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Notes on Graphics Functions
It is important to understand the distinction between high-level and low-level graphics functions. //A high-level// graphics function //starts a new graph//. It initializes the graphics window (creating it if necessary); sets the scale; maybe draws some adornments, such as a title and labels; and renders the graphic. Examples include:

plot
  * Generic plotting function
boxplot
  * Create a box plot
hist
  * Create a histogram
qqnorm
  * Create a quantile-quantile (Q-Q) plot
curve
  * Graph a function

A low-level graphics function cannot start a new graph. Rather, it //adds something to an existing graph//: points, lines, text, adornments, and so forth. Examples include:

points
  * Add points
lines
  * Add lines
abline
  * Add a straight line
segments
  * Add line segments
polygon
  * Add a closed polygon
text
  * Add text

You must call a high-level graphics routine before calling a low-level graphics routine. The low-level routine needs to have the graph initialized; otherwise, you get an error like this:

<code>> abline(a=0, b=1)
Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : 
  plot.new has not been called yet</code>

plot(x) produces **different results depending on whether x is** a vector, a factor, a data frame, a linear regression model, a table, or whatever.
  
====== Creating a Scatter Plot ======
Scatter Plot (number by number data)
<code>> cars
   speed dist
1      4    2
2      4   10
3      7    4
4      7   22
5      8   16
6      9   10
7     10   18
8     10   26
9     10   34
10    11   17
11    11   28
12    12   14
13    12   20
14    12   24
15    12   28
16    13   26
17    13   34
18    13   34
19    13   46
20    14   26
21    14   36
22    14   60
23    14   80
24    15   20
25    15   26
26    15   54
27    16   32
28    16   40
29    17   32
30    17   40
31    17   50
32    18   42
33    18   56
34    18   76
35    18   84
36    19   36
37    19   46
38    19   68
39    20   32
40    20   48
41    20   52
42    20   56
43    20   64
44    22   66
45    23   54
46    24   70
47    24   92
48    24   93
49    24  120
50    25   85
> 
</code>
The same thig . . .
<code>> plot(cars)
> plot(cars$speed, cars$dist)
</code>

{{:r:scatterplot01.png?600}}

====== Adding a Title and Labels ======
When calling plot:
  * Use the **main** argument for a title.
  * Use the **xlab** argument for an x-axis label.
  * Use the **ylab** argument for a y-axis label.
<code>> plot(x, main="The Title", xlab="X-axis Label", ylab="Y-axis Label")
</code>

<code>plot(cars,
            main="cars: Speed vs. Stopping Distance (1920)",
            xlab="Speed (MPH)",
            ylab="Stopping Distance (ft)")
</code>

====== Adding a Grid ======

  * Call plot with type="n" to initialize the graphics frame without displaying the data.
  * Call the grid function to draw the grid.
  * Call low-level graphics functions, such as points and lines, to draw the graphics overlaid on the grid.
<code>> plot(x, y, type="n")
> grid()
> points(x, y)
</code>

<code>plot(cars,
            main="cars: Speed vs. Stopping Distance (1920)",
            xlab="Speed (MPH)",
            ylab="Stopping Distance (ft)", type="n")
</code>
<code>grid()
points(cars)
</code>
{{:r:scatterplot02.png?600}}

====== Creating a Scatter Plot of Multiple Groups ======

<code>with(iris, plot(Petal.Length, Petal.Width))

with(iris, plot(Petal.Length, Petal.Width, pch=as.integer(Species)))
</code>


====== Adding a Legend ======
Here is how you create legends for points, lines, and colors:
Legend for points
  * <code>legend(x, y, labels, pch=c(pointtype1, pointtype2, ...))</code>
Legend for lines according to line type
  * <code>legend(x, y, labels, lty=c(linetype1, linetype2, ...))</code>
Legend for lines according to line width
  * <code>legend(x, y, labels, lwd=c(width1, width2, ...))</code>
Legend for colors
  * <code>legend(x, y, labels, col=c(color1, color2, ...))</code>

  - x and y are the coordinates of the legend box.
  - labels is a vector of the character strings to appear in the legend.
  - The pch, lty, lwd, and col arguments are vectors that parallel the labels.

<code>> legend(1.5, 2.4, c("setosa","versicolor","virginica"), pch=1:3)</code>
<code>> legend(1, 2.5, c("setosa","versicolor","virginica"), pch=1:3, col="red")</code>


<code>> f <- factor(iris$Species)
> with(iris, plot(Petal.Length, Petal.Width, pch=as.integer(f)))
> legend(1.5, 2.4, as.character(levels(f)), 
     pch=1:length(levels(f)), 
     col=c("red","blue","green"))
</code>


====== Plotting the Regression Line of a Scatter Plot ======

<code>> install.packages("faraway")
> library(faraway)
> 

> data(strongx)
> strongx
   momentum energy crossx sd
1         4  0.345    367 17
2         6  0.287    311  9
3         8  0.251    295  9
4        10  0.225    268  7
5        12  0.207    253  7
6        15  0.186    239  6
7        20  0.161    220  6
8        30  0.132    213  6
9        75  0.084    193  5
10      150  0.060    192  5

