Skip to content
This repository has been archived by the owner on Dec 22, 2024. It is now read-only.

Latest commit

 

History

History
67 lines (45 loc) · 2.56 KB

README.md

File metadata and controls

67 lines (45 loc) · 2.56 KB
Raw

Dataviz With GPT

Learning Objectives

Students will be able to:

  • Use ChatGPT to build something in a programming language they're not familiar with (D3) #learning-how-to-learn

Pre-requisites

This lesson assumes you are familiar with:

  • Basic HTML, CSS and JavaScript
  • Using GitHub

Instructions

https://data.boston.gov/dataset/311-service-requests

Part 1: Build with GPT

Download data of all 311 calls in Boston from 2023

wget -O boston_311_2023.csv https://data.boston.gov/dataset/8048697b-ad64-4bfc-b090-ee00169f2323/resource/e6013a93-1321-4f2a-bf91-8d8a02f1e62f/download/tmpc0m94i5x.csv

Part 1: Making stuff

Use your knowledge of the vocabulary of HTML, CSS and JS to prompt ChatGPT. Your goal is to, with it's help, make a D3 visualization of all of the 311 calls in Boston from 2023.

  1. Make a bar chart of the top 10 reasons for 311 calls in the past year (hint: use the reason column in the data)
  2. The initial bar chart may not look quite right. With the help of ChatGPT, fix anything that looks immediately off (for example, sometimes the axis labels overlap or the bars are out of order etc...)
  3. Give the bar chart a good headline and subheadline
  4. Make the bar chart vertical instead of horizontal
  5. Change the default colors, text size, or anything else
  6. Add a citation for where the data comes from and give yourslves a chart authorship credit in the footnotes

Bonus: Go grab the raw csv, and create a bar chart that shows the top 10 departments subject by number of 311 calls and has a drop down menu for each name of the neighborhood

Part 2: Analyze what we built

<!-- Talk about SVGs -->
<!-- Select a part of the Body (remember CSS Selectors?) -->