Python is a generic programming language designed to support many different
applications. Because of this, many commonly performed spatial tasks for science
including plotting and working with spatial data take many steps of code.
EarthPy builds upon the functionality developed for raster data (rasterio) and
vector data (geopandas) in Python and simplifies the code needed to:

- Stack and crop raster bands from data such as Landsat into an easy to use
  numpy array;
- Work with masks to set bad pixels such a those covered by clouds and
  cloud-shadows to NA (mask_pixels());
- Plot rgb (color), color infrared and other 3 band combination images
  (plot_rgb());
- Plot bands of a raster quickly using plot_bands();
- Plot histograms for a set of raster files;
- Create discrete (categorical) legends;
- Calculate vegetation indices such as Normalized Difference Vegetation Index
  (normalized_diff());
- Create hillshade from a DEM.

EarthPy also has an io module that allows users to

- Quickly access pre-created data subsets used in the earth-analytics courses
  hosted on www.earthdatascience.org;
- Download other datasets that they may want to use in their workflows.