You can easily add advanced cohort-building component to your analytical dashboard or simple 'Shiny' app. Then you can instantly start building cohorts using multiple filters of different types, filtering datasets, and filtering steps. Filters can be complex and data-specific, and together with multiple filtering steps you can use complex filtering rules. The cohort-building sidebar panel allows you to easily work with filters, add and remove filtering steps. It helps you with handling missing values during filtering, and provides instant filtering feedback with filter feedback plots. The GUI panel is not only compatible with native shiny bookmarking, but also provides reproducible R code.
| Version: | 0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | magrittr, glue, bslib, jsonlite, purrr, ggplot2, ggiraph, htmltools, shiny, shinyWidgets (≥ 0.7.0), dplyr, cohortBuilder (≥ 0.1), tryCatchLog, highr, shinyGizmo, rlang (≥ 1.0), tibble |
| Suggests: | pkgload, packer, sass, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2022-06-23 |
| Author: | Krystian Igras [cre, aut], Kamil Wais [aut], Adam Foryś [ctb] |
| Maintainer: | Krystian Igras <krystian8207 at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | shinyCohortBuilder results |
| Package source: | shinyCohortBuilder_0.1.tar.gz |
| Windows binaries: | r-devel: shinyCohortBuilder_0.1.zip, r-release: shinyCohortBuilder_0.1.zip, r-oldrel: shinyCohortBuilder_0.1.zip |
| macOS binaries: | r-release (arm64): shinyCohortBuilder_0.1.tgz, r-oldrel (arm64): shinyCohortBuilder_0.1.tgz, r-release (x86_64): shinyCohortBuilder_0.1.tgz, r-oldrel (x86_64): shinyCohortBuilder_0.1.tgz |
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