A Python data visualization library based on Matplotlib, providing a high-level interface for drawing attractive and informative statistical graphics.
Seaborn
- Pitón
- Gráficos 2D, IA y aprendizaje automático, Bioinformática, Análisis de datos, Calidad
- Pensamiento de diseño, Aprendizaje automático, Análisis estadístico, Control estadístico de procesos (CEP), Experiencia de usuario (UX), Interfaz de usuario (UI)
Características:
- Statistical plotting (distributions,relationships,categorical data),attractive default styles,high-level functions for common plot types (histograms,scatter plots,bar plots,box plots,violin plots,heatmaps,clustermaps,pair plots,joint plots),integration with pandas DataFrames,color palette management,regression model plotting
Precios:
- Gratis
- Produces aesthetically pleasing statistical visualizations with minimal code, simplifies complex plot creation, excellent integration with pandas, good for exploratory data analysis, extensive documentation and examples.
- Less customizable for very fine-grained plot details compared to direct Matplotlib (though it builds on it), primarily focused on statistical visualization (not general-purpose plotting like Matplotlib), performance can be an issue with extremely large datasets without pre-aggregation.
Ideal para:
- Data scientists, statisticians, and analysts for creating informative and visually appealing statistical graphics to explore and understand data.