This module explores the use of social media data - specifically Twitter data to better understand the social impacts and perceptions of natural disturbances and other events. Working with social media requires the use of API's to access data, text mining to extract useful information from non-standard text and then finally analysis using text-mining workflows
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.
In this module, we introduce various ways to access, download and work with data programmatically. These methods include downloading text files directly from a website onto your computer and into R, reading in data stored in text format from a website, into a data.frame in R and finally, accessing subsets of particular data using REST API calls in R.
This module will overview the basic principles of DRY - don't repeat yourself. It will then walk you through incorporating functions into your scientific programming to increase efficiency, clarity, and readability.
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!
This tutorial demonstrates how to access and visualize crime data for Denver, Colorado.
This tutorial outlines the process of installing the Google Earth Engine Python API client.