# GeoViews ¶

Geographic visualizations for HoloViews

GeoViews is a Python library that makes it easy to explore and visualize geographical, meteorological, and oceanographic datasets, such as those used in weather, climate, and remote sensing research.

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 packages. Each of the new  GeoElement  plot types is a new HoloViews  Element  that has an associated geographic projection based on  cartopy.crs  . The  GeoElements  currently include  Feature  ,  WMTS  ,  Tiles  ,  Points  ,  Contours  ,  Image  ,  QuadMesh  ,  TriMesh  ,  RGB  ,  HSV  ,  Labels  ,  Graph  ,  HexTiles  ,  VectorField  and  Text  objects, each of which can easily be overlaid in the same plots. E.g. an object with temperature data can be overlaid with coastline data using an expression like  gv.Image(temperature) * gv.Feature(cartopy.feature.COASTLINE)  . Each  GeoElement  can also be freely combined in layouts with any other HoloViews  Element  , making it simple to make even complex multi-figure layouts of overlaid objects.

With GeoViews, you can now work easily and naturally with large, multidimensional geographic datasets, instantly visualizing any subset or combination of them, while always being able to access the raw data underlying any plot. Here's a simple example:

In [1]:
import geoviews as gv
import geoviews.feature as gf
import xarray as xr
from cartopy import crs

gv.extension('bokeh', 'matplotlib')