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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "ggstratify" in publications use:'
type: software
license: GPL-3.0-only
title: 'ggstratify: Fast Stratified Descriptive Figures with a Point-and-Click GUI'
version: 0.2.0.9000
doi: 10.5281/zenodo.21961507
identifiers:
- type: doi
  value: 10.32614/CRAN.package.ggstratify
abstract: 'A point-and-click ''shiny'' interface for the descriptive analysis that
  comes before any model is chosen. Pass a data frame, pick the variable to describe,
  and add the layers you want to see it within: a second variable becomes the panels
  of a ''ggplot2'' facet_wrap(), and further variables become separate figures, one
  file each, taken either one variable at a time or crossed. Every stratum is reported
  with the number of observations behind it, on the figure and on each of its panels;
  strata that contain none are listed rather than dropped, and rows with a missing
  value in a layer variable are excluded and counted. A continuous variable can be
  categorized into quantile groups, equal-width bins or user-supplied cut points,
  a variable of any type can be turned into whether it is missing or observed, so
  that the rows a layer would exclude become a stratum of their own, and a date or
  date-time variable can be read at a chosen resolution, either as a calendar period
  or as a position in the yearly cycle such as the month or the season; any of them
  can then be used as a layer. The figure types follow those offered by the ''ggplotgui''
  package and add the line plot for change over time, an optional LOWESS smoother,
  and the Kaplan-Meier curve estimated by ''survival'', with an optional number-at-risk
  table. An error bar can show a standard error or a confidence interval, the latter
  from the t distribution for a mean and from the Clopper-Pearson or Wilson method
  for a proportion, and the points can be joined by a line computed from the same
  summary, which is how a trend over time is read. A survey weight can be set: the
  figure is then drawn from the weighted data, every count is reported both as rows
  and as the sum of the weights, and error bars and confidence bands are design-based
  estimates from the ''survey'' package. Columns are described as they are typed,
  so convert each to the type you mean first. Figures are written as PNG or SVG, and
  the application prints the ''ggplot2'' code behind the figure on screen, so that
  a description can be repeated, shared or accounted for later. Everything runs locally,
  with no network access and no AI involved.'
authors:
- family-names: Shiroshita
  given-names: Akihiro
  email: akihirokun8@gmail.com
- family-names: Kataoka
  given-names: Yuki
  email: youkiti@gmail.com
preferred-citation:
  type: manual
  title: 'ggstratify: Fast Stratified Descriptive Figures with a Point-and-Click GUI'
  authors:
  - family-names: Shiroshita
    given-names: Akihiro
    email: akihirokun8@gmail.com
  - family-names: Kataoka
    given-names: Yuki
    email: youkiti@gmail.com
  year: '2026'
  notes: R package version 0.2.0.9000
  url: https://CRAN.R-project.org/package=ggstratify
  doi: 10.5281/zenodo.21961507
repository: https://akishiroshita.r-universe.dev
repository-code: https://github.com/AkiShiroshita/ggstratify
commit: 9670f44d384fdebb31bb16d815c4ce937409e923
url: https://akishiroshita.github.io/ggstratify/
date-released: '2026-09-25'
contact:
- family-names: Shiroshita
  given-names: Akihiro
  email: akihirokun8@gmail.com