CS-GY 6313: Information Visualization
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1.0.0
  • Introduction
  • Defining Information Visualization
  • Why Use Visualization?
  • Popular Visualization Sources and Tools
  • Why Use a Graphical Representation?
  • The Problem with Statistics
  • Why Use a Computer to Visualize Data?
  • Why Use Interaction?
  • Assessing the Quality of a Visualization
  • Data Abstraction
    • Types of Datasets
    • Types of Attributes
    • Attribute Semantics
    • Data Abstraction to Visualization
    • Data Profiling
  • Fundamental Graphs
    • Alternate Representations
    • Visualizing More Than 2 Attributes
    • Faceting
  • Data Transformation
  • Graphical Components and Mapping Strategies
    • Marks
    • Channels
    • Graphical Decoding
    • Evaluating the Quality of a Visual Encoding
    • Contextual Components
  • Color
    • Color Perception
    • Color Specification
    • Color Use
      • Quantitative Color Scales
      • Categorical Color Scales
      • Diverging Color Scales
      • Highlighting
    • Perceptual Issues with Color
  • Geo Visualization
    • When to Use Maps
    • Geo Visualization Techniques
      • Dot Maps
      • Heat Maps
      • Hexbin Maps
      • Choropleth Maps
      • Graduated Symbol Maps
      • Summary of Map Types
    • Issues with Maps
    • Visualizing Geo Data with Time
  • Visualizing Temporal Data
    • Time Structures
    • Visualization Methods
    • Increasing Visual Scalability
    • Beyond Using Position
  • Networks and Trees
    • Visualizing Network Data
      • Node-Link Diagrams
        • Clutter Reduction
      • Matrices
    • Visualizing Trees
      • Node-Link Diagrams
      • Special Kinds of Trees
      • Space-Partitioning and Containment
        • Sunburst and Icicle Plots
  • Interaction and Multiple Views
    • Single and Multiple View Methods
      • Single View Methods
      • Multiple (Linked) Views Methods
    • Common Scenarios
  • Exploring Data
  • Animation, Pacing and Exposition
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  • Stacked and Grouped Bar Charts
  • Stacked Bar Charts
  • Grouped Bar Charts
  • Line Charts and Stacked Area Charts
  • Line Charts
  • Stacked Area Charts

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  1. Fundamental Graphs

Visualizing More Than 2 Attributes

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Last updated 5 years ago

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Stacked and Grouped Bar Charts

Stacked Bar Charts

If we have two attributes, with x and y values respectively, we will have x bars, each with y stacked components.

This is particularly useful when we need to visualize proportions.

Grouped Bar Charts

If we have 2 attributes, with x and y values respectively, we will have x groups with y bars per group.

This is particularly useful when we want to compare every single value to another.

Line Charts and Stacked Area Charts

Line Charts

Say we have a line chart with the number of collisions plotted over a given time range.

To represent a 3rd attribute, say 'borough', we can use one of two line chart visualizations: a single line chart with one line per borough, or multiple line charts, one per borough. The former is useful if we need to compare the boroughs, since all the lines are on a single chart.

Stacked Area Charts

These are particularly useful if we need to compare the proportions of quantities and how they change with time.

However, it isn't effective if we need to read the values or compare the values over time. This is because, since the lines are stacked, their pattern depends on that of the one below them, thereby not denoting actual values.