> m <- lm(crossx ~ energy, data=strongx) # get linear regression model 
> plot(crossx ~ energy, data=strongx)
> abline(m)

</code>

===== e.g. 1 =====
<code># Creating a Graph
attach(mtcars)
plot(wt, mpg) 
abline(lm(mpg~wt))
title("Regression of MPG on Weight")</code>
{{:R:regression_line.png}}

===== e.g. 2 =====

<code>?LifeCycleSavings
lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)

> summary(lm.SR)

Call:
lm(formula = sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)

Residuals:
    Min      1Q  Median      3Q     Max 
-8.2422 -2.6857 -0.2488  2.4280  9.7509 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) 28.5660865  7.3545161   3.884 0.000334 ***
pop15       -0.4611931  0.1446422  -3.189 0.002603 ** 
pop75       -1.6914977  1.0835989  -1.561 0.125530    
dpi         -0.0003369  0.0009311  -0.362 0.719173    
ddpi         0.4096949  0.1961971   2.088 0.042471 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.803 on 45 degrees of freedom
Multiple R-squared:  0.3385,	Adjusted R-squared:  0.2797 
F-statistic: 5.756 on 4 and 45 DF,  p-value: 0.0007904

> plot(LifeCycleSavings)
> plot(lm.SR)
</code>

{{:r:LifeCycleSavings.jpeg}}
{{:R:regression_model.png}}

====== Plotting All Variables Against All Other Variables ======
<code>> head(iris)
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa
</code>

<code>plot(iris[,1:4])</code>
{{:R:plot_all_variables.png}}
====== Creating One Scatter Plot for Each Factor Level ======

<code>data(Cars93, package="MASS")
coplot(Horsepower ~ MPG.city | Origin, data=Cars93)</code>
{{:R:scatterplot_each_factor.png}}
====== Creating a Bar Chart ======
<code>> airquality
    Ozone Solar.R Wind Temp Month Day
1      41     190  7.4   67     5   1
2      36     118  8.0   72     5   2
3      12     149 12.6   74     5   3
4      18     313 11.5   62     5   4
5      NA      NA 14.3   56     5   5
6      28      NA 14.9   66     5   6
7      23     299  8.6   65     5   7
8      19      99 13.8   59     5   8
9       8      19 20.1   61     5   9
10     NA     194  8.6   69     5  10
11      7      NA  6.9   74     5  11
12     16     256  9.7   69     5  12
13     11     290  9.2   66     5  13
14     14     274 10.9   68     5  14
15     18      65 13.2   58     5  15
16     14     334 11.5   64     5  16
17     34     307 12.0   66     5  17
18      6      78 18.4   57     5  18
19     30     322 11.5   68     5  19
20     11      44  9.7   62     5  20
21      1       8  9.7   59     5  21
22     11     320 16.6   73     5  22
23      4      25  9.7   61     5  23
24     32      92 12.0   61     5  24
25     NA      66 16.6   57     5  25
26     NA     266 14.9   58     5  26
27     NA      NA  8.0   57     5  27
28     23      13 12.0   67     5  28
29     45     252 14.9   81     5  29
30    115     223  5.7   79     5  30
31     37     279  7.4   76     5  31
32     NA     286  8.6   78     6   1
33     NA     287  9.7   74     6   2
34     NA     242 16.1   67     6   3
35     NA     186  9.2   84     6   4
36     NA     220  8.6   85     6   5
37     NA     264 14.3   79     6   6
38     29     127  9.7   82     6   7
39     NA     273  6.9   87     6   8
40     71     291 13.8   90     6   9
41     39     323 11.5   87     6  10
42     NA     259 10.9   93     6  11
43     NA     250  9.2   92     6  12
44     23     148  8.0   82     6  13
45     NA     332 13.8   80     6  14
46     NA     322 11.5   79     6  15
47     21     191 14.9   77     6  16
48     37     284 20.7   72     6  17
49     20      37  9.2   65     6  18
50     12     120 11.5   73     6  19
51     13     137 10.3   76     6  20
52     NA     150  6.3   77     6  21
53     NA      59  1.7   76     6  22
54     NA      91  4.6   76     6  23
55     NA     250  6.3   76     6  24
56     NA     135  8.0   75     6  25
57     NA     127  8.0   78     6  26
58     NA      47 10.3   73     6  27
59     NA      98 11.5   80     6  28
60     NA      31 14.9   77     6  29
61     NA     138  8.0   83     6  30
62    135     269  4.1   84     7   1
63     49     248  9.2   85     7   2
64     32     236  9.2   81     7   3
65     NA     101 10.9   84     7   4
66     64     175  4.6   83     7   5
67     40     314 10.9   83     7   6
68     77     276  5.1   88     7   7
69     97     267  6.3   92     7   8
70     97     272  5.7   92     7   9
71     85     175  7.4   89     7  10
72     NA     139  8.6   82     7  11
73     10     264 14.3   73     7  12
74     27     175 14.9   81     7  13
75     NA     291 14.9   91     7  14
76      7      48 14.3   80     7  15
77     48     260  6.9   81     7  16
78     35     274 10.3   82     7  17
79     61     285  6.3   84     7  18
80     79     187  5.1   87     7  19
81     63     220 11.5   85     7  20
82     16       7  6.9   74     7  21
83     NA     258  9.7   81     7  22
84     NA     295 11.5   82     7  23
85     80     294  8.6   86     7  24
86    108     223  8.0   85     7  25
87     20      81  8.6   82     7  26
88     52      82 12.0   86     7  27
89     82     213  7.4   88     7  28
90     50     275  7.4   86     7  29
91     64     253  7.4   83     7  30
92     59     254  9.2   81     7  31
93     39      83  6.9   81     8   1
94      9      24 13.8   81     8   2
95     16      77  7.4   82     8   3
96     78      NA  6.9   86     8   4
97     35      NA  7.4   85     8   5
98     66      NA  4.6   87     8   6
99    122     255  4.0   89     8   7
100    89     229 10.3   90     8   8
101   110     207  8.0   90     8   9
102    NA     222  8.6   92     8  10
103    NA     137 11.5   86     8  11
104    44     192 11.5   86     8  12
105    28     273 11.5   82     8  13
106    65     157  9.7   80     8  14
107    NA      64 11.5   79     8  15
108    22      71 10.3   77     8  16
109    59      51  6.3   79     8  17
110    23     115  7.4   76     8  18
111    31     244 10.9   78     8  19
112    44     190 10.3   78     8  20
113    21     259 15.5   77     8  21
114     9      36 14.3   72     8  22
115    NA     255 12.6   75     8  23
116    45     212  9.7   79     8  24
117   168     238  3.4   81     8  25
118    73     215  8.0   86     8  26
119    NA     153  5.7   88     8  27
120    76     203  9.7   97     8  28
121   118     225  2.3   94     8  29
122    84     237  6.3   96     8  30
123    85     188  6.3   94     8  31
124    96     167  6.9   91     9   1
125    78     197  5.1   92     9   2
126    73     183  2.8   93     9   3
127    91     189  4.6   93     9   4
128    47      95  7.4   87     9   5
129    32      92 15.5   84     9   6
130    20     252 10.9   80     9   7
131    23     220 10.3   78     9   8
132    21     230 10.9   75     9   9
133    24     259  9.7   73     9  10
134    44     236 14.9   81     9  11
135    21     259 15.5   76     9  12
136    28     238  6.3   77     9  13
137     9      24 10.9   71     9  14
138    13     112 11.5   71     9  15
139    46     237  6.9   78     9  16
140    18     224 13.8   67     9  17
141    13      27 10.3   76     9  18
142    24     238 10.3   68     9  19
143    16     201  8.0   82     9  20
144    13     238 12.6   64     9  21
145    23      14  9.2   71     9  22
146    36     139 10.3   81     9  23
147     7      49 10.3   69     9  24
148    14      20 16.6   63     9  25
149    30     193  6.9   70     9  26
150    NA     145 13.2   77     9  27
151    14     191 14.3   75     9  28
152    18     131  8.0   76     9  29
153    20     223 11.5   68     9  30
></code> 

