Research

This course will teach the basics of time series analysis, a statistical approach to dealing with sequential data sets. We'll cover trends, autocorrelation, moving averages, and modeling with Facebook's prophet library, all with stock markets as a motivating example!

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

GitHub is a place where millions of developers gather every day to collaborate on open source software. It hosts billions of lines of code. This course will give a step-by-step tutorial for beginners to get started with git and Github. Learn all the important pieces of GitHub that you should know.

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

This workshop will discuss how to select colors that complement the message of your data visualization without sacrificing readability. We will also review best practices for using color to encode numerical values and explore how color can be used to accent information and establish a clear visual hierarchy.

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

This workshop will review research in visual perception and explore how different visual forms impact a viewer’s understanding of the data. We will also discuss general guidelines for visualization design. Participants will have the opportunity to apply what they learned during a hands-on visualization exercise.

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

Excel is an easy to use tool for creating charts and graphs. This short workshop will provide tips and techniques for refining and customizing Excel’s basic chart types. It will also cover some advanced charts and methods to help in visualizing your data.

Please contact Monica Rivero if you have any questions.

Matplotlib is the most popular data visualization library in Python. It allows us to create figures and plots. This tutorial is intended to help you get up-and-running with Matplotlib quickly. We’ll go over how to create the most commonly used plots, and discuss when to use each one.

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

Pandas is one of the most useful Python libraries, used for the creation, manipulation, and analysis of data tables. Attendees will learn the fundamentals of table creation and manipulation in Pandas.

Please contact dataworkshop@rice.edu if you need to cancel your registration or have any questions.

Drowning in data? Not sure how to organize and back it up? This hands-on, interactive workshop will share tips for effectively organizing, documenting and storing research data. Participants will walk away with ideas for completing a data management plan, naming and organizing files, and safely storing data. We’ll also explore some of the features of Box, a cloud-based storage and collaboration platform used by Rice University.

This course will build upon the basics of R and introduce basic forms of data visualization techniques in R as well as more advanced forms of data manipulation that weren't covered in the introductory class through use of for loops and if statements. Individuals will be able to perform data analysis and visualization processes on large data sets as well as clean data to perform more efficient analysis by the end of this course.