QQplotit

QQplotit is a software tool for generating quantile-quantile (QQ) plots to assess how closely a dataset matches a reference distribution. The project emphasizes accessibility, reproducibility, and compatibility with common data analysis workflows.

Core features include support for multiple theoretical distributions (normal, t, gamma, lognormal, exponential, chi-square, and others), parameter estimation via maximum likelihood or robust methods, auto-fitting of distributions, configurable confidence bands via bootstrap or simulation, handling of tied observations, and options for different axes scales and reference lines. Plots can be produced in vector or raster formats and can be exported as PNG, SVG, or PDF.

QQplotit offers multiple interfaces: a Python API for integration into data pipelines, a command-line interface for quick use, and a lightweight R wrapper to facilitate use in R-based analyses. It is designed to work with datasets in common formats (CSV, TSV, DataFrame-like structures) and can operate on streaming data or large arrays with parallel processing options.

The project is open source and cross-platform, with releases distributed under a permissive license. It began as a community-driven tool in the late 2010s and has seen regular updates to expand supported distributions, improve rendering quality, and enhance documentation.

In practice, QQplotit is used in statistics education and data analysis to validate distributional assumptions, compare empirical data to theoretical models, and support reporting with standardized visuals. Limitations include less emphasis on advanced goodness-of-fit testing compared to specialized software and reliance on user-specified reference distributions.