First version done: Added code for Base R and ggplot2 plotting

visualization.R

@@ -10,8 +10,18 @@ temp <- tempfile()
 download.file("https://archive.ics.uci.edu/ml/machine-learning-databases/00275/Bike-Sharing-Dataset.zip", temp)
 bike <- read.csv(unz(temp, "day.csv"), stringsAsFactors = FALSE)
 
+#data prep - convert to factors
+iris$class <- factor(iris$class)
+
+bike$dteday <- as.Date(bike$dteday)
+bike$weathersit <- factor(bike$weathersit)
+bike$holiday <- factor(bike$holiday)
+bike$season <- factor(bike$season)
+
+
 ### Graphing using base R ###
 
+
 ### Primary plotting functions
 plot(iris[-length(iris)]) #scatterplot matrix of numeric fields #Example of primary plotting function
 title("Scatterplot Matrix") #If you have a plot already and want to add a title, 
@@ -28,7 +38,7 @@ plot(x = iris$sepal_length, y = iris$sepal_width,
 
 #plot using color argument
 plot(x = iris$sepal_length, y = iris$sepal_width, 
-     col = factor(iris$class))
+     col = iris$class)
 
 ##Strip chart
 stripchart(iris$petal_length) #bare bone
@@ -44,12 +54,19 @@ hist(iris$sepal_length) #bare minimum call
 
 hist(iris$sepal_length, col = "grey", border = "blue") #colour params
 
+hist(iris$sepal_length, breaks = seq(from = 2, to = 9, by = 0.5)) #using break parameter to change the historgram
+
+hist(iris$sepal_length, freq = FALSE) #plotting probabilities instead of frequency
+
 #hist with extra params
 hist(iris$sepal_length, 
      main = "Histogram: Sepal Length", 
      xlab = "Sepal Length",
      labels = TRUE)
 
+attributes(hist(iris$sepal_length)) #attributes for histogram
+hist(iris$sepal_length)$counts #counts
+
 ##Boxplots
 boxplot(iris$sepal_width) #Single column
 boxplot(iris$sepal_length, iris$sepal_width, iris$petal_length, iris$petal_width) #Comparitve Boxplot - 4 columns
@@ -100,8 +117,31 @@ points(x = iris$sepal_length, y = iris$petal_width, pch = 18)
 
 legend(x = 5, c("Sepal Width", "Petal Width"), pch= c(1, 18))
 
+##Adding a curve to the plot - using the curve() function
+hist(iris$sepal_length, density = 20, 
+     probability = TRUE, ylim = c(0,1), xlim = c(3,9),
+     main = "Histogram: Sepal Length", 
+     xlab = "Sepal Length")
+
+curve(dnorm(x, mean = mean(iris$sepal_length), sd = sd(iris$sepal_length)), y = 3, to = 9,
+      col = "red", lwd = 2, add = TRUE)
+
+##Adding secondary axis
+par(mar = c(5,5,2,5))
+with(bike, plot(x = dteday, y = cnt, type = "l", col="red",  
+             ylab = "Sepal Width", xlab = "Date"))
+
+par(new=TRUE)
+with(bike, plot(x = dteday, y = temp, pch = 16, cex = 0.6,
+                axes = FALSE, xlab = NA, ylab = NA))
+axis(side=4)
+mtext(side = 4, line = 3, "Temperature Recorded")
+legend("topleft",
+       legend = c("Count", "Temp"),
+       lty = c(1,0), pch = c(NA, 16), col = c("red", "black"))
+
 ### Parameter settings
-par(mfcol = c(1, 2))
+par(mfcol = c(2, 2))
 
 #par(mfcol = c(1, 1))
 
@@ -114,6 +154,172 @@ plot(x = iris$sepal_length, y = iris$sepal_width,
      main = "Sepal: Length Vs Width", xlab = "Sepal Length", ylab = "Sepal Width")
 dev.off()
 
