Data Exploration and Analysis Lessons

Explore, Analyze and Visualize Environmental Data with R and Python

In Earth data science, often the greatest amount of time is spent figuring out how to open, clean up and explore your data. Once the data are cleaned up, you can then begin to visualize and analyze them. In the lessons below, learn the basic skills needed to open, clean up, plot and analyze scientific data.

Work With Twitter Social Media Data in R - An Introduction

This lesson will discuss some of the challenges associated with working with social media data in science. These challenges include working with non standard text, large volumes of data, API limitations, and geolocation issues.

last updated: 10 Jan 2018

Adjust plot extent in R.

In this lesson you will review how to adjust the extent of a spatial plot in R using the ext() or extent argument and the extent of another layer.

last updated: 10 Jan 2018

Plot Grid of Spatial Plots in R.

In this lesson you learn to use the par() or parameter settings in R to plot several raster RGB plots in R in a grid.

last updated: 10 Jan 2018