Class times and due dates

Reading quiz, live coding assignment, and lab assignment due dates:

Tuesday, February 6, 11:59pm

Our class live session for this module will be on Wednesday, January 31, 7:15-8:15pm:

Zoom link: https://virginia.zoom.us/j/91374174025?pwd=azRWK2dyem9hSVlTVDVuOHhkeGFuUT09

Office hours:

Jon's office hours: Thursdays, 7:15-9:15pm or by appointment

https://virginia.zoom.us/j/8014929228

(If I am not there, I'm just waiting for people to arrive. Send me a Teams message and I'll be right with you)
By appointment: email or Teams message me to set up a time to meet one-on-one

Textbook, Video Lectures, and Slides

Please read Chapter 3 of "Surfing the Data Pipeline with Python": https://jkropko.github.io/surfing-the-data-pipeline/ch3.html

The following video lectures follow the discussion in chapter 3 of "Surfing the Data Pipeline with Python", and use these slides:

module3slides.pdf

Lecture 3.1: What are JSON Files?

Lecture 3.2: Elements of JSON Files

Lecture 3.3: Loading and Flattening JSONs

External Readings and Reading Quiz

The readings for this module are

Blog: https://medium.com/analytics-vidhya/python-dictionary-and-json-a-comprehensive-guide-ceed58a3e2ed (if you can't access Medium posts, see the PDF link underneath these links)

Blog: https://stackabuse.com/reading-and-writing-json-to-a-file-in-python/

Official documentation: https://www.json.org/json-en.html

Medium article in PDF format

You may have these readings open as you take the following reading quiz:

Reading Quiz 3

Lab Assignment

You can find this module's lab assignment on Gradescope (don't forget the [instructions for submitting your assignments to Gradescope] ) :

Lab assignment on Gradescope

You can download the PDF version of the lab on Gradescope, but here is the .ipynb notebook file that you can use as a template to write your assignment:

labassignment3.ipynb

Live Coding Exercise

When you are ready, please submit your own Python notebook or script for this live coding exercise using the following link:

Live Coding Assignment: Module 3

Don't worry: JSON data isn't as scary as Jason (source: https://www.pinterest.com/pin/40673202872115688/)

In this live coding session we will access three different datasets which we can access on the internet without having to supply any API keys or other credentials (we'll cover APIs with credentials next week).

The goal is to examine the structure of the data, decide what is metadata and what constitutes the content of the dataframe we are trying to build, and to use the various tools available to us to convert the data to a pandas dataframe in our Python environment.

We'll work on the following three examples together:

Cocktail recipes from The Cocktail DB: http://www.thecocktaildb.com/api/json/v1/1/filter.php?c=Cocktail
Data on the pages on Wikipedia that pop up when searching for the term "Virginia": https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=Virginia&format=json&srlimit=500 (This search gets the first 500 hits, but there are 210391 results. If time, we will use the sroffset parameter described in the API documentation to get the full list)
Articles from NewsAPI.org. We will need to register for a free API key to be able to use this API. We'll talk about the best practices for storing API keys and keeping them secret during Module 4.