Lecture 7: Interactive Data Visualization

HKU STAT3622 Data Visualization by Dr. Aijun Zhang
12 October 2017


What's covered in this lecture?

  • D3.js Library
  • Plotly for R/ggplot2/Shiny
  • Other HTML widgets for R

Annoucement: DataViz Project (Call for Proposal)


Form a team and draft a proposal:

  1. Find one and only team member (team size = 2): Name/ID
  2. Choose a cool name for your name: e.g. Terminator, DataLover, …
  3. Draft a proposal:
    • find a topic or research question
    • describe the data source(s) and data background
    • plan for developing a DataViz app
    • plan to tell a good story behind data
  4. Submit to Jason (cc me) by Oct 25, 2017

Why Interactive Data Visualization?

  • iDataViz enables direct actions on a plot (e.g. mouse over, click, zoom, filter) to discover data information that may be otherwise hidden at the first sight.

  • In short, explore the details on demand.

  • It facilitates data-centered communcation and presentation.

  • It is often delivered in web graphics/html pages that are simple to view (by web browsers) and simple to share (by Email or URL).


PS: iDataViz also supports linking between multiple plots, i.e. connecting the elements selected in one plot with elements in another plot. This will be seperately discussed in next chapter on Shiny applications.

D3.js Library