Plot an empirical cumulative distribution function (CDF) in Python, comparing a manual Matplotlib version with Seaborn's ecdfplot.

Plot a confusion matrix in Python using scikit-learn's ConfusionMatrixDisplay or a manually styled Seaborn heatmap.

Build a ridge plot (joyplot) in Seaborn using a FacetGrid of overlapping KDE curves.

Plot grouped bar charts in Seaborn using hue, control group order, spacing, and orientation.

Control the size and shape of a Seaborn catplot using its height and aspect arguments instead of figsize.

Save Seaborn plots at print- or presentation-quality resolution using dpi, bbox_inches, and vector formats.

Set custom color palettes in Seaborn using hex lists, named palettes, category-to-color dictionaries, and diverging palettes.

Plot bivariate distributions in Seaborn with jointplot, choosing from scatter, hex, and kde kinds.

Overlay a swarm (scatter) plot on a Seaborn box plot to show every point alongside the summary.

Create, modify, and remove confidence interval bands in Seaborn with the errorbar parameter.

Rotate tick labels on Seaborn FacetGrid and pairplot figures with set_xticklabels and a small loop.

Style Seaborn heatmaps by annotating values, formatting labels, and masking cells you want to hide.

Add data values on top of Seaborn bar plots with ax.bar_label and custom formatting.

Control the x-axis category order in Seaborn with order=, CategoricalDtype, and hue_order.

Switch the look of any Matplotlib chart in one line with built-in style sheets like ggplot, dark_background, seaborn, and fivethirtyeight.

Build clear Seaborn heatmaps, from a simple matrix to annotated correlation charts.

Using Matplotlib, Seaborn, Altair and Plotly to create a line chart with a confidence interval

A complete guide to creating stacked bar charts in python using Pandas, Matplotlib, Seaborn, Plotnine and Altair

A short tutorial on creating and customizing violin plots in Seaborn

A short intro to get up and running with Seaborn