Data Stories

The major assignments in this course are seven “Data Stories”, due respectively at the end of weeks 2, 4, 6, 8, 10, 12, and 14 (Sundays at midnight Eastern). Each assignment requires that you source and wrangle data, perform analysis, and build data visualizations that tell a story. The assignments are in the form of story requests.

I recommend composing each story as a reproducible quarto report or presentation, using either R or python for the visualizations, and submitting your qmd file along with a rendered PDF or HTML file. Stories should be submitted on Brightspace.

  1. Story 1: Infrastructure Investment and Jobs Act Funding Allocation — due Sunday, September 13
  2. Story 2: Can the FED Control Inflation and Maintain Full Employment? — due Sunday, September 27
  3. Story 3: Do Stricter Gun Laws Reduce Firearm Gun Deaths? — due Sunday, October 11
  4. Story 4: High Revenue Airbnbs in NYC — due Sunday, October 25
  5. Story 5: What Factors Determine Housing Prices in Ames, Iowa? — due Sunday, November 8
  6. Story 6: Customer Segmentation at Instacart — due Sunday, November 22
  7. Story 7: Telling a Data Story with Shiny — due Sunday, December 13

Sample Data Story

To see an example of what a finished data story looks like, see this sample: Electricity and Carbon Over Time (PDF) (quarto source).