give you a datatable output that you can work with right away.

As the functions are evaluated as expressions as mentioned in the vignette

... Specify the calculation. The summarise expression must be an expression that can be used with the dplyr summarise() function. This expression is used internally by the pivottabler package with the dplyr summarise function.

we can wrap those with comma from formattable

We can use adorn_totals

How about this:

Summary

There are two different options - depending on the scenario you have:

1. If the data group combination has no matching rows in the data frame, use the noDataCaption argument.
2. If rows do exist for the data group combination in the data frame but the values are NA, use the exportOptions argument.

Option 1 - noDataCaption

Use the noDataCaption argument of the defineCalculation() function.

More information: http://pivottabler.org.uk/articles/v03-calculations.html#empty-cells-1

In the example below, there are no "Ordinary Passenger" trains for "Virgin Trains" in the bhmtrains data frame. In example 2, the empty cell is changed to display a dash.

I would suggest knitting the table in an r markdown file using knitr::kable as in:

I am the author of the pivottabler package.

There are currently only limited options to amend a pivot table after it has been calculated.

More detail

In your example, removing the columns would also remove the calculations, since in your R script the calculations are added after the columns. Reapplying the calculations is then not possible, because the pivot table recognises that the calculations were added already (you get an error). I will look at options to add flexibility in the future.

Alternative approach

One option to reduce the amount of code is to create a function which takes as a parameter the variable to show on the columns. This function can then be easily called to create different variations of the pivot table: