This paper introduces Pingouin, an open-source Python package designed to address the gap between Python and R in terms of statistical analysis. Despite Python's popularity in data science and machine learning, it lags behind R in general statistics. Pingouin provides user-friendly functions for a wide range of statistical tests, including ANOVAs, ANCOVAs, post-hoc tests, non-parametric tests, effect sizes, Bayesian T-tests, repeated measures correlations, robust correlations, and circular statistics. The package is built on the Pandas library and integrates seamlessly into data analysis pipelines. It includes extensive documentation, an API, and Jupyter notebook examples to facilitate its use.This paper introduces Pingouin, an open-source Python package designed to address the gap between Python and R in terms of statistical analysis. Despite Python's popularity in data science and machine learning, it lags behind R in general statistics. Pingouin provides user-friendly functions for a wide range of statistical tests, including ANOVAs, ANCOVAs, post-hoc tests, non-parametric tests, effect sizes, Bayesian T-tests, repeated measures correlations, robust correlations, and circular statistics. The package is built on the Pandas library and integrates seamlessly into data analysis pipelines. It includes extensive documentation, an API, and Jupyter notebook examples to facilitate its use.