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programminghistorian.org | ||
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statsandr.com
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| | | | | Learn how to create professional graphics and plots in R (histogram, barplot, boxplot, scatter plot, line plot, density plot, etc.) with the ggplot2 package | |
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indrajeetpatil.github.io
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| | | | | Extension of ggplot2, ggstatsplot creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) . | |
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www.cedricscherer.com
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| | | | | An extensive tutorial containing a general introduction to ggplot2 as well as many examples how to modify a ggplot, step by step. It covers several topics such as different chart types, themes, design choices, plot combinations, and modification of axes, labels, and legends, custom fonts, interactive charts and many more. | |
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juliasilge.com
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| | | A data science blog | ||
