From fea1d66fdb5430bcb969e74b698ca6eb71fb5ff2 Mon Sep 17 00:00:00 2001 From: dvelazq Date: Tue, 26 Nov 2024 11:28:54 -0500 Subject: [PATCH] Add badges --- .Rbuildignore | 1 + .gitignore | 1 + DESCRIPTION | 2 +- README.md | 2 ++ cran-comments.md | 2 +- 5 files changed, 6 insertions(+), 2 deletions(-) diff --git a/.Rbuildignore b/.Rbuildignore index 362cf85..c22a2e1 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -11,3 +11,4 @@ ^images$ ^\.github$ ^scatterbar$ +^CRAN-SUBMISSION$ diff --git a/.gitignore b/.gitignore index f26a87a..1a3af10 100644 --- a/.gitignore +++ b/.gitignore @@ -8,3 +8,4 @@ inst/doc .DS_Store .quarto docs +CRAN-SUBMISSION diff --git a/DESCRIPTION b/DESCRIPTION index 25a4f65..12d036d 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -16,7 +16,7 @@ Authors@R: comment = c(ORCID = "0000-0002-0212-5451"))) URL: https://github.com/JEFworks-Lab/scatterbar, http://jef.works/scatterbar/ BugReports: https://github.com/JEFworks-Lab/scatterbar/issues -Description: The scatterbar package provides a powerful and flexible tool for visualizing proportional data across spatially resolved contexts. By combining the concepts of scatter plots and stacked bar charts, scatterbar allows users to create scatterbar plots, which effectively display the proportions of different categories at each (x, y) location. This visualization is particularly useful for applications where understanding the distribution of categories across spatial coordinates is essential. This package features automatic determination of optimal scaling factors based on data, customizable scaling and padding options for both x and y axes, flexibility to specify custom colors for each category, options to customize the legend title, and integration with ggplot2 for robust and high-quality visualizations. +Description: Provides a powerful and flexible tool for visualizing proportional data across spatially resolved contexts. By combining the concepts of scatter plots and stacked bar charts, `scatterbar` allows users to create scattered bar chart plots, which effectively display the proportions of different categories at each (x, y) location. This visualization is particularly useful for applications where understanding the distribution of categories across spatial coordinates is essential. This package features automatic determination of optimal scaling factors based on data, customizable scaling and padding options for both x and y axes, flexibility to specify custom colors for each category, options to customize the legend title, and integration with `ggplot2` for robust and high-quality visualizations. For more details, see Velazquez et al. (2024) . License: GPL-3 Encoding: UTF-8 LazyData: FALSE diff --git a/README.md b/README.md index fda966e..5b200ea 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,8 @@ # scatterbar +[![R-CMD-check](https://github.com/JEFworks-Lab/scatterbar/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JEFworks-Lab/scatterbar/actions/workflows/R-CMD-check.yaml) +[![CRAN](https://www.r-pkg.org/badges/version/scatterbar)](https://CRAN.R-project.org/package=scatterbar) `scatterbar` is an open-source R package for displaying proportional data across spatially resolved contexts. This is the `scatterbar` R documentation diff --git a/cran-comments.md b/cran-comments.md index 858617d..62c010f 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,5 +1,5 @@ ## R CMD check results -0 errors | 0 warnings | 1 note +0 errors | 0 warnings | 0 note * This is a new release.