Python vector packages implement community standards for vector encoding. While these can seem complex, tools exist for conversion into various forms, and many of the tools including common interfaces for exchanging data across tools.
Packages exist for easily reading data from file-based and other serialized data formats.
Most of these packages involve a series of steps to handle data, such as stepping through features via a loop, etc. Most tools do one or a couple of things only. GeoPandas solves these problems by enabling operations on feature collections in one step, and bundling multiple tools via a coherent interface that builds on Pandas.
While still a young package, GeoPandas offers powerful capabilities.
GeoJSON and the common __geo_interface__ enable convenient and widespread geospatial data object exchange across geospatial packages in Python.
Most of these links are blog posts. The date shown is the blog post date, or else some other document date. A couple of links are in French, all from the same blog; apologies, but they’re excellent resources – if you know French! They’re probably useful even if you don’t know French.
2015-12: Plotting a GeoDataFrame with folium. Includes cool example of going from geodataframe.crs to projection information using pyepsg; plus reprojecting with geopandas to_crs method and serializing as GeoJSON to display in Folium! Including use of Carto basemaps in Folium.