<code>> heights <- tapply(airquality$Temp, airquality$Month, mean)</code>
<code>> barplot(heights)</code>
{{:R:barplot_heights.png}}

<code>> barplot(heights,
+         main="Mean Temp. by Month",
+         names.arg=c("May", "Jun", "Jul", "Aug", "Sep"),
+         ylab="Temp (deg. F)")</code>
{{:R:barplot_heights.2.png}}

====== Adding Confidence Intervals to a Bar Chart ======

<code>attach(airquality)
heights <- tapply(Temp, Month, mean)

install.packages("gplots")  # for barplot2 function
library(gplots) # load barplot2 function
</code>

<code>tmean <- tapply(Temp, list(as.factor(Month)), mean)  
# mean for each month
tsd <- tapply(Temp, list(as.factor(Month)),sd)  
# sd for each month
tse <- tsd/sqrt(length(Temp))  
# se for each month

lower <- tmean - 1.96*tse
upper <- tmean + 1.96*tse
barplot2(heights, plot.ci=TRUE, ci.l=lower, ci.u=upper)

barplot2(heights, plot.ci=TRUE, ci.l=lower, ci.u=upper,
          ylim=c(50,90), xpd=FALSE,
          main="Mean Temp. By Month",
          names.arg=c("May","Jun","Jul","Aug","Sep"),
          ylab="Temp (deg. F)")

</code>

====== Coloring a Bar Chart ======
<code>barplot(c(3,5,4), col=c("red","white","blue"))</code>

<code>rel.hts <- rank(heights) / length(heights)
grays <- gray(1 - rel.hts)
barplot(heights, col=grays)</code>

<code>rel.hts <- (heights - min(heights)) / (max(heights) - min(heights))
grays <- gray(1 - rel.hts)
barplot(heights,
        col=grays,
        ylim=c(50,90), xpd=FALSE,
        main="Mean Temp. By Month",
        names.arg=c("May", "Jun", "Jul", "Aug", "Sep"),
        ylab="Temp (deg. F)")
</code>

