GeoViews is an open source Python library that makes it easy to explore and visualize any data that includes geographic locations.
It has particularly powerful support for multidimensional meteorological and oceanographic datasets, such as those used in weather, climate, and remote sensing research, but it is useful for almost anything that you would want to plot on a map.
GeoViews is built on the HoloViews library for building flexible visualizations of multidimensional data. GeoViews adds a family of geographic plot types based on the Cartopy library, plotted using either the Matplotlib or Bokeh plotting backends.
Features of GeoViews include:
- Provides a library of Element types which make it very easy to plot data on various geographic projections.
- Convenient wrappers for various geometry types. In addition to basic Path and Polygons types, which draw geometries from lists of arrays, GeoViews also provides the Feature and Shape types, which wrap cartopy Features and shapely geometries respectively.
- Feature Element – overlay a set of basic geographic features on top of or behind a plot. These features include coastlines, country borders, and land masses.
- Shape – wraps around any shapely geometry, allowing finer grained control over each polygon.
- GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types, which makes it a very convenient way of working with geometries with associated variables.
- Designed to make full use of multidimensional gridded datasets stored in netCDF or other common formats, via the xarray and iris interfaces in HoloViews.
- Make complex multi-figure layouts of overlaid objects.
- Uses both matplotlib and Bokeh as its plotting backend. The Bokeh backend has the virtue of offering more advanced tools to interactively explore data.
- Resample large grids.
Support: Documentation, GitHub, Twitter
Developer: Anaconda. The main developers are Jean-Luc Stevens, Philipp Rudiger, and James A. Bednar
License: BSD 3-Clause “New” or “Revised” License