Python libraries for doing statistics

Python libraries for doing statistics#

see draft here: https://docs.google.com/document/d/1a-Ohl3hs7w8AiOr85PxW0DZP1ofFK02sk55IEw0zQPE/edit?tab=t.0

Click here to run the notebook interactively, so you can play with the code examples.

Notebook setup#

# Install stats library
%pip install --quiet ministats 

[notice] A new release of pip is available: 25.2 -> 25.3
[notice] To update, run: pip install --upgrade pip

Note: you may need to restart the kernel to use updated packages.

# Figures setup
import matplotlib.pyplot as plt
import seaborn as sns

plt.clf()  # needed otherwise `sns.set_theme` doesn't work
sns.set_theme(
    style="whitegrid",
    rc={'figure.figsize': (7, 2)},
)
# High-resolution figures please
%config InlineBackend.figure_format = 'retina'

def savefig(fig, filename):
    fig.tight_layout()
    fig.savefig(filename, dpi=300, bbox_inches="tight", pad_inches=0)

<Figure size 640x480 with 0 Axes>

Introduction#

Data management with Pandas#

Numerical computing with NumPy#

Scientific computing with SciPy#

Data visualization with Seaborn#

Frequentist statistics with Statsmodels#

Honorable mention: pingouin#

Bayesian statistics with Bambi (based on PyMC)#

Conclusion#

Contents