====== Plotting a Line from x and y Points ======
<code>plot(pressure)
plot(pressure, type="l")</code>
{{:R:barplot_points_line.png}}

<code>> par(mfrow=c(2, 2), cex=0.6, mar=c(4, 4, 1, 1))
> y <- rnorm(20)
> plot(y, type="p")
> plot(y, type="l")
> plot(y, type="b")
> plot(y, type="h")
></code> 
{{:r:plot_types.png}}
====== Plotting Multiple Datasets ======
<code>x <- rnorm(10,sd=5,mean=20)
y <- 2.5*x - 1.0 + rnorm(10,sd=9,mean=0)
cor(x,y)
[1] 0.7400576
plot(x,y,xlab="Independent",ylab="Dependent",main="Random Stuff")
x1 <- runif(8,15,25)
y1 <- 2.5*x1 - 1.0 + runif(8,-6,6)
points(x1,y1,col=2)
</code>

{{:R:plotting_multiple_datasets.png}}


====== Adding Vertical or Horizontal Lines ======
<code>> abline(v=0)          # Vertical line at x = 0
> abline(h=0)          # Horizontal line at y = 0</code>


====== Creating a Box Plot ======
boxplot(x), where x is a vector of numeric values.

<code>boxplot(Cars93$MPG.city)</code>

====== Creating One Box Plot for Each Factor Level ======
<code>boxplot(Cars93$MPG.city~Cars93$Origin)</code>
{{:R:boxplot.png}}
<code>> library(MASS)
> UScereal
                                      mfr  calories    protein
100% Bran                               N 212.12121 12.1212121
All-Bran                                K 212.12121 12.1212121
All-Bran with Extra Fiber               K 100.00000  8.0000000
Apple Cinnamon Cheerios                 G 146.66667  2.6666667
Apple Jacks                             K 110.00000  2.0000000
Basic 4                                 G 173.33333  4.0000000
Bran Chex                               R 134.32836  2.9850746
Bran Flakes                             P 134.32836  4.4776119
Cap'n'Crunch                            Q 160.00000  1.3333333
Cheerios                                G  88.00000  4.8000000
Cinnamon Toast Crunch                   G 160.00000  1.3333333
Clusters                                G 220.00000  6.0000000
Cocoa Puffs                             G 110.00000  1.0000000
Corn Chex                               R 110.00000  2.0000000
Corn Flakes                             K 100.00000  2.0000000
Corn Pops                               K 110.00000  1.0000000
Count Chocula                           G 110.00000  1.0000000
Cracklin' Oat Bran                      K 220.00000  6.0000000
Crispix                                 K 110.00000  2.0000000
Crispy Wheat & Raisins                  G 133.33333  2.6666667
Double Chex                             R 133.33333  2.6666667
Froot Loops                             K 110.00000  2.0000000
Frosted Flakes                          K 146.66667  1.3333333
Frosted Mini-Wheats                     K 125.00000  3.7500000
Fruit & Fibre: Dates Walnuts and Oats   P 179.10448  4.4776119
Fruitful Bran                           K 179.10448  4.4776119
Fruity Pebbles                          P 146.66667  1.3333333
Golden Crisp                            P 113.63636  2.2727273
Golden Grahams                          G 146.66667  1.3333333
Grape Nuts Flakes                       P 113.63636  3.4090909
Grape-Nuts                              P 440.00000 12.0000000
Great Grains Pecan                      P 363.63636  9.0909091
Honey Graham Ohs                        Q 120.00000  1.0000000
Honey Nut Cheerios                      G 146.66667  4.0000000
Honey-comb                              P  82.70677  0.7518797
Just Right Fruit & Nut                  K 186.66667  4.0000000
Kix                                     G  73.33333  1.3333333
Life                                    Q 149.25373  5.9701493
Lucky Charms                            G 110.00000  2.0000000
Mueslix Crispy Blend                    K 238.80597  4.4776119
Multi-Grain Cheerios                    G 100.00000  2.0000000
Nut&Honey Crunch                        K 179.10448  2.9850746
Nutri-Grain Almond-Raisin               K 208.95522  4.4776119
Oatmeal Raisin Crisp                    G 260.00000  6.0000000
Post Nat. Raisin Bran                   P 179.10448  4.4776119
Product 19                              K 100.00000  3.0000000
Puffed Rice                             Q  50.00000  1.0000000
Quaker Oat Squares                      Q 200.00000  8.0000000
Raisin Bran                             K 160.00000  4.0000000
Raisin Nut Bran                         G 200.00000  6.0000000
Raisin Squares                          K 180.00000  4.0000000
Rice Chex                               R  97.34513  0.8849558
Rice Krispies                           K 110.00000  2.0000000
Shredded Wheat 'n'Bran                  N 134.32836  4.4776119
Shredded Wheat spoon size               N 134.32836  4.4776119
Smacks                                  K 146.66667  2.6666667
Special K                               K 110.00000  6.0000000
Total Corn Flakes                       G 110.00000  2.0000000
Total Raisin Bran                       G 140.00000  3.0000000
Total Whole Grain                       G 100.00000  3.0000000
Triples                                 G 146.66667  2.6666667
Trix                                    G 110.00000  1.0000000
Wheat Chex                              R 149.25373  4.4776119
Wheaties                                G 100.00000  3.0000000
Wheaties Honey Gold                     G 146.66667  2.6666667
                                            fat    sodium     fibre
100% Bran                             3.0303030 393.93939 30.303030
All-Bran                              3.0303030 787.87879 27.272727
All-Bran with Extra Fiber             0.0000000 280.00000 28.000000
Apple Cinnamon Cheerios               2.6666667 240.00000  2.000000
Apple Jacks                           0.0000000 125.00000  1.000000
Basic 4                               2.6666667 280.00000  2.666667
Bran Chex                             1.4925373 298.50746  5.970149
Bran Flakes                           0.0000000 313.43284  7.462687
