Package: ggquickeda 0.3.3.9999

ggquickeda: Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary Tables

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.

Authors:Samer Mouksassi [aut, cre], Dean Attali [aut], James Craig [aut], Benjamin Rich [aut], Michael Sachs [aut]

ggquickeda_0.3.3.9999.tar.gz
ggquickeda_0.3.3.9999.zip(r-4.7)ggquickeda_0.3.3.9999.zip(r-4.6)ggquickeda_0.3.3.9999.zip(r-4.5)
ggquickeda_0.3.3.9999.tgz(r-4.6-any)ggquickeda_0.3.3.9999.tgz(r-4.5-any)
ggquickeda_0.3.3.9999.tar.gz(r-4.7-any)ggquickeda_0.3.3.9999.tar.gz(r-4.6-any)
ggquickeda_0.3.3.9999.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ggquickeda/json (API)

# Install 'ggquickeda' in R:
install.packages('ggquickeda', repos = c('https://smouksassi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/smouksassi/ggquickeda/issues

Pkgdown/docs site:https://smouksassi.github.io

Datasets:

On CRAN:

Conda:

8.35 score 75 stars 37 scripts 327 downloads 1 mentions 27 exports 179 dependencies

Last updated from:f80ba03f97. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE203
source / vignettesOK241
linux-release-x86_64NOTE202
macos-release-arm64NOTE130
macos-oldrel-arm64NOTE139
windows-develNOTE134
windows-releaseNOTE144
windows-oldrelNOTE151
wasm-releaseOK164

Exports:+attach_source_depcloglog_transcumhaz_transdostepevent_transgeom_kmgeom_kmbandgeom_kmticksGeomKmGeomKmbandGeomKmticksget_source_codeggcontinuousexpdistggkmrisktablegglogisticexpdistggresponseexpdistmerge_stepsrun_ggquickedasourceablestairstepnstat_kmstat_kmbandstat_kmticksStatKmStatKmbandStatKmticks

Dependencies:abindaskpassbackportsbase64encbeeswarmbitbit64bitopsblobbootbroombslibcachemcarcarDatacaToolscheckmatecliclustercodetoolscolorspacecolourpickercommonmarkconfintrconstructivecorrplotcowplotcpp11crayoncrosstalkcurldata.tableDBIDerivdiffobjdigestdoBydplyrDTevaluateexactRankTestsfarverfastmapfontawesomeforcatsforecastforeignFormulafracdifffsgenericsGGallyggbeeswarmggh4xggplot2ggpmiscggppggpubrggrepelggridgesggsciggsignifggstanceggstatsggtextgluegridExtragridtextgtablehighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvhttrisobandjpegjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelitedownlme4lmtestlubridatemagrittrmarkdownMASSMatrixMatrixModelsmaxstatmemoisemgcvmicrobenchmarkmimeminiUIminqamodelrmultcompmvtnormnlmenloptrnnetnumDerivopensslotelpatchworkpbkrtestpillarpkgconfigplotlyplyrpngpolsplinepolynomprettyunitsprogresspromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownrmsrpartRPostgresrstatixrstudioapiS7sandwichsassscalesshinyshinyFilesshinyjquishinyjssourcetoolsSparseMsplus2Rstringistringrsurvivalsurvminersystable1TH.datatibbletidyrtidyselecttimechangetimeDatetinytexurcautf8vctrsviporviridisLitewaldowithrxfunxml2xtablextsyamlzoo

Introduction to ggquickeda
Rendered fromggquickeda.Rmdusingknitr::rmarkdown

Last update: 2024-01-14
Started: 2018-04-04

Shiny App
Rendered fromapp.Rmdusingknitr::rmarkdown

Last update: 2022-06-18
Started: 2022-06-18

Visualizing Summary Data
Published Data | Load the Data into the app | X/Y Mappings and Splitting Options | Facets Options | Ordering of Variables and Values | Remove Default Points and add a Point Interval | Setting Titles, Captions and Logging the X axis | Example of what is Possible with ggquickeda
Rendered fromVisualizing_Summary_Data.Rmdusingknitr::rmarkdown

Last update: 2021-02-09
Started: 2020-10-26

Additional Plots and Stats with ggquickeda
Multiple Y variables, recoding continuous variables to categories and Medina/PI: | Boxplots, Median/PI, Mean: | Continuous and categorical variables descriptive stats: | Univariate Plots:
Rendered fromAdditionalPlotsStats.Rmdusingknitr::rmarkdown_notangle

Last update: 2020-07-21
Started: 2018-04-16