Statistical visualization on matplotlib with native pandas support. Auto aggregation, CIs, grouping for distributions (histplot, kdeplot), categorical (boxplot, violinplot), relational (scatterplot, lineplot), regression (regplot, lmplot), matrix (heatmap, clustermap), grids (pairplot, FacetGrid). Use for quick statistical summaries; matplotlib for fine control; plotly for interactive HTML.
Receba novas skills de Dados e Análise toda segunda
1 email curto, só com as skills novas de Dados e Análise. 4 minutos de leitura, sem spam, cancela com 1 clique.
Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.
Ler descrição completaRecolher descrição
Seaborn — Statistical Plots
Overview
Seaborn is a Python library for statistical data visualization built on top of matplotlib. It works directly with pandas DataFrames, automatically handles grouping by categorical variables, computes confidence intervals and kernel density estimates, and produces attractive publication-ready figures with minimal configuration. Seaborn separates axes-level functions (embeddable in custom layouts) from figure-level functions (with built-in faceting), enab
[Description truncada. Veja o README completo no GitHub.]