1 require(ggplot2)
   2 ## load the data set GaltonFamilies from the package HistData 
   3 require(HistData)
   4 
   5 ## bivariate plots
   6 ggplot(GaltonFamilies, aes(x=mother,y=father)) +
   7     geom_point() 
   8 
   9 
  10 ggsave("scatter.png")
  11 
  12 ## adding a trend line
  13 ggplot(GaltonFamilies, aes(x=mother,y=father)) +
  14     geom_point() +
  15     geom_smooth()
  16 
  17 ggsave("scattertrend1.png")
  18 
  19 
  20 
  21 ## adding a trend line
  22 ggplot(GaltonFamilies, aes(x=mother,y=father)) +
  23     geom_point() +
  24     geom_smooth(method="lm")
  25 
  26 ggsave("scattertrend2.png")
  27 
  28 ## dot plots
  29 ggplot(mtcars, aes(x = mpg)) + geom_dotplot()
  30 ggsave("dotplot1.png")
  31 
  32 ggplot(mtcars, aes(x = mpg)) + geom_dotplot(binwidth = 1.5)
  33 ggsave("dotplot2.png")
  34 
  35 ## Use fixed-width bins
  36 ggplot(mtcars, aes(x = mpg)) +
  37     geom_dotplot(method="histodot", binwidth = 1.5)
  38 ggsave("dotplot3.png")
  39 
  40 ## Some other stacking methods
  41 ggplot(mtcars, aes(x = mpg)) +
  42     geom_dotplot(binwidth = 1.5, stackdir = "center")
  43 ggsave("dotplot4.png")
  44 
  45 
  46 
  47 
  48 
  49 ## Exercises
  50 ## use again the GaltonFamilies data set; produce a scatter plot
  51 ## of childHeight vs midparentHeight
  52 
  53 
  54 
  55 
  56 
  57 ##add a trend line by using geom\_smooth() without any
  58 ## arguments. Which method is used?
  59 
  60 
  61 
  62 ## add a second trend line, this time a linear one!
  63 
  64 
  65 
  66 
  67 ## now use the aesthetic colour in the first line of the plot
  68 ## definition. What happens?
  69 
  70 
  71 
  72 
  73 
  74 
  75 ## INBOtheme
  76 install.packages("INBOtheme", repos="http://R-Forge.R-project.org")
  77 require(INBOtheme)
  78 
  79 p1 + theme_elsevier()
  80 ggsave("testelsevier.png",width = 15, height = 10, units = "cm")
  81 
  82 p1 + theme_INBO()
  83 p1 + theme_map()
  84 p1 + theme_inbo2015()
  85 
  86 
  87 ## density legends
  88 install.packages("oaPlots", repos = "http://repos.openanalytics.eu", type = "source")
  89 
  90 require(oaPlots)
  91 scatterplotDL(GaltonFamilies$mother,GaltonFamilies$childHeight,
  92               colorVar = GaltonFamilies$childHeight,
  93               colorPalette = INBOextra,
  94               pch = 19)
  95 
  96 scatterplotDL(GaltonFamilies$mother,GaltonFamilies$childHeight,
  97               colorVar = GaltonFamilies$childHeight,
  98               colorPalette = blues9,
  99               pch = 19)
 100 
 101 savePlot("legendexample.png")
 102 
 103 ## membranes and tritiated water
 104 data <- data.frame(values = c(0.8,0.83,1.89,1.04,1.45,
 105                        1.38,1.91,1.64,0.73,1.46,
 106                        1.15,0.88,0.9,0.74,1.21),
 107                    membrane = rep(LETTERS[1:2],c(10,5)))
 108 
 109 ## histogram
 110 
 111 
 112 
 113 
 114 
 115 ## test
 116 
 117 
 118 
 119 
 120 
 121 ## weight loss programs
 122 
 123 ## data
 124 data <- data <- data.frame(x=c(12.42,9.31,6.83,11.51,10.42,8.87,6.73,9.53,8.8,8.01,7.01,9.69),
 125                    y=c(13.8,10,8.51,11.95,10.66,8.76,7.93,11.81,11.62,9.76,9.2,11.2))
 126 
 127 
 128 ## investigate deviation from normality
 129 ## histogram
 130 
 131 
 132 ## test
 133 
 134 
 135 
 136 ## visualization
 137 
 138 
 139 
 140 ## magnets (require(), data())
 141