I'm working as a statistical programmer now, and have encountered datasets that:
Come from statistical packages that are not R,
Have data dictionaries in all sorts of formats (Word docs, non-OCRed PDF files, copies of forms that people fill out to enter the data in the first place),
Store data in 'value labels', which R does not really support (R's enumerated type is Factors).
This package lets me build data dictionaries in plain text (tab-separated TSV or TXT files) by copying/pasting out of existing dictionaries and then cleaning it up with regular expressions, and then it applies those dictionaries to a dataframe in a memory-conscious way so that it can work with very large data. It supports:
Converting variables to factors (ordered and unordered)
Adding "label" attributes to columns, which are recognised by RStudio and lots of packages.
github.com
I'm working as a statistical programmer now, and have encountered datasets that:
This package lets me build data dictionaries in plain text (tab-separated TSV or TXT files) by copying/pasting out of existing dictionaries and then cleaning it up with regular expressions, and then it applies those dictionaries to a dataframe in a memory-conscious way so that it can work with very large data. It supports: