Event box

Data Cleaning Made Easier with OpenRefine In-Person

In-Person Location: Robarts Library, 5th Floor, Room 5-053 (directly across from the elevator). Map & Data Library Computer Lab

In an ideal world, any data you collect or obtain would be clean and formatted perfectly for analysis and visualization. But the reality is that data can be really messy! Cleaning and reformatting your data can be a time-consuming and tedious task, but there are ways to speed things up and automate repetitive tasks. OpenRefine can help!

This 2-hour workshop will provide an introduction to OpenRefine, a powerful open-source tool for exploring, cleaning, and manipulating “messy” data, to prepare it for analysis and visualization. Through a combination of lecture, demonstrations, and activities, participants will learn how to:

  • Understand what kinds of tasks are involved in data cleaning
  • Understand why data cleaning is important
  • Get started using OpenRefine for data cleaning to manipulate both textual and numeric data, transform and reshape datasets, and search and filter data in a variety of ways

This workshop is designed for those new to data cleaning and OpenRefine. There are no prerequisites or assumptions of knowledge of math, statistics, or programming.

Map & Data Library workshops, such as this one, are a welcoming and inclusive environment for learning. To learn more, check out our Code of Conduct.

Alternatively, if you would like to learn more about data cleaning and OpenRefine on your own, you are encouraged to explore our OpenRefine online tutorials or self-enroll in our online, self-paced workshop (same content as this live one): Working with Messy Data in OpenRefine

Date:
Thursday, October 13, 2022
Time:
2:00pm - 4:00pm
Time Zone:
Eastern Time - US & Canada (change)
Location:
Map & Data Library
Campus:
St. George (Downtown) Campus
Categories:
  Data & Statistics     Digital Tools     Programming & Software  
Registration has closed.

Event Organizer

Profile photo of Map & Data Library
Map & Data Library