bayesplot R package for plotting Bayesian models
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Updated
Sep 8, 2025 - R
bayesplot R package for plotting Bayesian models
A gallery of animations in statistics and utilities to create animations
shinystan R package and ShinyStan GUI
SUpporting GRaphics with R for ANalysing Time Series
'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
A Toolkit for Interactive Statistical Data Visualization
Modern Statistical Graphics (《现代统计图形》的附加包)
Interactive Jupyter notebooks showcasing data visualization with Matplotlib and Seaborn for learners and data practitioners.
data science, statistics and machine learning
Visualizing the Covid-19 pandemic with doubling rates
📖 现代统计图形(第二版) Modern Statistical Graphics (Second Edition)
Materials for a workshop in June 2025
A Toolkit for Interactive Statistical Data Visualization
In this course, you will learn how to use Seaborn, a Python library for producing statistical graphics. You will learn how to use Seaborn's sophisticated visualization tools to analyze your data, create informative visualizations, and communicate your results with ease.
Supplementary materials for the following publication: Davydenko, A., & Goodwin, P. (2021). Assessing point forecast bias across multiple time series: Measures and visual tools. International Journal of Statistics and Probability, 10(5), 46-69. https://doi.org/10.5539/ijsp.v10n5p46
This comprehensive course covers the fundamental concepts and practical techniques of Matplotlib, the essential plotting library in Python. Learn to create various types of charts and visualizations including line plots, bar charts, scatter plots, histograms, pie charts, and subplots.
Slides for a presentation at ResBaz 2024
Data visualization examples using Seaborn in Python, including relational, categorical, and distribution plots with customization.
Performed exploratory data analysis (EDA) in python on the world happiness report datasets (for years 2015, 2016, 2017, 2018, and 2019) from Kaggle; to analyze how measurements of well-being can effectively help assess the progress of nations across the world.
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