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Working with Messy Data in OpenRefine In-Person

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 workshop will provide an introduction to OpenRefine, a powerful open source tool for exploring, cleaning and manipulating “messy” data. Through hands-on activities, using a variety of datasets, participants will learn how to:

  • Explore and identify patterns in data
  • Normalize data using facets and clusters
  • Manipulate and generate new textual and numeric data
  • Transform and reshape datasets
  • Use the General Regular Expression Language (GREL) to undertake advanced manipulations
  • Use APIs to augment existing datasets

Location: Robarts Library, 5th Floor. Map & Data Library Computer Lab

Date:
Wednesday, October 2, 2019
Time:
2:00pm - 5:00pm
Time Zone:
Eastern Time - US & Canada (change)
Location:
Map & Data Library
Campus:
St. George (Downtown) Campus
Categories:
  Data & Statistics     Digital Tools     Library Research     Programming & Software  
Registration has closed.

Event Organizer

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Kelly Schultz

Kelly Schultz (she/her) is a Data Librarian at the Map & Data Library. She has a BASc (Computer Engineering) and a MI, both from UofT.

She supports Data Visualization; Qualitative Data Analysis; Data Cleaning; Network Visualization and Analysis.

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Nick Field

Nick Field (they/them) is the Data Support Specialist at the Map & Data Library. They have a PhD from U of T, where they wrote their doctoral dissertation on archaeological maps of the Silk Road.

They help researchers and students find and work with maps and geospatial data.

 

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Map & Data Library