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Visual Grammar

This section describes how visual attributes relate to the characteristics of the data.

Each chart plots a set of variables

Bar chart: (1-2 categorical, 1 continuous)

Axis: categorical
Bar Length: continuous (optional)
optional colour legend: categorial (fewer items)

Scatter plot: (2 continuous, 1-3 categorical)

x-axis: continuous
y-axis: continuous
Values: categorical marker:

Example: (stacked) bar chart

What are the categorical and continuous variables?

nhs_appointments_col_chart

col_config_panel

Example: Scatter plot

What are the categorical and continuous variables?

scatter_chart_cars

scatter_config_panel

Reading a chart: look at the anatomy

Scaffolding provides the scope and indicates the reason, purpose.

Chart title - purpose of the chart
Axes - what do they measure? are these labelled clearly? Choice of start and end points?
Sources of data: are they shown, trustworthy

Visual encoding translates quantities to marks and symbols

position , length, slope, angle ,colour (hue and shade),area
Less often used: shape, pattern, line thickness

Context (author,intended audience, location of report)

Grammar of Graphics

data geometries are the basic configuration of the chart e.g. line, column
aesthetics map visual attributes (x, y, colour, shape, fill, alpha) to dataset columns.
scales configure the axes and set ranges, limits on visual attributes
stats summarise the data before plotting, most obviously in box plots
facets - small multiple charts

Source: ggplot2 (ggplot2-book.org) Hadley Wickham