Max Joseph

Max Joseph has contributed to the materials listed below. Max is a data scientist with the Analytics Hub at Earth Lab and maintains this website.

Course Lessons

Course lessons are developed as a part of a course curriculum. They teach specific learning objectives associated with data and scientific programming. Max Joseph has contributed to the following lessons:

Submit a pull request on the GitHub website

Learn how to create and submit a pull request to another repo.

How to fork a repo in GitHub

Learn how to fork a repository using the GitHub website.

Introduction to undoing things in git

Learn how to undo changes in git after they have been added or committed.

First steps with git: clone, add, commit, push

Learn basic git commands, including clone, add, commit, and push.

An introduction version control

Learn what version control is, and how Git and GitHub are used in a typical version control workflow.

Programmatically accessing geospatial data using API's - Working with and mapping JSON data from the Colorado Information Warehouse in R

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.

Programmatically access data using an API in R - The Colorado Information Warehouse

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

Introduction to the JSON data structure

This lesson covers the JSON data structure. JSON is a powerful text based format that supports hierarchical data structures. It is the core structure used to create geoJSON which is a spatial version of json that can be used to create maps. JSON is preferred for use over .csv files for data structures as it has been proven to be more efficient - particulary as data size becomes large.

Access secure data connections using the RCurl R package.

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

An example of creating modular code in R - Efficient scientific programming

This lesson provides an example of modularizing code in R.

Introduction to APIs

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.

Use lapply in R Instead of For Loops to Process .csv files - Efficient Coding in R

Learn how to take code in a for loop and convert it to be used in an apply function. Make your R code more efficient and expressive programming.

If Statements, Functions, and For Loops

Learn how to combine if statements, functions and for loops to process sets of text files.

Create For Loops

Learn how to write a for loop to process a set of .csv format text files in R.

Working with Function Arguments

Learn how to work with function arguments in the R programming language..

Get to Know the Function Environment & Function Arguments in R

This lesson introduces the function environment and documenting functions in R. When you run a function intermediate variables are not stored in the global environment. This not only saves memory on your computer but also keeps our environment clean, reducing the risk of conflicting variables.

How to Write a Function in R - Automate Your Science

Learn how to write a function in the R programming language.

What Could be Improved In this R Code?

Write Efficient Scientific Code - the DRY (Don't Repeat Yourself) Principle

This lesson will cover the basic principles of using functions and why they are important.

Data tutorials

Getting started with the PetaLibrary

This tutorial explains how members of Earth Lab can gain access to the PetaLibrary at the University of Colorado Boulder. It also outlines the process for setting up Globus to transfer files between endpoints (e.g., your local machine and the PetaLibrary).