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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 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 |
| 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 |
| 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.