## ----GetLibraries--------------------------------------------------------
library(BrailleR)   
library(ggplot2)   
library(magrittr)
dsmall = diamonds[1:100,]   

## ----g1------------------------------------------------------------------
g1 = qplot(carat, price, data = diamonds)   
# summary(g1)   
g1  
VI(g1)  

## ----g2------------------------------------------------------------------
g2 = qplot(carat, price, data = dsmall, colour = color)    
# summary(g2)   
g2
g2 %>% VI()   
# to get the content of the graph to be printed we need:   
#class(g2)="list"; g2   

## ----g3------------------------------------------------------------------
g3 = qplot(carat, price, data = dsmall, shape = cut)    
# summary(g3)   
g3
VI(g3)   
#class(g3)="list"; g3   

## ----g4------------------------------------------------------------------
# to get semi-transparent points   
g4 = qplot(carat, price, data = diamonds, alpha = I(1/100))    
# summary(g4)   
g4
VI(g4)   

## ----g5------------------------------------------------------------------
# to add a smoother (default is loess for n<1000)   
g5 = qplot(carat, price, data = dsmall, geom = c("point", "smooth"))    
# summary(g5)   
g5
VI(g5)   
#! g5a = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), span = 1)    
library(splines)    
#! g5b = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), method = "lm")    
#! g5c = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), method = "lm", formula = y ~ ns(x,5))    

## ----g6------------------------------------------------------------------
# continuous v categorical   
g6 = qplot(color, price / carat, data = diamonds, geom = "jitter", alpha = I(1 / 50))    
# summary(g6)   
g6
VI(g6)   
g6a = qplot(color, price / carat, data = diamonds, geom = "boxplot")    
# summary(g6a)   
g6a
VI(g6a)   

## ----g7------------------------------------------------------------------
# univariate plots   
g7a = qplot(carat, data = diamonds, geom = "histogram")    
# summary(g7a)   
g7a
VI(g7a)   
g7b = qplot(carat, data = diamonds, geom = "histogram", binwidth = 1, xlim = c(0,3))    
g7b
VI(g7b)   
g7c = qplot(carat, data = diamonds, geom = "histogram", binwidth = 0.1, xlim = c(0,3))
g7c
VI(g7c)   
g7d = qplot(carat, data = diamonds, geom = "histogram", binwidth = 0.01, xlim = c(0,3))    
# summary(g7d)   
g7d
VI(g7d)   

## ----g8------------------------------------------------------------------
g8 = qplot(carat, data = diamonds, geom = "density")    
# summary(g8)   
g8
VI(g8)   

## ----g9------------------------------------------------------------------
# data is separated by implication using the following...   
g9 = qplot(carat, data = diamonds, geom = "density", colour = color)    
# summary(g9)   
g9
VI(g9)   
g10 = qplot(carat, data = diamonds, geom = "histogram", fill = color)    
# summary(g10)   
g10
VI(g10)   

## ----g11-----------------------------------------------------------------
# bar charts for categorical variable   
g11a = qplot(color, data = diamonds)    
# summary(g11a)   
g11a
VI(g11a)   
g11b = qplot(color, data = diamonds, geom = "bar")    
# summary(g11b)   
g11b
VI(g11b)   
g12a = qplot(color, data = diamonds, geom = "bar", weight = carat)   
# summary(g12a)   
g12a
VI(g12a)   
g12b = qplot(color, data = diamonds, geom = "bar", weight = carat) + scale_y_continuous("carat")    
# summary(g12b)   
g12b
VI(g12b)   

## ----g13-----------------------------------------------------------------
# time series plots   
g13a = qplot(date, unemploy / pop, data = economics, geom = "line")    
# summary(g13a)   
g13a
VI(g13a)   
g13b = qplot(date, uempmed, data = economics, geom = "line")    
# summary(g13b)   
g13b
VI(g13b)   

## ----g14-----------------------------------------------------------------
# path plots   
year <- function(x) as.POSIXlt(x)$year + 1900    
g14a = qplot(unemploy / pop, uempmed, data = economics, geom = c("point", "path"))    
# summary(g14a)   
g14a
VI(g14a)   
#g14b = qplot(unemploy / pop, uempmed, data = economics, geom = "path", colour = year(date)) + scale_area()    
#summary(g14b)   
#VI(g14b)   

## ----g15-----------------------------------------------------------------
# facets is the ggplot term for trellis' panels   
g15a = qplot(carat, data = diamonds, facets = color ~ ., geom = "histogram", binwidth = 0.1, xlim = c(0, 3))    
# summary(g15a)   
g15a
VI(g15a)   
g15b = qplot(carat, ..density.., data = diamonds, facets = color ~ ., geom = "histogram", binwidth = 0.1, xlim = c(0, 3))   
# summary(g15b)   
g15b
VI(g15b)   

## ----g16-----------------------------------------------------------------
# rescaling of the axes   
g16 = qplot(carat, price, data = dsmall, log = "xy")   
# summary(g16)   
g16
VI(g16)   

## ----g17-----------------------------------------------------------------
# Facets syntax without a "." before the "~" causes grief
g17 = qplot(displ, hwy, data=mpg, facets =~ year) + geom_smooth()    
# summary(g17)   
g17
VI(g17)   

