03 — Data Visualization¶
Charts that communicate: Matplotlib, seaborn, Plotly, Bokeh, Altair, and geospatial mapping.
Scope¶
Cheat sheets for static, statistical, interactive, and geographic visualization in Python. Data manipulation belongs to 02-Data-Analysis.
Cheat Sheets¶
| Cheat Sheet | Description |
|---|---|
| matplotlib.md | Static publication charts: figures/axes, all chart types, subplots, annotations, styles, exports |
| seaborn.md | Statistical charts from DataFrames: distributions, categoricals, heatmaps, facets, themes |
| plotly.md | Interactive charts with Plotly Express: hovers, subplots, animations, static export via kaleido |
| bokeh.md | Interactive web plots: glyphs, ColumnDataSource, hover tools, linked panels, widgets |
| altair.md | Declarative Vega-Lite charts: encodings, transforms, faceting, layering, selections |
| folium.md | Interactive Leaflet maps: markers, choropleths, heatmaps, layer control, HTML export |
| geopandas.md | Geospatial vector data: GeoDataFrames, CRS, spatial joins, choropleth plots, basemaps |
Planned Cheat Sheets¶
- Plotnine — grammar-of-graphics plotting for Python
Contribute¶
- Template: CHEATSHEET_TEMPLATE.md
- Guide: CONTRIBUTING.md