R-ggplot2
Port variant standard
Summary Data visualizations using Grammar of Graphics
Package version 3.3.6
Homepage https://ggplot2.tidyverse.org
Keywords cran
Maintainer CRAN Automaton
License Not yet specified
Other variants There are no other variants.
Ravenports Buildsheet | History
Ravensource Port Directory | History
Last modified 08 MAY 2022, 14:37:35 UTC
Port created 14 APR 2020, 06:14:40 UTC
Subpackage Descriptions
single ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
Configuration Switches (platform-specific settings discarded)
This port has no build options.
Package Dependencies by Type
Build (only) gmake:single:ravensys
R:primary:standard
Build and Runtime R-digest:single:standard
R-glue:single:standard
R-gtable:single:standard
R-isoband:single:standard
R-rlang:single:standard
R-scales:single:standard
R-tibble:single:standard
R-withr:single:standard
Runtime (only) R:complete:standard
Download groups
main mirror://CRAN/src/contrib
Distribution File Information
bfcb4eb92a0fcd3fab713aca4bb25e916e05914f2540271a45522ad7e43943a9 3061989 CRAN/ggplot2_3.3.6.tar.gz
Ports that require R-ggplot2:standard
R-broom:standard Convert statistical analysis into Tidy tibbles
R-caret:standard Classification and Regression Training
R-forecast:standard Forecasting for time series and linear models
R-ggforce:standard Accelerating 'ggplot2'
R-ggmap:standard Spatial Visualization with ggplot2
R-ggraph:standard Grammar of Graphics implementation
R-ggrepel:standard Positions non-overlapping text labels on gpplot2
R-plotly:standard Create Interactive Web Graphics via 'plotly.js'
R-sentimentr:standard Calculate Text Polarity Sentiment
R-tidyquant:standard Tidy Quantitative Financial Analysis
R-timetk:standard Tool Kit for Working with Time Series in R
R-viridis:standard Colorblind-Friendly Color Maps for R