Package: ggquickeda
Title: Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary
        Tables
Version: 0.2.2
Authors@R: c(
    person("Samer", "Mouksassi", email = "samermouksassi@gmail.com",
      role = c("aut", "cre"),comment = c(ORCID = "https://orcid.org/0000-0002-7152-6654")),
    person("Dean", "Attali", email = "daattali@gmail.com",
      role = c("aut")),
    person("Benjamin", "Rich", email = "mail@benjaminrich.net",
      role = c("aut"), comment = "provided summary stats tables tab code"), 
    person("Michael", "Sachs", email = "sachsmc@gmail.com",
      role = c("aut"), comment = "provided ggkm code")
    )
Description: Quickly and easily perform exploratory data analysis by uploading your
     data as a 'csv' file. Start generating insights using 'ggplot2' plots and
     'table1' tables with descriptive stats, all using an easy-to-use point and click 
     'Shiny' interface.
URL: https://github.com/smouksassi/ggquickeda
BugReports: https://github.com/smouksassi/ggquickeda/issues
Depends: R (>= 3.6.0)
Imports: colourpicker, dplyr, DT, Formula, GGally (>= 2.1.0),
        ggbeeswarm, ggplot2 (>= 3.3.4), ggpmisc, ggrepel (>= 0.7.0),
        ggpubr, gridExtra, Hmisc, markdown, methods, plotly, quantreg,
        rlang, scales, shiny (>= 1.0.4), shinyjs (>= 1.1), shinyjqui,
        stringr, survival, survminer, tidyr, table1 (>= 1.2), zoo,
        shinyFiles, RPostgres
Suggests: knitr, rmarkdown
License: MIT + file LICENSE
SystemRequirements: pandoc with https support
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-05-16 11:15:21 UTC; smouksas
Author: Samer Mouksassi [aut, cre] (<https://orcid.org/0000-0002-7152-6654>),
  Dean Attali [aut],
  Benjamin Rich [aut] (provided summary stats tables tab code),
  Michael Sachs [aut] (provided ggkm code)
Maintainer: Samer Mouksassi <samermouksassi@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-16 11:40:02 UTC
