We have just released a major update of the cdata R package to CRAN.

If you work with R and data, now is the time to check out the cdata package.

Among the changes in the 0.5.* version of cdata package:

• All coordinatized data or fluid data operations are now in the cdata package (no longer split between the cdata and replyr packages).
• The transforms are now centered on the more general table driven moveValuesToRowsN() and moveValuesToColumnsN() operators (though pivot and un-pivot are now made available as convenient special cases).
• All the transforms are now implemented in SQL through DBI (no longer using tidyr or dplyr, though we do include examples of using cdata with dplyr).
• This is (unfortunately) a user visible API change, however adapting to the changed API is deliberately straightforward.

cdata now supplies very general data transforms on both in-memory data.frames and remote or large data systems (PostgreSQL, Spark/Hive, and so on). These transforms include operators such as pivot/un-pivot that were previously not conveniently available for these data sources (for example tidyr does not operate on such data, despite dplyr doing so).

To help transition we have updated the existing documentation:

• “Coordinatized Data” Theory.
• The “fluid data” methodology.

The fluid data document is a bit long, as it covers a lot of concepts quickly. We hope to develop more targeted training material going forward.

In summary: cdata theory and package now allow very concise and powerful transformations of big data using R.