Cap'n'Crunch                          2.6666667 293.33333  0.000000
Cheerios                              1.6000000 232.00000  1.600000
Cinnamon Toast Crunch                 4.0000000 280.00000  0.000000
Clusters                              4.0000000 280.00000  4.000000
Cocoa Puffs                           1.0000000 180.00000  0.000000
Corn Chex                             0.0000000 280.00000  0.000000
Corn Flakes                           0.0000000 290.00000  1.000000
Corn Pops                             0.0000000  90.00000  1.000000
Count Chocula                         1.0000000 180.00000  0.000000
Cracklin' Oat Bran                    6.0000000 280.00000  8.000000
Crispix                               0.0000000 220.00000  1.000000
Crispy Wheat & Raisins                1.3333333 186.66667  2.666667
Double Chex                           0.0000000 253.33333  1.333333
Froot Loops                           1.0000000 125.00000  1.000000
Frosted Flakes                        0.0000000 266.66667  1.333333
Frosted Mini-Wheats                   0.0000000   0.00000  3.750000
Fruit & Fibre: Dates Walnuts and Oats 2.9850746 238.80597  7.462687
Fruitful Bran                         0.0000000 358.20896  7.462687
Fruity Pebbles                        1.3333333 180.00000  0.000000
Golden Crisp                          0.0000000  51.13636  0.000000
Golden Grahams                        1.3333333 373.33333  0.000000
Grape Nuts Flakes                     1.1363636 159.09091  3.409091
Grape-Nuts                            0.0000000 680.00000 12.000000
Great Grains Pecan                    9.0909091 227.27273  9.090909
Honey Graham Ohs                      2.0000000 220.00000  1.000000
Honey Nut Cheerios                    1.3333333 333.33333  2.000000
Honey-comb                            0.0000000 135.33835  0.000000
Just Right Fruit & Nut                1.3333333 226.66667  2.666667
Kix                                   0.6666667 173.33333  0.000000
Life                                  2.9850746 223.88060  2.985075
Lucky Charms                          1.0000000 180.00000  0.000000
Mueslix Crispy Blend                  2.9850746 223.88060  4.477612
Multi-Grain Cheerios                  1.0000000 220.00000  2.000000
Nut&Honey Crunch                      1.4925373 283.58209  0.000000
Nutri-Grain Almond-Raisin             2.9850746 328.35821  4.477612
Oatmeal Raisin Crisp                  4.0000000 340.00000  3.000000
Post Nat. Raisin Bran                 1.4925373 298.50746  8.955224
Product 19                            0.0000000 320.00000  1.000000
Puffed Rice                           0.0000000   0.00000  0.000000
Quaker Oat Squares                    2.0000000 270.00000  4.000000
Raisin Bran                           1.3333333 280.00000  6.666667
Raisin Nut Bran                       4.0000000 280.00000  5.000000
Raisin Squares                        0.0000000   0.00000  4.000000
Rice Chex                             0.0000000 212.38938  0.000000
Rice Krispies                         0.0000000 290.00000  0.000000
Shredded Wheat 'n'Bran                0.0000000   0.00000  5.970149
Shredded Wheat spoon size             0.0000000   0.00000  4.477612
Smacks                                1.3333333  93.33333  1.333333
Special K                             0.0000000 230.00000  1.000000
Total Corn Flakes                     1.0000000 200.00000  0.000000
Total Raisin Bran                     1.0000000 190.00000  4.000000
Total Whole Grain                     1.0000000 200.00000  3.000000
Triples                               1.3333333 333.33333  0.000000
Trix                                  1.0000000 140.00000  0.000000
Wheat Chex                            1.4925373 343.28358  4.477612
Wheaties                              1.0000000 200.00000  3.000000
Wheaties Honey Gold                   1.3333333 266.66667  1.333333
                                         carbo    sugars shelf
100% Bran                             15.15152 18.181818     3
All-Bran                              21.21212 15.151515     3
All-Bran with Extra Fiber             16.00000  0.000000     3
Apple Cinnamon Cheerios               14.00000 13.333333     1
Apple Jacks                           11.00000 14.000000     2
Basic 4                               24.00000 10.666667     3
Bran Chex                             22.38806  8.955224     1
Bran Flakes                           19.40299  7.462687     3
Cap'n'Crunch                          16.00000 16.000000     2
Cheerios                              13.60000  0.800000     1
Cinnamon Toast Crunch                 17.33333 12.000000     2
Clusters                              26.00000 14.000000     3
Cocoa Puffs                           12.00000 13.000000     2
Corn Chex                             22.00000  3.000000     1
Corn Flakes                           21.00000  2.000000     1
Corn Pops                             13.00000 12.000000     2
Count Chocula                         12.00000 13.000000     2
Cracklin' Oat Bran                    20.00000 14.000000     3
Crispix                               21.00000  3.000000     3
Crispy Wheat & Raisins                14.66667 13.333333     3
Double Chex                           24.00000  6.666667     3
Froot Loops                           11.00000 13.000000     2
Frosted Flakes                        18.66667 14.666667     1
Frosted Mini-Wheats                   17.50000  8.750000     2
Fruit & Fibre: Dates Walnuts and Oats 17.91045 14.925373     3
Fruitful Bran                         20.89552 17.910448     3
Fruity Pebbles                        17.33333 16.000000     2
Golden Crisp                          12.50000 17.045455     1
Golden Grahams                        20.00000 12.000000     2
Grape Nuts Flakes                     17.04545  5.681818     3
Grape-Nuts                            68.00000 12.000000     3
