This course introduces common data visualization techniques and design principles using python with the seaborn, bokeh, plotly, and networkx packages. Students design and implement interactive, multivariate, text, hierarchical, network, and temporal data visualizations. Restriction: Restricted to Graduate level; Restricted to Analytics Majors

Assignment 3 - Time-Series Visualization - (50 points)



Due date: 4/9/2018 at 11:59pm

Objectives



  • Get practice with time-series visualization techniques
  • Familiarize yourself with interactive python visualization libraries
  • Gain practice with real-world data

For this assignment, you will implement the time-series visualization techniques with interaction using bokeh or plotly.

Explore the SF Monthly Property Crime Data using at least 4 of the following visualization techniques:

  • Line charts
  • Multi line charts
  • Bar charts
  • Stacked area charts
  • Stacked bar charts
  • Heatmap
  • Animated bubble charts
Note: The data is from the Data SF Portal and can be found here.

Extra credit



Any other interesting visualization technique (1 point per technique)

Submitting the assignment



  • For this assignment, submit all your python code along with the expected output (screenshots and a report with captions) or a python notebook.
  • Your report/notebook must contain your name, title of the assignment - "Time-Series Visualization using bokeh/plotly"
  • Submit a zip file that contains all the contents of the folder - report, python code, and screenshots or the python notebook on Canvas.