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Python and Jupyter Notebook Basics for Exploring Archival Collections Datasets

Python and Jupyter Notebook Basics for Exploring Archival Collections Datasets Online

This session is designed as a follow-up to the DSI workshops Intro to Python Parts 1&2, with support for learners interested in programming foundations and applications for digital health humanities research.

From 12-1pm we will open up for new learner questions and troubleshooting relating to getting started with Python programming.

Starting at 1pm, we will provide a walkthrough demonstration covering some basic approaches to characterizing the data included in a large archival collections datasets by reviewing, exploring, and analyzing metadata (structured data descriptions included in a dataset file). Initially characterizing what data is included in an archival collections dataset file will help you evaluate how useful it may be to your research and what kinds of research questions it may address based on such attributes as provenance, date ranges and subjects represented, and extent of available data.

Please feel free to join either or both halves of this session! This session will include opportunities throughout for questions and sharing insights and expertise.

Participants will find it helpful to have taken the two sequential DSI Intro to Python workshops, though can alternatively have reviewed materials related to that session independently and/or consulting introductory learning materials for those workshops on the CLE. 

Date:
Tuesday, Feb 7 2023
Time:
12:00pm - 2:00pm
Time Zone:
Pacific Time - US & Canada (change)
Campus:
Online
Online:
This is an online event. Event URL will be sent via registration email.
Categories:
  Archives and Special Collections     Data Science Initiative  

Registration is required. There are 15 seats available.

Event Organizer

Profile photo of Kathryn Stine
Kathryn Stine