#  examples from ggplot2 book
# http://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis/dp/0387981403/ref=sr_1_1?ie=UTF8&qid=1423697224&sr=8-1&keywords=ggplot2

library(rbokeh)
library(ggplot2)

data(diamonds)

bp <- figure( height = 400, width = 700 )

bp %>% ly_points(carat,price,diamonds,color=cut,size=5)
# add hover
bp %>%
  ly_points(carat,price,diamonds,color=cut,size=1,hover=list(cut,clarity,color))
# make it a hexbin
bp %>%
  ly_hexbin( carat, price, diamonds )
# make it a hexbin with facet by color
lapply(
  levels(unique(diamonds$color))
  ,function(c){
    figure( height = 300, width = 300, title = paste0("Color: ",c) ) %>%
      ly_hexbin( carat, log(price), diamonds[which(diamonds$color==c),] )
  }
) %>%
  grid_plot( nrow = 3, ncol = 3, same_axes = T )

# histogram on diamonds
bp %>% ly_hist( x = carat, data = diamonds, breaks = 2 )
# density on diamonds
bp %>% ly_density( x = carat, data = diamonds )
# quantile on diamonds
bp %>% ly_quantile(price,group = "color", diamonds)
bp %>% ly_quantile(price,group = "color", diamonds, distn=qnorm)

#demo a transform
bp %>%
  ly_points( cyl, mpg^2, mtcars ) %>%
  # not transformed
  ly_points( cyl, mpg, mtcars, color = "red" )  %>%
  # axis need to come after layers specified
  y_axis( log = T ) 


# set vs map color
bp %>%
  ly_points( mpg, wt, mtcars, color = "purple")
bp %>%
  ly_points( mpg, wt, data.frame(name=rownames(mtcars),mtcars), color = cyl, hover = list(name))




# boxplot
data("Oxboys", package = "nlme")
bp %>%
  ly_boxplot( Occasion, height, Oxboys )