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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  1. Fundamental Graphs

Alternate Representations

It is an important skill to be able to determine if multiple visualizations can be created for the same data. This allows us to choose the most appropriate visualization for our data.

When we have multiple different representations, we can reason about graphical encoding and compare the pros and cons of alternate designs.

Some examples of alternate designs:

  • A dot plot is an alternate design for a bar chart. A line chart, on the other hand, is a poor alternate design for a bar chart because it may convey a pattern, or indicate that the discrete categories are ordered or continuous.

  • A slope chart is an alternate design for a scatter plot. Although not as effective as a scatter plot, it can be used to denote the direction in which the values are going.

  • Alternate designs for a line plot include bar charts, area charts and dot plots. A dot plot, however, is a very poor alternate design because trends that are clearly visible in line plots cannot be depicted by dot plots.

  • Matrix alternatives include stacked bar charts (this representation makes it difficult to denote quantities), or bar graphs with nested categories (this representation doesn't scale easily).

  • Alternate designs for symbol maps include bar charts.

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