Package: ggstratify
Title: Fast Stratified Descriptive Figures with a Point-and-Click GUI
Version: 0.2.0
Authors@R: 
    c(
      person(
        "Akihiro", "Shiroshita",
        email = "akihirokun8@gmail.com",
        role = c("aut", "cre", "cph")
      ),
      person(
        "Yuki", "Kataoka",
        email = "youkiti@gmail.com",
        role = "aut"
      )
    )
Description: 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.
License: GPL-3
URL: https://github.com/AkiShiroshita/ggstratify,
        https://akishiroshita.github.io/ggstratify/
BugReports: https://github.com/AkiShiroshita/ggstratify/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: bslib (>= 0.5.0), checkmate (>= 2.1.0), data.table (>=
        1.14.0), ggplot2 (>= 3.4.0), grDevices, patchwork (>= 1.1.0),
        ragg, shiny (>= 1.7.0), stats, survey (>= 4.5), survival (>=
        3.2.0), utils
Suggests: knitr, rmarkdown, svglite (>= 2.1.0), testthat (>= 3.0.0),
        tibble
VignetteBuilder: knitr
LazyData: true
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-09-24 22:54:41 UTC; shiroa1
Author: Akihiro Shiroshita [aut, cre, cph],
  Yuki Kataoka [aut]
Maintainer: Akihiro Shiroshita <akihirokun8@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-25 07:10:02 UTC
Built: R 4.6.1; ; 2026-09-25 10:27:08 UTC; unix
