Week 3

Lecture 7: Introduction to data visualization (guest lecture)

Lecture 8: Data visualization continued (link to video lecture)

Lecture 9: Data visualization with seaborn (guest lecture)

NOTE: instructions for Lecture 7

At the link to Lecture 7 on this page, you can view the full data visualization tutorial from our guest lecturer with empty code blocks in places meant for in-class practice. The filled in version with answers is linked along with the other “code complete” lectures in the section below.

However, if you’re watching the lecture at home and wish to follow along, you should not download the notebook linked here. Instead, follow these instructions:

  • Visit the github repo for this lecture here.

  • On this page, click the green “Code” button at the top right and select “Download ZIP”.

  • Unzip this folder on your local computer.

  • Then, on your datahub homepage at datahub.ucsd.edu, upload the file called Walkthrough (without answers).ipynb

  • Next, on your datahub home page in the same directory where you just uploaded Walkthrough (without answers).ipynb, make two new folders: one called img and another called data.

  • In the img folder you just created on datahub, upload all the files in the folder called img in Sean’s github repo that you just downloaded.

  • In the data folder you just created on datahub, upload the file missing_work.csv that is in the data folder in Sean’s github repo that you just downloaded.

Doing the above will allow you to run the Walkthrough (without answers).ipynb file on your datahub with the same data and images in Sean’s original lecture. If you have questions about how to do any of this, feel free to reach out on campuswire!

Lecture 6 (4/8/22) Lecture 7 (guest) - Introduction to Data Visualization in Python