Great Grains Pecan                    39.39394 12.121212     3
Honey Graham Ohs                      12.00000 11.000000     2
Honey Nut Cheerios                    15.33333 13.333333     1
Honey-comb                            10.52632  8.270677     1
Just Right Fruit & Nut                26.66667 12.000000     3
Kix                                   14.00000  2.000000     2
Life                                  17.91045  8.955224     2
Lucky Charms                          12.00000 12.000000     2
Mueslix Crispy Blend                  25.37313 19.402985     3
Multi-Grain Cheerios                  15.00000  6.000000     1
Nut&Honey Crunch                      22.38806 13.432836     2
Nutri-Grain Almond-Raisin             31.34328 10.447761     3
Oatmeal Raisin Crisp                  27.00000 20.000000     3
Post Nat. Raisin Bran                 16.41791 20.895522     3
Product 19                            20.00000  3.000000     3
Puffed Rice                           13.00000  0.000000     3
Quaker Oat Squares                    28.00000 12.000000     3
Raisin Bran                           18.66667 16.000000     2
Raisin Nut Bran                       21.00000 16.000000     3
Raisin Squares                        30.00000 12.000000     3
Rice Chex                             20.35398  1.769912     1
Rice Krispies                         22.00000  3.000000     1
Shredded Wheat 'n'Bran                28.35821  0.000000     1
Shredded Wheat spoon size             29.85075  0.000000     1
Smacks                                12.00000 20.000000     2
Special K                             16.00000  3.000000     1
Total Corn Flakes                     21.00000  3.000000     3
Total Raisin Bran                     15.00000 14.000000     3
Total Whole Grain                     16.00000  3.000000     3
Triples                               28.00000  4.000000     3
Trix                                  13.00000 12.000000     2
Wheat Chex                            25.37313  4.477612     1
Wheaties                              17.00000  3.000000     1
Wheaties Honey Gold                   21.33333 10.666667     1
                                      potassium vitamins
100% Bran                             848.48485 enriched
All-Bran                              969.69697 enriched
All-Bran with Extra Fiber             660.00000 enriched
Apple Cinnamon Cheerios                93.33333 enriched
Apple Jacks                            30.00000 enriched
Basic 4                               133.33333 enriched
Bran Chex                             186.56716 enriched
Bran Flakes                           283.58209 enriched
Cap'n'Crunch                           46.66667 enriched
Cheerios                               84.00000 enriched
Cinnamon Toast Crunch                  60.00000 enriched
Clusters                              210.00000 enriched
Cocoa Puffs                            55.00000 enriched
Corn Chex                              25.00000 enriched
Corn Flakes                            35.00000 enriched
Corn Pops                              20.00000 enriched
Count Chocula                          65.00000 enriched
Cracklin' Oat Bran                    320.00000 enriched
Crispix                                30.00000 enriched
Crispy Wheat & Raisins                160.00000 enriched
Double Chex                           106.66667 enriched
Froot Loops                            30.00000 enriched
Frosted Flakes                         33.33333 enriched
Frosted Mini-Wheats                   125.00000 enriched
Fruit & Fibre: Dates Walnuts and Oats 298.50746 enriched
Fruitful Bran                         283.58209 enriched
Fruity Pebbles                         33.33333 enriched
Golden Crisp                           45.45455 enriched
Golden Grahams                         60.00000 enriched
Grape Nuts Flakes                      96.59091 enriched
Grape-Nuts                            360.00000 enriched
Great Grains Pecan                    303.03030 enriched
Honey Graham Ohs                       45.00000 enriched
Honey Nut Cheerios                    120.00000 enriched
Honey-comb                             26.31579 enriched
Just Right Fruit & Nut                126.66667     100%
Kix                                    26.66667 enriched
Life                                  141.79104 enriched
Lucky Charms                           55.00000 enriched
Mueslix Crispy Blend                  238.80597 enriched
Multi-Grain Cheerios                   90.00000 enriched
Nut&Honey Crunch                       59.70149 enriched
Nutri-Grain Almond-Raisin             194.02985 enriched
Oatmeal Raisin Crisp                  240.00000 enriched
Post Nat. Raisin Bran                 388.05970 enriched
Product 19                             45.00000     100%
Puffed Rice                            15.00000     none
Quaker Oat Squares                    220.00000 enriched
Raisin Bran                           320.00000 enriched
Raisin Nut Bran                       280.00000 enriched
Raisin Squares                        220.00000 enriched
Rice Chex                              26.54867 enriched
Rice Krispies                          35.00000 enriched
Shredded Wheat 'n'Bran                208.95522     none
Shredded Wheat spoon size             179.10448     none
Smacks                                 53.33333 enriched
Special K                              55.00000 enriched
Total Corn Flakes                      35.00000     100%
Total Raisin Bran                     230.00000     100%
Total Whole Grain                     110.00000     100%
Triples                                80.00000 enriched
Trix                                   25.00000 enriched
Wheat Chex                            171.64179 enriched
Wheaties                              110.00000 enriched
Wheaties Honey Gold                    80.00000 enriched
> 
</code>

