Geographic visualizations for HoloViews.
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GeoViews is a 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 is useful for almost anything that you would want to plot on a map! You can see lots of example notebooks at geoviews.org.
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,
Path, Polygons, Shape, Contours, LineContours,
FilledContours, Image, ImageStack, RGB, QuadMesh, TriMesh,
Graph, HexTiles, Labels, Text, Rectangles, Segments,
VectorField and WindBarbs 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.
You can then install GeoViews and all of its dependencies with the following:
conda install geoviewsAlternatively, you can install the geoviews-core package, which only installs the minimal dependencies required to run geoviews:
conda install geoviews-coreIf you want to try out the latest features between releases, you can
get the latest dev release by specifying -c pyviz/label/dev.
You can also install it with pip:
python -m pip install geoviews