In this notebook, we show how to produce simple graphics using the base R installation. We will eventually introduce more sophisticated graphics via thelattice,tidyverse and the ggplot2 library in other notebooks.

TUTORIAL OUTLINE

  1. Scatterplots (swiss, iris)
  2. Histograms and Bar Charts (swiss, iris)
  3. Bubble Charts (Canadian 2011 demographic data, Canadian CMA 2011 demographic data)

1. SCATTERPLOTS

On a scatter plot, the features you study depend on the scale of interest:

1.1 swiss dataset

We start with a built-in R dataset called swiss.

str(swiss) # structure of the swiss dataset
## 'data.frame':    47 obs. of  6 variables:
##  $ Fertility       : num  80.2 83.1 92.5 85.8 76.9 76.1 83.8 92.4 82.4 82.9 ...
##  $ Agriculture     : num  17 45.1 39.7 36.5 43.5 35.3 70.2 67.8 53.3 45.2 ...
##  $ Examination     : int  15 6 5 12 17 9 16 14 12 16 ...
##  $ Education       : int  12 9 5 7 15 7 7 8 7 13 ...
##  $ Catholic        : num  9.96 84.84 93.4 33.77 5.16 ...
##  $ Infant.Mortality: num  22.2 22.2 20.2 20.3 20.6 26.6 23.6 24.9 21 24.4 ...
pairs(swiss) # scatter plot matrix for the swiss dataset

Let’s focus on one specific pair: Fertility vs. Education

# raw plot
plot(swiss$Fertility, swiss$Education)