Final project

Goal: Demonstrate that you know how to do data analysis in R

Can be done individually or in a pair.

Minimum requirements:

• 1 R Markdown file and 1 HTML file
• Use a dataset that we have not used in class
• “Introduction”, “Data analysis” and “Conclusion” sections
• At least 3 data visualizations, each of a different type (6 data visualizations with at least 3 different types if working with a teammate)
• Examples on the class website
• Due Nov 2 (Sat), 23:59:59

Project proposal

• 1-2 paragraphs long
• Details on the problem you wish to explore, datasets you will use, potential visualizations
• Due Oct 16 (Wed), 23:59:59

Recap of session 3

• Different types of plots
  • 1 categorical variable: barplot
  • 1 continuous variable: histogram
  • Continuous vs. continuous: scatterplot
  • Continuous vs. time: lineplot
  • Continuous vs. categorical: boxplots & violin plots
  • Categorical vs. categorical: heatmap
• Visualizing data with ggplot2
  • Key elements: data, geometries, aesthetics

3 essential elements of graphics: data, geometries, aesthetics

##     mpg weight cylinders
## 1  21.0  2.620         6
## 2  21.0  2.875         6
## 3  22.8  2.320         4
## 4  21.4  3.215         6
## 5  18.7  3.440         8
## 6  18.1  3.460         6
## 7  14.3  3.570         8
## 8  24.4  3.190         4
## 9  22.8  3.150         4
## 10 19.2  3.440         6

3 essential elements of graphics: data, geometries, aesthetics

3 essential elements of graphics: data, geometries, aesthetics

Examples of other aesthetics

Examples of other aesthetics

Agenda for today

• Layers
• Scales
• Facets
• Themes (“non-data ink”)

Layers: Combining multiple plots into one graphic

We can have more than one layer in a graphic.

= +

Each layer contains (essentially):

• 1 dataset, 1 geometric object, aesthetic mappings

ggplot2 code

ggplot() +
    geom_boxplot(data = df, mapping = aes(x = cylinders, y = mpg)) +
    geom_point(data = df, mapping = aes(x = cylinders, y = mpg), 
               position = "jitter")

ggplot2 code

When layers share attributes, we only have to type them once:

ggplot(data = df, mapping = aes(x = cylinders, y = mpg)) +
    geom_boxplot() +
    geom_point(position = "jitter")

ggplot2 code

• We can drop data = if it is the first argument of ggplot()
• We can drop mapping = if:
  • it is the second argument of ggplot()
  • it is the first argument of a geom_xx() function

ggplot(df, aes(x = cylinders, y = mpg)) +
    geom_boxplot() +
    geom_point(position = "jitter")

Scales

• Aesthetics only tell you which column corresponds with which aesthetic (e.g. cylinder -> color, mpg -> x)
• Does not tell you how to do the mapping
  • E.g. Which color should represent which cylinder value?
  • E.g. What should the range of the x-axis be?
• Scales define that for you
• (On the bright side, defaults usually ok)

Examples of scales (Source: A Layered Grammar of Graphics)

Scales example: colors

Scales example: x- & y-axes

Facets

• Plotting different parts of our data on different canvases
• Can give a clearer, less cluttered picture
• We can facet by rows and/or columns

Themes

Refers to all non-data ink

• Titles, axis ticks & labels, background color, legend, etc.
• Can manually set each item, or use preset themes

More pre-set themes

We’ve only scratched the surface!

R Graph Gallery: an excellent source of inspiration and code snippet examples

Today’s dataset: Diamonds

(Source: USA TODAY)

Optional material

Full specification of a graphic

One graphic contains:

• 1 or more layers
  • Each layer has 1 dataset, 1 geometric object, aesthetic mappings, 1 statistic (default usually ok), 1 position (default usually ok)
• 1 scale for each aesthetic mapping (defaults usually ok)
• 1 coordinate system (default usually ok)
• facet specification (if any)

Other grammatical elements: statistics

Behind the scenes, R may need to do some transformation on the dataset to make the graphic.

• Each geometry has a default statistic, usually good enough

Other grammatical elements: position

Sometimes we need to tweak the position of the geometric elements because they obscure each other.

• E.g. jitter: randomly shifting points slightly

Shapes in R

Colors in R

Color scales in R