> # Tables of counts
> 
> # First off, we can figure out the unique values in a set
> # We use the unique()
> colours <- c("red", "blue", "red", "red", "green", "blue")
> unique(colours)
[1] "red"   "blue"  "green"
> # These would also be the factor levels if we converted colours to a factor
> as.factor(colours)
[1] red   blue  red   red   green blue 
Levels: blue green red
> 
> # But what if we wanted to find out how many times each unique value appears in the set?
> # I.e., how many times does "red" appear in the colours vector?
> # R has a class that allows us to easily do so, and it's called 'table'
> # All we have to do, is feed our vector to table()
> t <- table(colours)
> t
colours
 blue green   red 
    2     1     3 
> class(t)
[1] "table"
> # We can also do this with numbers
> ages <- c(22,20,21,21,23,21)
> t2 <- table(ages)
> t2
ages
20 21 22 23 
 1  3  1  1 
> #
> # Table of joint counts
> # You can also make a table with two vectors and count how often each combination occurs
> shapes <- c("round", "round", "square", "round", "square", "round")
> colours <- c("red", "blue", "red", "red", "green", "blue")
> table(colours, shapes)
       shapes
colours round square
  blue      2      0
  green     0      1
  red       2      1
> # They are counted by considering the values at each index in the two vectors
> # You can also use a two-column data frame
> d <- data.frame(col=colours, shape=shapes)
> table(d)
       shape
col     round square
  blue      2      0
  green     0      1
  red       2      1
> colours <- c("red", "blue", "red", "red", "green", "blue", "red")
> table(colours, shapes)
Error in table(colours, shapes) : all arguments must have the same length
> 
> # Bar plots
> 
> # Something that we could use our table of counts for is to make a barplot
> # A barplot is a plot that shows the frequency of each unique value using different sized bars
> # Let's make a bar plot of our colours table 't'
> barplot(t)
> ages
[1] 22 20 21 21 23 21
Warning message:
In doTryCatch(return(expr), name, parentenv, handler) :
  invalid graphics state
> ages
[1] 22 20 21 21 23 21
> barplot(table(ages))
> # You can make a bar plot with a table joint counts
> barplot(table(colours, shapes))
> barplot(table(colours, shapes))
Error in table(colours, shapes) : all arguments must have the same length
> colours <- c("red", "blue", "red", "red", "green", "blue")
> barplot(table(colours, shapes))
> barplot(t)
> barplot(table(ages))
> help(barplot)
> barplot(t, names.arg = c("b", "g", "r"))
> source('~/Desktop/word_frequencies.R')
> 
> # There are many ways to change how your plot looks (colours, labels, etc.)
> # You can have a look at some R documentation online and start getting creative
> 
> # R built-in data: trees
> trees
   Girth Height Volume
1    8.3     70   10.3
2    8.6     65   10.3
3    8.8     63   10.2
4   10.5     72   16.4
5   10.7     81   18.8
6   10.8     83   19.7
7   11.0     66   15.6
8   11.0     75   18.2
9   11.1     80   22.6
10  11.2     75   19.9
11  11.3     79   24.2
12  11.4     76   21.0
13  11.4     76   21.4
14  11.7     69   21.3
15  12.0     75   19.1
16  12.9     74   22.2
17  12.9     85   33.8
18  13.3     86   27.4
19  13.7     71   25.7
20  13.8     64   24.9
21  14.0     78   34.5
22  14.2     80   31.7
23  14.5     74   36.3
24  16.0     72   38.3
25  16.3     77   42.6
26  17.3     81   55.4
27  17.5     82   55.7
28  17.9     80   58.3
29  18.0     80   51.5
30  18.0     80   51.0
31  20.6     87   77.0

> lm (trees$Volume ~ trees$Girth)

Call:
lm(formula = trees$Volume ~ trees$Girth)

Coefficients:
(Intercept)  trees$Girth  
    -36.943        5.066  

> m <- lm(trees$Volume ~ trees$Girth)
> abline(m)