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Intermediate Data Analysis with Python

Intermediate Data Analysis with Python

Data in the wild can be messy, malformed, and/or generally ill-suited to the specifications of statistical analyses and machine-learning techniques. In this workshop, you'll learn how to use Python to clean, reshape, and transform data prior to analysis. Topics covered may include:

  • Editing strings with regular expressions
  • Converting data between wide and long formats
  • Dealing with null values
  • Grouping and aggregating data
  • Working with time series/datetime types
  • Encoding categorical values
  • Importing and exporting to and from common formats

It is helpful to have prior exposure to Python, such as through Introduction to Python Programming or Python Camp.

Please register here.

This workshop is part of the Program with Python series for for anyone who wants to get started or learn more about using the programming language Python. These tools can help you to collect, manipulate, clean, analyze, and visualize research data or automate many repetitive tasks. If you need personalized assistance with a data analysis, programming, or coding project, consider booking a consultation with one of our librarian-experts. Learn more about our services for programming and coding and for working with data.

All sessions are free to GW students, faculty, staff, and alumni. GW has an institutional commitment to ensuring that all of our programs and events are accessible for all individuals. If you require any accommodations to participate in this event, please contact at least 72 business hours (3 business days) prior to the event.

In-person attendance of this workshop is open to anyone whose GWorld allows them to tap into Gelman Library. If you do not have access to Gelman, please attend online.