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.
All the primary computing systems & services offered by 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:
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!
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.
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
- GitHub is an incredibly powerful tool for version control management - a must-know skill for developers, researchers, and anyone who uses a command line often in their work. Come learn about the basics of Git and GitHub, create a repository and use the RStudio GitHub integration to upload your work to GitHub.
- GitHub is an incredibly powerful tool for version control management - a must-know skill for developers, researchers, and anyone who uses a command line often in their work. Come learn about the basics of Git and GitHub, create a repository and make your first pull request.
- Please download GitHub Desktop before the session: https://desktop.github.com.
Excel pivot tables help you to quickly summarize, report and find patterns in your datasets. This short course will cover how to setup a pivot table from scratch and special techniques to make the most of this feature. The use of Excel Pivot Tabes will help you to organize, visualize and gain insights from your data.
Note: Class offered via Canvas. Link to be provided via registration.
Please contact Monica Rivero if you have any questions.
Have you ever wanted to learn how to use R to make estimates about your dataset? Come to this session prepared to learn about the basics of multiple linear regression, and use an interactive demo website where you can upload your own data as a CSV file and learn how to make predictions with it. We will have a sample CSV file prepared for you, or bring your own.
So you’ve gotten really good at python. Your algorithm is perfect, your data is clean … and it takes hours to run. In fact, you just realized that you could be running this in a dozen different ways by tweaking some parameters, but that would take days to run … if you get really lucky and it completes with no errors. It’s time to parallelize your code. In this class, you will learn a couple basic methods for parallelizing your code and completing your jobs in a fraction of the time. Prior experience with python is strongly recommended.