This is a series of Jupyter Notebooks, originally developed by Research Computing Services Lead Data Scientist Colby Witherup Wood (GitHub: agithasnoname) for the Lunch Lessons workshop series. Designed for Python coders who have completed the Python Fundamentals workshop series or a similar beginning Python tutorial, these individual lessons cover the coding skills that answer the question, “What should I learn next?” These topics explore the shortcuts and tools that aren’t usually covered in Python intro level workshops, but that are regularly used by intermediate and advanced Python coders. Answer keys are included.
Each GitHub repo can be downloaded to open the notebooks on your own computer, or the notebooks can be opened in Google Colab and run on the cloud.
Links to notebooks will be posted here the morning before each Lunch Lesson. Links to recordings will be posted here in the afternoon after each Lunch Lesson; the password to view recordings will only be sent to registered participants by email.
October 11: Managing file paths with pathlib
Materials to work on your own computer
Link to work on the cloud
Link to recording
October 18: Opening files from URLs
Materials to work on your own computer
Link to work on the cloud
Link to recording
October 25: Level up your Pandas with df.query and df.eval
Materials to work on your own computer
Link to work on the cloud
Link to recording
November 1: Saving and using your custom functions
Materials to work on your own computer
Link to work on the cloud
Link to recording
November 8: Intro to creating your own object classes
Materials to work on your own computer
Link to work on the cloud
Link to recording
November 15: List comprehensions
Materials to work on your own computer
Link to work on the cloud
January 10: Colormaps
Workshop materials
Link to recording
January 17: NetworkX
Workshop Materials
Link to recording
January 31: Intro to Plotly
Workshop matierals and installation instructions
Link to recording
February 7: Intro to Shiny
Workshop matierals and installation instructions
Link to recording
February 14: Intro to Quarto
Workshop materials and installation instructions
Link to recording
February 28: Mesa for Agent Based Modeling
Workshop materials
Link to recording
March 6: Intro to Polars for large scale data analysis
Workshop materials
Link to recording
April 10: Bayesian Inference in STAN
Workshop materials
Link to recording
April 17: Creating Interactive Figures with Python + Bokeh
Workshop materials
Please note: For this workshop, it will be best to work on your local computer, instead of Google Colab. Please follow the installation instructions from the workshop materials (linked above).
Link to recording
April 24: Statistics in Python: Statsmodels
Workshop materials
Link to recording
May 1: Efficient looping with Itertools
Workshop materials
Link to recording
May 8: Intro to web scraping with Selenium
Workshop materials
Link to recording
May 15: Computing distance (or similarity) for different data types
Workshop materials
Link to recording
May 22: Parsing text with NLTK
Workshop materials
Link to recording
These notebooks will teach you to write more efficient code.
- List comprehensions and dictionary comprehensions
- Combining strings and variables with fstrings
- Saving and loading Python objects with pickle and json
These notebooks cover topics that you will encounter in other people's code.
- Recognizing and indexing NumPy arrays
- Lambda functions and when to use them
- How to use functions with *args and **kwargs
If you frequently work with text strings or Pandas DataFrames:
- Finding patterns in strings with built-in functions and the re package
- Selecting and filtering data with Pandas loc, iloc, at, and iat
There are two ways to access the materials:
- On your own computer: If you have the Anaconda distribution of Python 3, you should have all the packages needed for these notebooks. Click on the green Code button above and choose Download ZIP. On your computer, open up Anaconda Navigator and choose either Jupyter Lab or Jupyter Notebook. Navigate to the folder you downloaded and open up the notebook of choice.
- Online: Go to http://colab.research.google.com/. Choose GitHub from the orange menu. Search for NUITRCS/NextStepsInPython and select your notebook of choice.