
ggstatsplot
CreatorEnhancing {ggplot2} plots with statistical analysis
R and Python packages for data analysis, visualisation, statistical reporting, and developer tooling — 69M+ recorded downloads across CRAN and PyPI, including packages I co-author.
This page covers my R and Python package portfolio. It is not an exhaustive list of my public repositories: standalone applications, templates, experiments and presentation sources live on my GitHub profile.
The 4 packages I created account for 1,507,988 recorded downloads; the 69M+ total covers all 18 packages, including those I co-author. Downloads are cumulative registry counts, not unique users. CRAN counts cover the available cranlogs history; PyPI uses pepy.tech totals, retaining the previous count when unavailable. A new PyPI package may initially use a recent-window pypistats estimate.
Many of these packages grew out of methodological needs in my own research. The broader context is summarised in Research, while peer-reviewed software papers are listed under Publications.
18 packages

Enhancing {ggplot2} plots with statistical analysis

Tidy dataframes and expressions with statistical details

Apply functions to all combinations of elements from multiple iterables

Convert Markdown to LinkedIn-compatible post format

Significance brackets for ggplot2

Easy access to model information for various model objects

Easy data preparation and statistical transformations

Static code analysis for R

Assessment, comparison and testing of statistical models

Extracting, computing and exploring model parameters

Understanding and describing Bayesian models and posterior distributions

Non-invasive pretty printing of R code

Indices of effect size and standardised parameters

Methods for correlation analysis

Visualisation toolbox for beautiful and publication-ready figures

Estimation of model-based predictions, contrasts and means

Automated reporting of results and statistical models

A unified framework for easy statistical modelling, visualisation, and reporting
Download counts from CRAN and PyPI, last updated .