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.
Listed in Teaching Materials
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/).
- college_spadina_2010_2017.csv(CSV | 48 KB)
- faculty_notes.pdf(PDF | 135 KB)
- lecture-notes-python-workshop.html(HTML | 2 MB)
- lecture-notes-python-workshop.ipynb(IPYNB | 2 MB)
- college_spadina_excel_screenshot.jpg(JPG | 177 KB)
- jupyter-start-screen.jpg(JPG | 38 KB)
- split-apply-combine.png(PNG | 25 KB)
- License terms
Cite this work
Researchers should cite this work as follows:
- Bonsma-Fisher, M. (2018). Working with spreadsheet-style data in Python with pandas and seaborn. QUBES Educational Resources. doi:10.25334/Q4PF1D