<code>boxplot(sugars ~ shelf, data=UScereal)
boxplot(sugars ~ shelf, data=UScereal,
        main="Sugar Content by Shelf",
        xlab="Shelf", ylab="Sugar (grams per portion)")
</code>
{{:R:boxplot2.png}}

====== Creating a Histogram ======
Use hist(x), where x is a vector of numeric values.

<code>data(Cars93, package="MASS")
hist(Cars93$MPG.city)
hist(Cars93$MPG.city, 20)
hist(Cars93$MPG.city, 20, main="City MPG (1993)", xlab="MPG")
</code>

{{:r:hist_Cars93.png}}
====== Creating a Normal Quantile-Quantile (Q-Q) Plot ======

<code>data(Cars93, package="MASS")
qqnorm(Cars93$Price, main="Q-Q Plot: Price")
qqline(Cars93$Price)
</code>

<code>data(Cars93, package="MASS")
qqnorm(log(Cars93$Price), main="Q-Q Plot: log(Price)")
qqline(log(Cars93$Price))</code>

{{:R:qqplot.png}}

====== E.G. ======
<code>

#
#  Comment:
# 
#  Examples of the use of standard high-level plotting functions.
# 
#  In each case, extra output is also added using low-level 
#  plotting functions.
#


par(mfrow=c(3, 2))

# Scatterplot
x <- c(0.5, 2, 4, 8, 12, 16)
y1 <- c(1, 1.3, 1.9, 3.4, 3.9, 4.8)
y2 <- c(4, .8, .5, .45, .4, .3)
par(las=1, mar=c(4, 4, 2, 4))
plot.new()
plot.window(range(x), c(0, 6))
lines(x, y1)
lines(x, y2)
points(x, y1, pch=16, cex=2)
points(x, y2, pch=21, bg="white", cex=2)
par(col="grey50", fg="grey50", col.axis="grey50")
axis(1, at=seq(0, 16, 4))
axis(2, at=seq(0, 6, 2))
axis(4, at=seq(0, 6, 2))
box(bty="u")
mtext("Travel Time (s)", side=1, line=2, cex=0.8)
mtext("Responses per Travel", side=2, line=2, las=0, cex=0.8)
mtext("Responses per Second", side=4, line=2, las=0, cex=0.8)
text(4, 5, "Bird 131")
par(mar=c(5.1, 4.1, 4.1, 2.1), col="black", fg="black", col.axis="black")

# Histogram
# Random data
Y <- rnorm(50)
# Make sure no Y exceed [-3.5, 3.5]
Y[Y < -3.5 | Y > 3.5] <- NA
x <- seq(-3.5, 3.5, .1)
dn <- dnorm(x)
par(mar=c(4.5, 4.1, 3.1, 0))
hist(Y, breaks=seq(-3.5, 3.5), ylim=c(0, 0.5), 
     col="grey80", freq=FALSE)
lines(x, dnorm(x), lwd=2)
par(mar=c(5.1, 4.1, 4.1, 2.1))

# Barplot
# Modified from example(barplot)
par(mar=c(2, 3.1, 2, 2.1))
midpts <- barplot(VADeaths, col=grey(0.5 + 1:5/12), 
                  names=rep("", 4))
mtext(sub(" ", "\n", colnames(VADeaths)),
      at=midpts, side=1, line=0.5, cex=0.5)
text(rep(midpts, each=5), apply(VADeaths, 2, cumsum) - VADeaths/2,
     VADeaths, col=rep(c("white", "black"), times=2:3, cex=0.8))
par(mar=c(5.1, 4.1, 4.1, 2.1))

