Clean Up Crew: Skills for Fixing Messy Data
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Interested in DataGeek Workshops?
Contact Mary Hamman regarding future opportunities.
Clean Up Crew: Skills for Fixing Messy Data
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Two schedules are offered for your convenience. The same content is provided via each schedule. You choose which schedule works best for you! |
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4 Weeks
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1 Week
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| April 5–May 1 | April 26–May 1 |
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Workshop participants will meet virtually for a Live Project Day: |
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Data in the wild is far from the tame well-organized examples you may have seen in class or worked with in online training programs. It’s messy in all sorts of unique ways and often requires a lot of time and energy to clean. In fact, most data analysts agree data cleaning is one of the most difficult parts of their jobs. In this workshop you’ll learn best practices for preparing “tidy data” and some great tips and tricks for taming your own messy data. You’re encouraged to bring your own data to work on throughout the workshop, but if you don’t have any, don’t worry. We’ll be happy to share our mess with you! No prior experience with R needed.
Learning Outcomes
- Understand the anatomy of tidy data and develop data wrangling skills to convert messy data to tidy data.
- Identify variable types (including dates) and properly convert variables.
- Distinguish between wide and long data and use pivot functions to reshape.
- Distinguish between joins, binds, and set operations and use each appropriately to obtain the desired resulting dataframe.
Who should attend:
Anyone seeking upgrade and expand their data skills—whether you’re just beginning or you’re already a bit of a data geek—can benefit from DataGeek Workshops. Workshops are open to all skill levels and job roles because content is personalized to fit your goals. No data analysis or prior experience with analysis software is necessary. Those already using R or Tableau can set goals to expand proficiency.
This workshop is for anyone who wants to:
- Feel more confident when working with data
- Handle large data sets more efficiently
- Save time and reduce errors in data management
- Document data workflow
- Clean messy data
- Automate reports and save time
- Provide clear visuals and dashboards to accurately convey insight
- Understand Application Programming Interface (API)
- Create API calls and prepare the resulting data
Those already using R or Tableau can set goals to expand proficiency.