+#----#
+
+
+
+### Graphing using ggplot2 ###
+#require(ggplot2)
+
+### qplot function
+##Line plot
+qplot(x = dteday, y = cnt, data = bike, 
+      color = weathersit, geom = "line")
+
+qplot(x = dteday, y = cnt, data = bike, 
+      color = weathersit) + geom_line()
+
+##Scatter plot
+qplot(x = dteday, y = cnt, data = bike) #base call
+
+qplot(x = dteday, y = cnt, data = bike, 
+      color = weathersit, geom = "point")
+
+qplot(y = cnt, x = dteday, geom = "point", data = bike,
+      color = weathersit, shape = holiday)
+
+qplot(x = dteday, y = cnt, data = bike, #smoother
+      color = weathersit, geom = "smooth", method = "lm")
+
+##Boxplot
+qplot(x = class, y = sepal_length, formula = y ~ x, 
+      data = iris, geom = "boxplot")
+
+##Histogram
+qplot(bike$cnt, geom = "histogram", binwidth = 500, xlim = c(0, 9000))
+
+qplot(bike$cnt, geom = "histogram", breaks = seq(0, 9000, by = 500), 
+      xlim = c(0, 9000))
+
+##Density plot
+qplot(casual, geom = "density", data = bike,
+      colour = weathersit)
+
+#using facets
+qplot(cnt, geom = "density", data = bike, 
+      facets = weathersit~.)
+
+qplot(cnt, geom = "density", data = bike, 
+      facets = .~weathersit)
+
+### ggplot function
+
+##Scatter plot
+ggplot(data = bike) + geom_point(aes(x = hum, y = cnt)) #bare bone call
+
+#multi-layered plots
+p <- ggplot(data = bike, aes(x = hum, y = cnt))
+p + geom_point()
+p + geom_point(aes(color = season)) #colour aesthetics
+p + geom_point(aes(shape = holiday)) #shape aesthetics
+
+#set colours for points
+p + geom_point(color = "green4")
+p + geom_point(aes(color = season), shape = 5) + scale_color_manual(values = c("blue", "red", 
+                                                                               "yellow", "green"))
+
+#set shape for points
+p + geom_point(shape = 4)
+p + geom_point(aes(shape = holiday)) + scale_shape_manual(values = c(1, 4))
+
+#scale axis limits
+p + geom_point() + scale_x_continuous(limits = c(-1,1))
+
+#set the legend
+p + geom_point(aes(color = holiday)) + theme(legend.position = "top")
+
+p + geom_point(aes(color = holiday)) + theme(legend.position = "none") #remove legend
+
+##Histogram
+ggplot(data = bike, aes(x = casual)) + geom_histogram() #bare bone
+
+ggplot(data = bike) + geom_histogram(aes(x = casual), binwidth = 100, 
+                                     fill = "grey", color = "black")
+
+ggplot(data = bike, aes(x = casual, fill = weathersit)) + geom_histogram()
+
+##Density plot
+ggplot(data = bike) + geom_density(aes(x = casual), fill = "grey")
+
+ggplot(data = bike, aes(x = casual)) + geom_line(stat = "density")
+
+ggplot(data = bike, aes(x = casual, y = ..density..)) + 
+  geom_histogram(binwidth = 100, fill = "grey", color = "black") + 
+  geom_line(stat = "density", color = "blue3")
+
+##Boxplot
+ggplot(data = bike, aes(y = cnt, x = 1)) + geom_boxplot() #bare bone
+
+ggplot(data = bike, aes(y = cnt, x = holiday)) + geom_boxplot() + coord_flip()
+
+ggplot(data = bike, aes(y = cnt, x = holiday)) + geom_boxplot(fill = "lightblue") #outlier.size/shape
+
+##Violin plot
+ggplot(data = bike, aes(y = cnt, x = season)) + geom_violin()
+
+p <- ggplot(data = bike, aes(y = cnt, x = factor(season)))
+p + geom_violin()
+p + geom_violin() + geom_point()
+
+##Line plot
+ggplot(data = bike, aes(y = cnt, x = dteday)) + geom_line()
+
+bike$dteyear <- format(bike$dteday, "%Y")
+bike$dtemonth <- format(bike$dteday, "%b")
+
+p <- ggplot(data = bike, aes(y = cnt, x = dtemonth))
+p + geom_line(aes(color = dteyear, group = dteyear))
+
+##Add lines to the plots
+p <- ggplot(data = bike, aes(x = windspeed, y = casual))
+p + geom_point() + geom_vline(xintercept = 0.25, color = "red")
+p + geom_point() + geom_hline(yintercept = 1500, color = "green")
+cf <- coefficients(lm(casual ~ windspeed, data = bike))
+p + geom_point() + geom_abline(intercept = cf[["(Intercept)"]], 
+                               slope = cf[["windspeed"]], 
+                               color = "blue3", linetype = "dashed")
+
+##Manipulate text in the plots
+p <- ggplot(data = bike, aes(x = windspeed, y = casual))
+
+#add title
+p + geom_point() + ggtitle("Casual Vs Windspeed")
+p + geom_point() + labs(title = "Rented Casual Vs Windspeed")
+
+#change x and y labels
+p + geom_point() + xlab("Wind Speed") + ylab("Rented Casual")
+
+p + geom_point() + theme(axis.title = element_text(size = 10, lineheight = .9, 
+                                                   color = "green")) #formatting axis labels
+
+#insert text in the plot with annotate
+bike[bike$windspeed > 0.5, c("casual", "windspeed")]
+p + geom_point() + annotate("text", x = 0.507463, y = 532, 
+                            label = "Scatter", size = 2, color = "blue2")
+
+#insert text labels with geom_text
+p + geom_point() + geom_text(aes(label = windspeed), size = 2, color = "blue1")
+
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+
+#----#
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