# Boxplot
# Modified example(boxplot) - itself from suggestion by Roger Bivand
par(mar=c(3, 4.1, 2, 0))
     boxplot(len ~ dose, data = ToothGrowth,
             boxwex = 0.25, at = 1:3 - 0.2,
             subset= supp == "VC", col="grey90",
             xlab="",
             ylab="tooth length", ylim=c(0,35))
     mtext("Vitamin C dose (mg)", side=1, line=2.5, cex=0.8)
     boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
             boxwex = 0.25, at = 1:3 + 0.2,
             subset= supp == "OJ", col="grey70")
     legend(1.5, 9, c("Ascorbic acid", "Orange juice"), bty="n",
            fill = c("grey90", "grey70"))
par(mar=c(5.1, 4.1, 4.1, 2.1))

# Persp
# Almost exactly example(persp)
    x <- seq(-10, 10, length= 30)
     y <- x
     f <- function(x,y) { r <- sqrt(x^2+y^2); 10 * sin(r)/r }
     z <- outer(x, y, f)
     z[is.na(z)] <- 1
# 0.5 to include z axis label
par(mar=c(0, 0.5, 0, 0), lwd=0.1)
     persp(x, y, z, theta = 30, phi = 30, expand = 0.5, col = "grey80")
par(mar=c(5.1, 4.1, 4.1, 2.1), lwd=1)

# Piechart
# Example 4 from help(pie)
par(mar=c(0, 2, 1, 2), xpd=FALSE, cex=0.5)
     pie.sales <- c(0.12, 0.3, 0.26, 0.16, 0.04, 0.12)
     names(pie.sales) <- c("Blueberry", "Cherry",
         "Apple", "Boston Cream", "Other", "Vanilla")
     pie(pie.sales, col = gray(seq(0.4,1.0,length=6)))



</code>
{{:R:various_graphs.png}}

<code>#
# Comment:
#
# A bit of mucking around is required to get the second (whole-world)
# map positioned correctly;  this provides an example of calling a 
# plotting function to perform calculations but do no drawing (see the
# second call to the map() function).
#
# Makes use of the "maps" and "mapproj" packages to draw the maps.
#


library(maps)
par(mar=rep(0, 4))
map("nz", fill=TRUE, col="grey80")
points(174.75, -36.87, pch=16, cex=2)
arrows(172, -36.87, 174, -36.87, lwd=3)
text(172, -36.87, "Auckland  ", adj=1, cex=2)
# mini world map as guide
maplocs <- map(projection="sp_mercator", wrap=TRUE, lwd=0.1, 
               col="grey", ylim=c(-60, 75),
               interior=FALSE, orientation=c(90, 180, 0), add=TRUE,
               plot=FALSE)
xrange <- range(maplocs$x, na.rm=TRUE)
yrange <- range(maplocs$y, na.rm=TRUE)
aspect <- abs(diff(yrange))/abs(diff(xrange))
# customised to 6.5 by 4.5 figure size
par(fig=c(0.99 - 0.5, 0.99, 0.01, 0.01 + 0.5*aspect*4.5/6.5), 
    mar=rep(0, 4), new=TRUE)
plot.new()
plot.window(xlim=xrange,
            ylim=yrange)
map(projection="sp_mercator", wrap=TRUE, lwd=0.1, ylim=c(-60, 75),
    interior=FALSE, orientation=c(90, 180, 0), add=TRUE)
symbols(-.13, -0.8, circles=1, inches=0.1, add=TRUE)</code>
{{:R:using_maps_R.png}}

<code>par(mfrow=c(2, 2))
z <- 2 * volcano        # Exaggerate the relief
x <- 10 * (1:nrow(z))   # 10 meter spacing (S to N)
y <- 10 * (1:ncol(z))   # 10 meter spacing (E to W)
# Don't draw the grid lines :  border = NA
par(mar=rep(0, 4))
persp(x, y, z, theta = 135, phi = 30, col = "light grey", scale = FALSE,
      ltheta = -120, shade = 0.75, border = NA, box = FALSE)
mtext("persp()", side=3, line=-2)
par(mar=c(3, 3, 2, 0.5))
# Note that  example(trees)  shows more sensible plots!
N <- nrow(trees)
attach(trees)
# Girth is diameter in inches
symbols(Height, Volume, circles=Girth/24, inches=FALSE,
        main="", xlab="", ylab="", bg=grey(Girth/max(Girth)))
mtext("symbols()", side=3, line=0.5)
par(mar=rep(0.5, 4))
contour(x, y, z, asp=1, labcex=0.35, axes=FALSE)
rect(0, 0, 870, 620)
mtext("contour()", side=3, line=-1.5)
image(x, y, z, asp=1, col=grey(0.5 + 1:12/24), xlab="", ylab="", axes=FALSE)
rect(min(x)-5, min(y)-5, max(x)+5, max(y)+5)
mtext("image()", side=3, line=-1.5)


</code>
{{:R:poly_graph.png}}