Carson Farmer

Folium is a Python package that can be used to create interactive maps in Jupyter Notebook. Learn how to create interactive maps with raster overlays in Python using Folium.

You can use the Twitter RESTful API to access tweet data from Twitter. Learn how to use tweepy to download and work with twitter social media data in Python.

This lesson walks through the process of retrieving and manipulating surface water data housed in the Colorado Information Warehouse. These data are stored in JSON format with spatial x, y information that support mapping.

API's allow you to automate access and downloading data in your code to support open reproducible science. Learn how how to use API's to download data from the internet using open source python.

Learn how to perform a basic sentiment analysis using the tidytext package in R.

This lesson provides an example of modularizing code in R.

This lesson provides an example of modularizing code in R.

Text mining is used to extract useful information from text - such as Tweets. Learn how to use the Tidytext package in R to analyze twitter data.

You can use the Twitter RESTful API to access data about Twitter users and tweets. Learn how to use rtweet to download and analyze twitter social media data in R.

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.

This lesson covers the basics of creating an interactive map using the leaflet API in R. We will import data from the Colorado Information warehouse using the SODA RESTful API and then create an interactive map that can be published to an HTML formatted file using knitr and rmarkdown.

This lesson walks through the process of retrieving and manipulating surface water data housed in the Colorado Information Warehouse. These data are stored in JSON format with spatial x, y information that support mapping.

This lesson covers accessing data via the Colorado Information Warehouse SODA API in R.

This lesson reviews how to use functions within the RCurl package to access data on a secure (https) server in R.

This lesson provides an example of modularizing code in R.

In this module, you learn 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.

To explore uncertainty in remote sensing data, it is helpful to compare ground-based measurements and data that are collected via airborne instruments or satellites. Learn how to create scatter plots that compare values across two datasets.

For many scientific analyses, it is helpful to be able to select raster pixels based on their relationship to a vector dataset (e.g. locations, boundaries). Learn how to extract data from a raster dataset using a vector dataset.