33
Summary
R for Visual Analytics
Preface
The Building Block
1
A Layered Grammar of Graphics: ggplot2 methods
2
Beyond ggplot2 Fundamentals
3
Programming Interactive Data Visualisation with R
4
Programming Animated Statistical Graphics with R
Not So Common Chart
5
Visualising Likert Scale Data with Divergining Stacked Bar Chart
6
Visual Correlation Analysis
7
R for Data Science: Tidyverse principles and methods
8
R for Data Science: Tidyverse principles and methods
Visual Analytics
9
Visualising Distribution
10
Visual Statistical Analysis
11
Visualising Uncertainty
12
Funnel Plots for Fair Comparisons
Visualising and Analysing Multivariate Data
13
Creating Ternary Plot with R
14
Heatmap for Visualising and Analysing Multivariate Data
15
Visual Multivariate Analysis with Parallel Coordinates Plot
16
Treemap Visualisation with R
Visualising and Analysing Time-series Data
17
Visualising and Analysing Time-oriented Data
18
R for Data Science: Tidyverse principles and methods
19
R for Data Science: Tidyverse principles and methods
20
Time on the Horizon: ggHoriPlot methods
Visualising and Analysing Geographical Data
21
Choropleth Mapping with R
22
Visualising Geospatial Point Data
23
Analytical Mapping
24
R for Data Science: Tidyverse principles and methods
Visualising and Analysing Spatio-temporal Data
25
R for Data Science: Tidyverse principles and methods
26
R for Data Science: Tidyverse principles and methods
Visualising and Analysing Network Data
27
Chapter 27: Modelling, Visualising and Analysing Network Data with R
28
R for Data Science: Tidyverse principles and methods
Visualising and Analysing Text Data
29
Visualising and Analysing Text Data with R: tidytext methods
30
R for Data Science: Tidyverse principles and methods
Information Dashboard Design with R
31
Information Dashboard Design: R methods
32
R for Data Science: Tidyverse principles and methods
33
Summary
References
33
Summary
32
R for Data Science: Tidyverse principles and methods
References