fitPlotpy: A Python Package for Plotting Probability Distribution

Abstract

The fitPlotpy package offers a comprehensive collection of functions for visualizing univariate probability distributions. It provides an integrated framework for plotting probability density functions, cumulative distribution functions, survival functions, and hazard functions. In addition, the package includes tools to compute and display fundamental descriptive measures of a distribution, such as the mean, median, mode, and measures of dispersion, as well as higher-order moments including skewness and kurtosis. Beyond descriptive and theoretical plots, fitPlotpy supports diagnostic visualization through fitted probability density and cumulative distribution plots, quantile–quantile (QQ) plots, and probability–probability (PP) plots. These features are complemented by comprehensive graphical summaries, enabling an effective and detailed overview of distributional characteristics and model fit.