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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes
Learn both basic and advanced techniques for transforming data using OpenRefine, an essential open-source tool for fast clean up of tabular data in preparation for analysis.
Software: OpenRefine
Duration: 60 min

Room description:

During the Fall 2021 semester, some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering

Prerequisites:

None

Skills Taught / Learning Outcomes:
  • Learning how to use the OpenRefine interface, import datasets
  • Understand how OpenRefine documents changes to datasets to enable reproducible scholarship
  • Perform mass edits on data syntax to enable accurate data analysis
  • Perform automated transformations to save time in cleaning data
  • Learn how to use OpenRefine web connections to automate identification of data entries and to geocode data
Class Materials:

Slides: https://nyu-dataservices.github.io/CleaningData-OpenRefine/

Related Classes:

Data Visualization with Tableau

Introduction to Stata

Introduction to R

Introduction to JMP

Introduction to SAS

Introduction to MATLAB

Introduction to Python

Data Wrangling in R

Data Wrangling in Stata

Introduction to ArcGIS

Data Cleaning for GIS

Additional Training Materials:

OpenRefine official videos

Programming Historian tutorial

Data carpentry lesson [exercise/project]

Feedback: bit.ly/feedbackds

Upcoming sessions for this tutorial