Data @ Rice

Colors in Data Visualization

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.

Introduction to Effective Data Visualization

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.

Introduction to Rice's Research Computing Infrastructure

Learn about Rice’s networked storage, its virtual machine farm, and its supercomputing cluster. This workshop will introduce you to what these resources are, how to gain access to them, and integrated use cases that will be of interest to humanists and scientists alike, in 3 areas: 1) data-driven web applications, 2) massively parallelized processes, 3) managing large datasets.

Python-Pandas

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.

 

Introduction to Data Management

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.

R Visualization and Data Manipulation

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.

Introduction to R

This course will cover the foundational elements of coding in R including understanding the interface and syntax of R as well as basic techniques for storing and manipulating data sets in R. It will run through the different data types utilized in R as well as basic commands and functions that can be used for data analysis.

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