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
DOI: 10.32614/CRAN.package.datastepr
Author: Brandon Taylor
Maintainer: Brandon Taylor <brandon.taylor221 at>
License: CC0
NeedsCompilation: no
Materials: README
CRAN checks: datastepr results


Reference manual: datastepr.pdf
Vignettes: Data Stepping


Package source: datastepr_0.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): datastepr_0.0.2.tgz, r-oldrel (arm64): datastepr_0.0.2.tgz, r-release (x86_64): datastepr_0.0.2.tgz, r-oldrel (x86_64): datastepr_0.0.2.tgz
Old sources: datastepr archive


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