Data @ Rice

Remote Access to Computing Resources

All the primary computing systems & services offered by the Center for Research Computing (CRC) are available to researchers who are working from off campus.

In fact, "remote" access workflows are often the same as best practices for using our resources.

Get a schematic overview, along with some practical examples of how to use the following in concert with one another to multiply your computing power:

Containerized Data Visualization with Docker and Plotly

Learn how to create lightweight, interactive data visualization apps for medium-sized datasets. This will be useful for introducing students and researchers to basic exploratory data analysis. We will begin with a basic introduction to data frames in Python and R using a basic dataset; then we will see how to render that data as an interactive dashboard in Python and R; finally, we will deploy see what deploying your app to a free public web server in Heroku looks like!

Census with Python

U.S. Census Bureau conducts surveys on demographic, economic and population data. In this class, we will introduce Census Data Products; learn how to access Decennial Census of Population and Housing and American Community Survey using Census API. We will also anlyze the data with Python Pandas library. 

Python for Excel Users

Excel is a popular and Powerful tool for data storage and analysis. The openpyxl module allows Python to read and modify Excel files, automate your boring tasks and increase your work efficiency. In this workshop, you will learn:

  • How to import Excel workbook
  • Change sheet name
  • Create / remove sheet 
  • Change fonts
  • Write values to certain cells
  • Automate your boring tasks with code