Week 3 Lab: Fundamental Graphs and Visual Encoding

CS-GY 6313 - Information Visualization

Ryan Kim

New York University

2025-09-19

Week 3 Lab Overview

User Interface Graphics Library Notebook Zoom
observablehq.com Vega-Lite Week 3 Lab Notebook Zoom Meeting

Today’s Lab Activities

  1. Warm up: Practice with Scenarios & Choices
  2. Mutli-View Composition
  3. Partner Activity: Chart Exploration

Recall Today’s Main Topics:

  • 5 Fundamental Graphs: Bar Charts, Line Graphs, Scatter Plots, Matrix, Symbol Maps
  • Principles: Expressiveness & Effectiveness
  • Transformation Types: Aggregation, Filtering, Binning, Deriving, Normalization
  • Domains & Scales: Linear, Log, Ordinal

(Available via the Week 3 Lab Notebook)

Part 1: Warm Up - Thinking about Design Choices (~5-10 mins)

Our Task:

  • What we’re given: A data scenario & a goal in mind
  • Our task: Answer, collectively, the optimal way to:
    1. Identify the data domains [Q, C, O, T, Spatial (S)]
    2. Graph the data [Bar, Line, Scatter, Matrix, Symbol]

Exercise 1

  • What we’re given: Monthly sales revenue ($) over the past 12 months for a retail store.
  • Goal: Identify trends over time.
  • StrawPoll

(Source: dataamir)

Exercise 2

  • What we’re given: Population size of different countries.
  • Goal: Compare country population sizes
  • StrawPoll

(Source: Kaggle: Population by Country - 2020)

Exercise 3

  • What we’re given: Product ratings from 1 to 5 stars collected from customer feedback.
  • Goal: Show frequency of each rating.
  • StrawPoll

(Source: openbigdata.org)

Exercise 4

  • What we’re given: Test scores (0%-100%) of students plotted against hours studied.
  • Goal: Determine the correlation between study time and performance.
  • StrawPoll

Exercises - Answers

Exercise 1: Monthly Sale Revenues

  • Data domains: Monthly Sales (Q) over 12 months (T/O)
  • Graph: Line or Bar

Exercise 2: Population Sizes

  • Data domains: Population Size (Q) by Country (S)
  • Graph: Symbol Map (via GeoData)

Exercise 3: Product Ratings

  • Data domains: A collection (Q) of Product Ratings (O)
  • Graph: Bar Chart

Exercise 4: Test Scores

  • Data domains: Test scores (Q) vs. hours studied (Q)
  • Graph: Scatter Plot

Part 2: Facets and Multiple Views

Context:

In prior labs and exercises, we touched upon the idea of “facets”, or multiple views within a single chart. Facets allow us to divide visualizations based on a categorical feature as a 3rd dimension.

In this part, we’ll really get deep into generating multi-view compositions.


Concepts Covered:

  • layer: place compatible charts directly on top of each other,
  • facet: partition data into multiple charts, organized in rows or columns,
  • concatenate: position arbitrary charts within a shared layout, and
  • repeat: take a base chart specification and apply it to multiple data fields.

Largely inspired by UW Data Lab Summary: Multi-View Composition. Follow this notebook, then return here for Part 3.

Part 3: Multiple Chart Types in Vega-Lite

Documentation

We’ve already covered several plot types, but Vega-Lite provides a very wide variety of different chart types.


Changes to our Approach

  • Moving away from specifying “answer” graphs
  • Instead, moving more towards prompt-based questions and analysis.

Part 3 Exercises: Answering Prompts (~20-30 mins)

Your Task:

IN PAIRS OF TWO:

For each scenario prompt, take the data and attempt to generate a visualization of your choice that shows something unique about that dataset. At the end of this exercise, we will have volunteers show their graphs for each scenario and provide a narrative for what the graph is telling them.

  • You are allowed to use any visualization.
  • Feel free to use any filters, calculations, or multi-view compositions.
  • Use the cheatsheet to help you identify optimal graphs, scales, and transformations.
  • Try to avoid the common pitfalls.
  • Keep it simple!

End of Lab

  • Exercise #3 will be posted no later than September 20, 2025.
  • Exercise #3 is due on September 25th, 2025 @ 11:59pm!
  • Where do I ask questions?
    • TA Office Hours:
    • Our course Discord!