In its original sense, in archeology, a glyph is a carved symbol.

Heiroglyph	Mayan glyph

A data glyph is also a mark, e.g.

The features of a data glyph encodes the value of variables.

• Some are very simple, e.g. a dot:
• Some combine different elements, e.g. a pointrange:
• Some are complicated, e.g. a dotplot:

See: http://docs.ggplot2.org/current/

Aesthetics are visual properties of a glyph.

• Aesthetics for points: location (x and y), shape, color, size, transparency

• Each glyph has its own set of aesthetics.

glyph : The basic graphical unit that represents one case. Other terms used include mark and symbol.

aesthetic : a visual property of a glyph such as position, size, shape, color, etc.

• may be mapped based on data values: sex -> color
• may be set to particular non-data related values: color is black

scale : A mapping that translates data values into aesthetics.

• example: male -> blue; female -> pink

frame : The position scale describing how data are mapped to x and y

guide : An indication for the human viewer of the scale. This allows the viewer to translate aesthetics back into data values.

• Examples: x- and y-axes, various sorts of legends

Glyph-ready data has this form:

• There is one row for each glyph to be drawn.
• The variables in that row are mapped to aesthetics of the glyph (including position)

##   sbp dbp    sex  smoker
## 1 129  75   male   never
## 2 105  62 female   never
## 3 122  72   male   never
## 4 128  83 female  former
## 5 123  90   male  former
## 6 122  77   male current

   sbp -> x      
   dbp -> y     
smoker -> color
   sex -> shape

1. Facets – using x and y twice
2. Layers – building up to complex graphics
3. Stats – data transformations

• x is determined by sbp and sex
• basically a separate frame for each sex

Each layer may have its own data, glyphs, aesthetic mapping, etc.

• one layer has points
• another layer has the curves

• What are the glyphs, aesthetics, etc. for this plot?
• How is the data for this plot related to the "raw" data?

##   sbp dbp    sex smoker
## 1 129  75   male  never
## 2 105  62 female  never
## 3 122  72   male  never
## 4 128  83 female former

1. Eye-training

   • recognize and describe glyphs, aesthetics, scales, etc.
   • identify data required for a plot

2. Data wrangling

   • get data into glyph-ready format (dplyr, tidyr)

3. Graphics construction

   • describe data, glyphs, aesthetics, etc. to R (lattice, ggplot2)

Map variables to aesthetics with mplot()