This chapter provides a series of activities that allow you to practice your Python plotting skills using differen types of data.
New course: Earth Analytics - Spring 2017
A newly designed Earth Systems Analytics course - GEOG 4563 / 5563 is being held this Spring 2017 on the CU Boulder campus. This course fuses key topics related to the grand challenges in science, remote sensing and computationally intensive approaches.
Recent Classroom Modules
Below, is a list of the most recent classroom modules. Classroom modules consist of background materials, readings and student activities. Classroom modules are data intensive, however many contain pre-populated interactive plots and maps that can be used to teach a class without having to actually process data.
Check out the instructor notes to better understand how each lesson can be taught.
There are two primary spatial data formats that are useful for earth data science, vector and raster. Learn about these two common spatial data formats for earth data science workflows.
MODIS is remote sensing data that is stored in the HDF4 file format. Learn how to open and manipulate data stored in the HDF4 file format using open source Python.
Recent code tutorials
Check out our latest code tutorials. Leave questions in the comment box at the bottom. We’ll try our best to help!