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* [Pandas] (http://pandas.pydata.org/) - Open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
* [Shapely] (https://pypi.python.org/pypi/Shapely) - Manipulation and analysis of geometric objects in the Cartesian plane.
* [Cartopy] (http://scitools.org.uk/cartopy/) - A library providing cartographic tools for python for plotting spatial data.
* [rtree] (http://toblerity.org/rtree/) - For efficiently querying spatial data.
* [Rtree] (http://toblerity.org/rtree/) - For efficiently querying spatial data.
* [NodeBox-opengl] (http://www.cityinabottle.org/nodebox/) - For playing around with animations.
* [Statsmodels] (http://statsmodels.sourceforge.net/) - Python module that allows users to explore data, estimate statistical models, and perform statistical tests.
* [NumPy] (http://www.numpy.org/) - NumPy is the fundamental package for scientific computing with Python.
* [geopy] (https://github.com/geopy/geopy) - geopy is a Python 2 and 3 client for several popular geocoding web services.
* [IPython] (http://ipython.org/) - For a wondering interactive environment in which to play.
* [FreeType] (https://code.google.com/archive/p/freetype-py/) - For converting font glyphs to polygons.
* [PyQGIS] (http://docs.qgis.org/testing/en/docs/pyqgis_developer_cookbook/) - Python for QGIS.
* [Fiona] (http://toblerity.org/fiona/) - For making it easy to read/write geospatial data formats.
* [matplotlib] (http://matplotlib.org/) - Python 2D plotting library.
* [networkx] (http://networkx.github.io/) - To work with networks.
* [PySAL] (http://pysal.readthedocs.io/en/latest/) - For all your spatial econometrics needs.
* [Descartes] (https://pypi.python.org/pypi/descartes) - Plot geometries in matplotlib.
* [PyShp] (https://code.google.com/archive/p/pyshp/) - For reading and writing shapefiles.
* [PyProj] (https://github.com/jswhit/pyproj) - For conversions between projections.