Data Visualization
1
Start
2
Understanding the Purposes of Data visualization
2.1
Explore versus Explain
2.2
Exploratory Data visualization
2.3
Explanatory Data visualization
2.4
Degrees of Separation
3
Design Basics
3.1
Gestalt Principles
3.2
Slow forms of visual perception
4
Data Basics
4.1
Variable Classes
4.2
Data Classes
4.3
Descriptive Statistics for Continuous Variables
4.3.1
Measurements for the location of a data set:
4.3.2
Measurements for spread:
4.4
Inferential statistics for the spread of a data set:
4.4.1
Summary of Types of Plots
4.4.2
Minimum Components of a Plot
4.4.3
Regression Lines
5
Using Design to Communicate
5.1
Small Multiples
5.2
Data-Ink Ratio
5.3
Aspect Ratio
5.4
Elements for Encoding Continuous Variables
5.5
Elements for Encoding Categorical Variables
5.6
The Case Against Pie Charts and Heat maps
5.6.1
Type 1: Different observations, same variables
5.6.2
Type 2: Same observations, Different variables
5.6.3
The Sankey Diagram
5.7
Pie chart best practices
6
Data and Design
6.1
Graphics have a Grammar
6.2
Case Study: The Iris Dataset
6.3
Case Study: Sugar Concentrations in Peppermint
7
Geometries of Univariate Distributions
7.1
Points: Strip Plots
7.2
Lines: Density Plots
7.3
Bars: Histograms
8
Geometries of Multivariate Comparisons
8.1
Points
8.1.1
Comparing Two Continuous Variables using Scatter Plots
8.2
The story of jittering
8.3
More points
8.4
geom_violin(), geom_density2d()
8.4.1
Density plots
8.5
Comparing a Continuous and a Categorical Variable using Dot Plots
8.6
Lines
8.6.1
Comparing Position in Multiple Variables using Parallel Plots
8.6.2
Time Series
8.7
An area plot:
8.8
Paths instead of lines
8.9
Multiple timelines
8.9.1
A nice example of small multiple with line plots
8.9.2
Comparing Distributions with Multiple Density Plots
8.9.3
time series with very different scales
8.10
Bars
8.10.1
Comparisons of Categorical Variable Sub-groups
8.10.2
Comparing Distributions with Multiple Histograms
8.11
Boxes
8.12
Area
8.12.1
Violin Plots
8.12.2
ridges
8.12.3
Showing parts-of-a-whole using Pie Charts and Stacked Bar Charts
8.12.4
Comparing two or more Categorical Variables using Mosaic Plots
8.12.5
Showing Distributions in Two Dimensions with a Smoothed Scatter Plot
8.13
Intersections between two or more variables
8.13.1
Venn and Euler Diagrams
8.13.2
Intersection plots:
8.14
Matrices
8.14.1
Multivariate Comparisons using Heat Maps
8.14.2
7b) Multivariate Comparisons using Scatter Plot Matrices
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Data Visualization
Data Visualization
Rick Scavetta
2019-05-01
1
Start