Build Powerful Pivot Tables and Dynamically Slice & Dice your Data

Build powerful pivot tables (aka Pivot Grid, Pivot Chart, Cross-Tab) and dynamically slice & dice / drag 'n' drop your data. 'rpivotTable' is a wrapper of 'pivottable', a powerful open-source Pivot Table library implemented in 'JavaScript' by Nicolas Kruchten. Aligned to 'pivottable' v2.11.0.



The rpivotTable package is an R htmlwidget built around the pivottable library.

PivotTable.js is a Javascript Pivot Table library with drag'n'drop functionality built on top of jQuery/jQueryUI and written in CoffeeScript by Nicolas Kruchten at Datacratic. It is available under an MIT license

The rpivotTable package depends on the development version of the htmlwidgets package so you need to install both packages. You can do this using the devtools package as follows:

devtools::install_github(c("ramnathv/htmlwidgets", "smartinsightsfromdata/rpivotTable"))

Just plug in your data.frame or data.table (e.g. dt) to rpivotTable().

It is as simple as this:

data(mtcars)
rpivotTable(mtcars)

The pivot table should appear in your RStudio Viewer or your browser of choice.

Please refer to the examples and explanations here.

rpivotTable parameters decide how the pivot table will look like the firs time it is opened:

  • data can be a data.frame or data.table. Nothing else is needed. If only the data is selected the pivot table opens with nothing on rows and columns (but you can at any time drag and drop any variable in rows or columns at your leasure)
  • rows and cols allow the user to create a report, i.e. to indicate which element will be on rows and columns.
  • aggregatorName indicates the type of aggregation. Options here are numerous: Count, Count Unique Values, List Unique Values, Sum, Integer Sum, Average, Sum over Sum, 80% Upper Bound, 80% Lower Bound, Sum as Fraction of Total, Sum as Fraction of Rows, Sum as Fraction of Columns, Count as Fraction of Total, Count as Fraction of Rows, Count as Fraction of Columns
  • vals specifies the variable to use with aggregatorName.
  • renderers dictates the type of graphic element used for display, like Table, Treemap etc.
  • sorters allow to implement a javascript function to specify the ad hoc sorting of certain values. See vignette for an example. It is especially useful with time divisions like days of the week or months of the year (where the alphabetical order does not work)

For example, to display a pivot table with frequency of colour combinations of eyes and hair, you can specify:

data(HairEyeColor)
rpivotTable(data = HairEyeColor, rows = "Hair",cols="Eye", vals = "Freq", aggregatorName = "Sum", rendererName = "Table", width="100%", height="400px")

This will display a cross tab with the frequency of eyes by hair colour. Dragging & dropping (slicing & dicing) categorical variables in rows and columns changes the shape of the table.

If you want to include it as part of your dplyr / magrittr pipeline, you can do that also:

library(dplyr)
iris %>%
tbl_df %>%
filter( Sepal.Width > 3 ) %>%
rpivotTable

News

Reference manual

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install.packages("rpivotTable")

0.2.0 by Enzo Martoglio, 3 months ago


https://github.com/smartinsightsfromdata, http://smartinsightsfromdata.github.io


Browse source code at https://github.com/cran/rpivotTable


Authors: Enzo Martoglio [aut, cre] (R interface), Nicolas Kruchten [ctb, cph] (pivottable library)


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports htmlwidgets

Suggests testthat, htmltools, knitr, rmarkdown, devtools, dplyr, data.table

Enhances shiny


Suggested by vaersNDvax, vaersvax.


See at CRAN