R3: Graphics and Visualization
Graphics and Visualization
This is an overview of some of the standard methods available in R for visualization of data with statistical graphics. Examination of your data graphically is an important early step of any data analysis. In general, you should start off with univariate methods, histograms and such, examining each variable in isolation. Then look at pairs of variables with scatterplots, and work your way up to high-dimensional methods.
Only a small number of examples of each method will be provided. Remember that you can always use the help function to get more details and options on any of these functions.
1. Categorical Data
data(Titanic)
Titanic
, , Age = Child, Survived = No
Sex
Class Male Female
1st 0 0
2nd 0 0
3rd 35 17
Crew 0 0
, , Age = Adult, Survived = No
Sex
Class Male Female
1st 118 4
2nd 154 13
3rd 387 89
Crew 670 3
, , Age = Child, Survived = Yes
Sex
Class Male Female
1st 5 1
2nd 11 13
3rd 13 14
Crew 0 0
, , Age = Adult, Survived = Yes
Sex
Class Male Female
1st 57 140
2nd 14 80
3rd 75 76
Crew 192 20
ftable(Titanic)
Survived No Yes
Class Sex Age
1st Male Child 0 5
Adult 118 57
Female Child 0 1
Adult 4 140
2nd Male Child 0 11
Adult 154 14
Female Child 0 13
Adult 13 80
3rd Male Child 35 13
Adult 387 75
Female Child 17 14
Adult 89 76
Crew Male Child 0 0
Adult 670 192
Female Child 0 0
Adult 3 20
Titanic1 ................
................
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