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Working with spreadsheet-style data in Python with pandas and seaborn

By Madeleine Bonsma-Fisher

University of Toronto

This 4-hour participatory live-coding workshop takes learners through the basics of programming in Python via the Jupyter Lab interface and culminates with exploration and visualization of real-world bicycle count data from the City of Toronto.

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Additional materials available

Version 1.0 - published on 20 Dec 2018 doi:10.25334/Q4PF1D - cite this

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms

1200px-Bike_path_on_College_in_Toronto.jpeg output_263_1.png

Description

This workshop takes learners through the basics of programming in Python via the Jupyter Lab interface and culminates with exploration and visualization of real-world bicycle count data from the City of Toronto. The file 'lecture-notes-python-workshop.ipynb' can be opened and run with Jupyter notebook or Jupyter Lab, and the material is designed to be presented as a participatory live-coding workshop in which learners follow along as the instructor projects their code. The file 'lecture-notes-python-workshop.html' is a rendered version of the .ipynb notebook file that can be viewed in a browser.
This material focuses on using the package pandas for working with spreadsheet-type data and the packages matplotlib and seaborn for data visualization.


This material is based on workshops (https://uoftcoders.github.io/2018-07-12-utoronto/) hosted by UofT Coders (https://uoftcoders.github.io), inspired by the Data Carpentry Ecology Python lesson (https://datacarpentry.org/python-ecology-lesson/).

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