datastepr: An Implementation of a SAS-Style Data Step

Based on a SAS data step. This allows for row-wise dynamic building of data, iteratively importing slices of existing dataframes, conducting analyses, and exporting to a results frame. This is particularly useful for differential or time-series analyses, which are often not well suited to vector- based operations.

Version: 0.0.2
Depends: R (≥ 3.1.3)
Imports: dplyr (≥ 0.5.0), lazyeval (≥ 0.1.10), R6 (≥ 2.0.1), magrittr (≥ 1.5), tibble (≥ 1.1)
Suggests: knitr, covr, rmarkdown, testthat
Published: 2016-08-20
Author: Brandon Taylor
Maintainer: Brandon Taylor <brandon.taylor221 at gmail.com>
BugReports: https://github.com/bramtayl/datastepr/issues
License: CC0
URL: https://github.com/bramtayl/datastepr
NeedsCompilation: no
Materials: README
CRAN checks: datastepr results

Downloads:

Reference manual: datastepr.pdf
Vignettes: Data Stepping
Package source: datastepr_0.0.2.tar.gz
Windows binaries: r-devel: datastepr_0.0.2.zip, r-release: datastepr_0.0.2.zip, r-oldrel: datastepr_0.0.2.zip
OS X El Capitan binaries: r-release: datastepr_0.0.2.tgz
OS X Mavericks binaries: r-oldrel: datastepr_0.0.2.tgz
Old sources: datastepr archive

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