Effective Data Visualization with R: Volume I – Base Graphics

Effective Data Visualization with R: Volume I - Base Graphics
Preface
    About the author
    Who is this book for
    How is this Book Structured
Dedication
1 Introduction to data visualization
    Chapter Objectives
    1.1 What is data visualization?
    1.2 The importance of data visualization
    1.3 Static versus interactive data visualization
    1.4 Exploratory versus Explanatory data visualization
    1.5 Chart types
        1.5.1 Chart types classified by purpose
        1.5.2 Chart types classified by the number and type of variables
    1.6 Chart attributes
    1.7 Plot elements
    1.8 R data visualization packages
2 Introduction to plotting with base graphics
    Chapter Objectives
    2.1 The plot() function
        2.1.1 Filtering data
    2.2 Shape
        2.2.1 Shapes by groups (categories)
    2.3 Size
        2.3.1 Size as a variable
    2.4 Colour
        2.4.1 Gray colours
        2.4.2 RGB
        2.4.3 HSV
        2.4.4 Converting between different colour models
        2.4.5 Colouring points by groups (categories)
        2.4.6 Colouring by a continuous variable
        2.4.7 Transparency
    2.5 Colour palettes
        2.5.1 R’s default colour palette
        2.5.2 The grDevices colour palettes
        2.5.3 RcolorBrewer
        2.5.4 The colorspace palette
        2.5.5 Wes Anderson colour palettes
    2.6 Plot type
    2.7 Line width and style
        2.7.1 Line width
        2.7.2 Line style
        2.7.3 Line end style
    2.8 Controlling axes ranges (zooming)
    2.9 Applying log transformation
    2.10 Saving plots to variables names
    2.11 Summary
3 Plot elements
    Chapter Objectives
    3.1 Title, labels, and text
        3.1.1 Adding a title and axis labels
        3.1.2 Remove title and axis labels
        3.1.3 Adding titles and axis labels using title()
        3.1.4 Customizing title and labels
        3.1.5 Adding a title and axis labels using mtext()
        3.1.6 Adding data labels and comments
    3.2 Controlling axes and tick marks
        3.2.1 Removing borders
        3.2.2 Removing axes
        3.2.3 Adding axes
        3.2.4 Customizing axis
    3.3 Controlling plot elements using par
        3.3.1 Get default setting
        3.3.2 Controlling size
        3.3.3 Restoring default settings
        3.3.4 Controlling colours
        3.3.5 Controlling font style
        3.3.6 Font family
        3.3.7 Controlling line style and width
        3.3.8 Controlling box styles
        3.3.9 Controlling background and foreground colours
        3.3.10 Controlling plot margins
        3.3.11 Axis interval
        3.3.12 Tick marks length
        3.3.13 Controlling margin line
    3.4 Subplots (multiple plots on the same sheet)
        3.4.1 Subplots with mfcol and mfrow
        3.4.2 Subplots with layout()
    3.5 Clipping region
    3.6 Adding a legend
        3.6.1 Legend position
        3.6.2 Legend orientation
        3.6.3 Legend title
        3.6.4 Legend text
        3.6.5 Legend shapes (boxes, lines, and points)
        3.6.6 Legend body
    3.7 Gridlines
    3.8 Background and borders
        3.8.1 Panel colour
        3.8.2 Adding a box around the plot
    3.9 Saving plot to computer
        3.9.1 Saving plot using code
        3.9.2 Saving plot using RStudio
4 One discrete variable charts
    Chapter Objectives
    4.1 Bar chart
        4.1.1 Bar width and space
        4.1.2 Borders and colours
        4.1.3 Shading lines
        4.1.4 Column chart
        4.1.5 Adding data labels
        4.1.6 Adding error bars
    4.2 Pie chart
        4.2.1 Controlling size
        4.2.2 Controlling direction
        4.2.3 Adding a legend
    4.3 3D pie chart
        4.3.1 Adding labels
        4.3.2 Exploding the pie chart
        4.3.3 Height
        4.3.4 Margins
    4.4 Treemap
        4.4.1 Colouring by a variable
        4.4.2 Plotting hierarchical data
5 One continuous variable charts
    Chapter Objectives
    5.1 Histogram
        5.1.1 Bin size and number of breaks
        5.1.2 Colour, border, and shading lines
        5.1.3 Multiple histograms
        5.1.4 Comparing two series
        5.1.5 Converting to probability densities
    5.2 Density plot
        5.2.1 Multiple lines
        5.2.2 Controlling smoothness
        5.2.3 Kernel
        5.2.4 Filling the area under the curve
        5.2.5 Combining histogram and density plot
        5.2.6 Adding rug
    5.3 Q-Q plot
    5.4 Stem-and-leaf plot
6 Two discrete variables charts
    Chapter Objectives
    6.1 Mosaic plot
        6.1.1 Colour and border
        6.1.2 Controlling space
        6.1.3 Horizontal mosaic plot
    6.2 Spine plot
        6.2.1 Colour and border
        6.2.2 Controlling space
        6.2.3 Adding a legend
    6.3 Association plot
        6.3.1 Spacing
7 One discrete and one continuous variable charts
    Chapter Objectives
    7.1 Stacked bar chart
        7.1.1 Adding data labels
        7.1.2 Adding a legend
        7.1.3 Stacked column chart
        7.1.4 100% stacked bar chart
        7.1.5 100% stacked column chart
    7.2 Clustered Bar Chart
        7.2.1 Adding space between bars
        7.2.2 Adding vertical lines
        7.2.3 Adding data labels
    7.3 Dot Plot
        7.3.1 Adding labels
        7.3.2 Adding groups
        7.3.3 Adding group values
        7.3.4 Shapes
        7.3.5 Dot sizes
        7.3.6 Colour
    7.4 Spinogram
        7.4.1 Breaks
        7.4.2 Reordering levels
    7.5 Conditional Density Plots
    7.6 Boxplot
        7.6.1 Box width
        7.6.2 Adding notch
        7.6.3 Horizontal boxplot
        7.6.4 Removing outliers
        7.6.5 Log transformation
        7.6.6 Grouped boxplot
        7.6.7 Using two continuous variables
        7.6.8 Grouping by two or more discrete variables
        7.6.9 Plotting two or more continuous variables
        7.6.10 Customizing boxplot
        7.6.11 Box width
        7.6.12 Boxplot annotated with the number of observations
    7.7 Strip plot
        7.7.1 Adding jitter
        7.7.2 Vertical strip plot
        7.7.3 Grouped strip plot
        7.7.4 Using two continuous variables
        7.7.5 Grouping by two or more discrete variables
        7.7.6 Plotting two or more continuous variables
        7.7.7 Combining boxplot and strip plot
    7.8 Violin plot
        7.8.1 Horizontal
        7.8.2 Customizing
        7.8.3 Combining violin and strip plot
8 Two continuous variables charts
    Chapter Objectives
    8.1 Scatter plot
        8.1.1 Adding jitter
        8.1.2 Adding rug
        8.1.3 Adding lines
        Adding a linear regression line
        Adding smooth
    8.2 Grouped or clustered scatter plot
        8.2.1 Using points()
        8.2.2 Adding data labels
    8.3 Using scatterplot() from the package car
        8.3.1 3D scatterplot
        8.3.2 Adding horizontal lines
    8.4 Smooth scatter plot
        8.4.1 Bin size
        8.4.2 Colouring
        8.4.3 Points
    8.5 Combining scatter plot and other chart types
        8.5.1 Scatter plot and violin plot
        8.5.2 Combining scatter plot and histograms
    8.6 Bubble plot
        8.6.1 Controlling bubble size
    8.7 Line and lollipop charts
    8.8 Line chart by groups
        8.8.1 Long data
        8.8.2 Wide data
        8.8.3 Margin labels
9 Three variables charts
    Chapter Objectives
    9.1 Heat map
        9.1.1 Normalization across columns or rows
        9.1.2 Suppressing row and column dendrogram
        9.1.3 Changing colours
        9.1.4 Heat map for the English premier league (EPL) 2018/2019
        9.1.5 Using the function image() to create a heat map
        9.1.6 Using the function heatmap.2() from the gplots package
        9.1.7 Using the function pheatmap() from the pheatmap package
    9.2 Contour plot
        9.2.1 Contour levels
        9.2.2 Adding and removing data labels
        9.2.3 Filled contour plots
        9.2.4 Using the function image()
        9.2.5 Combining a line and filled contour plot
10 More than Three variables charts
    Chapter Objectives
    10.1 Scatter plot matrix
        10.1.1 panel function
        10.1.2 Using scatterplotMatrix() from car
        10.1.3 Using corrgram() from corrgram
    10.2 Parallel plot
        10.2.1 Highlighting a particular group
    10.3 Conditional Plots
        10.3.1 Conditioning on categorical variables
        10.3.2 Conditioning on continuous variables
        10.3.3 Conditioning on continuous and categorical variables
        10.3.4 Customizing the plot
        10.3.5 panel function
    10.4 Radar chart (spider plot)
        10.4.1 Changing labels
        10.4.2 Axis type
        10.4.3 Colours
        10.4.4 Adding polygons
        10.4.5 Controlling lines
        10.4.6 Shading lines
11 Base maps with maps
    Chapter Objectives
    11.1 The map() function
    11.2 The mapdata package
    11.3 Plotting regions
    11.4 Customising maps
        11.4.1 Map projection
        11.4.2 Controlling fill, interior and boundary lines
        11.4.3 Gridlines
        11.4.4 Zooming with xlim and ylim
        11.4.5 Adding axes
        11.4.6 City names
        11.4.7 Combining maps
        11.4.8 Adding points and text
        11.4.9 Adding lines
        11.4.10 Highlighting portions of a map
12 Qualitative Maps
    12.1 Dot maps
        12.1.1 Plotting dots
        12.1.2 Adding base map
        12.1.3 Zooming
        12.1.4 Adding text
    12.2 Radial flow maps
        12.2.1 Adding lines with the function segments()
        12.2.2 Adding lines with the function arrows()
    12.3 Categorical map
13 Quantitative maps
    Chapter Objectives
    13.1 Bubble (proportional symbols) map
        13.1.1 Data transformation
    13.2 Network flow maps
    13.3 Choropleth maps
        13.3.1 Using the function classIntervals()
        13.3.2 Using the function findColours()