gistfile1.txt

####################################
# diamond data bar chart
# Questions? Email [email protected]
# For more docs, see plot.ly/api
####################################
library(plotly)

py <- plotly(username='USERNAME', key='API_KEY')


#return list of n ggplot default colors (evenly spaced around the color wheel)
gg_color_hue <- function(n) {
	  hues = seq(15, 375, length=n+1)
	  hcl(h=hues, l=65, c=100)[1:n]
}

#combine elements with same name in two named lists (useful for combining layouts)
appendList <- function (x, val) 
{
    stopifnot(is.list(x), is.list(val))
    xnames <- names(x)
    for (v in names(val)) {
        x[[v]] <- if (v %in% xnames && is.list(x[[v]]) && is.list(val[[v]])) 
            appendList(x[[v]], val[[v]])
        else c(x[[v]], val[[v]])
    }
    x
}

#returns margins, based on existence of legend
margins <- function(l){
						if(l){
									return (list(
													b = 57,
													t = 80,
													r = 151,
													l = 81,
													pad = 0
												 )
											)
								  }
					    else{
					    			return (list(
													b = 57,
													t = 80,
													r = 41,
													l = 81,
													pad = 0
												 )
											)
					    	}
					}
##########################################################
library(ggplot2)

#convert data frame to list of lists used by plotly
l_diamonds <- lapply(split(diamonds,seq_along(diamonds[1,1])), function(l){list(as.list(l))})

#extract data
clarity <- get('clarity',l_diamonds[[1]][[1]])
cut <- row.names(table(get('cut',l_diamonds[[1]][[1]])))


y <- lapply(seq(5),function(i){
								as.vector(
											table(
													get('clarity',subset(diamonds, cut==cut[i]))
												 )
										)


							}


			)
#generate colors
ggcols <- gg_color_hue(5)
cols <- list(ggcols[1],ggcols[2],ggcols[3], ggcols[4],ggcols[5])


#populate dataset
#data <- as.list(seq())
data <- 
	lapply(seq(5),function(i){return(list(
			x = row.names(table(clarity)),
			y = y[i][[1]],
			name = cut[i],
			type = 'bar',
			mode = 'stack',
			marker = list(
							color = rep(cols[i],length(row.names(table(clarity))))
						 )
		))})

	

legend <- TRUE # change to TRUE to make legend visible and adjust layout (to ggplot standards)
#default layout options for ggplot default theme_grey exported to pdf through Quartz 2 (OSX)
gglayout <- list(
					plot_bgcolor = "#E5E5E5",
					font = list(
									color = "#000000",
									face = "Arial, sans-serif",
									size = 12
								),
					xaxis = list(
									gridcolor = "#FFFFFF",
									gridwith = 1,
									zeroline = FALSE,
									showline = FALSE,
									mirror = FALSE,
									tickwidth =1,
									ticklen = 5,
									tickcolor = "7f7f7f",
									tickfont = list(
														color = "#7f7f7f",
														face = "Arial, sans-serif",
														size = 9.6
													)
								),
					yaxis = list(
									gridcolor = "#FFFFFF",
									zeroline = FALSE,
									showline = FALSE,
									mirror = FALSE,
									tickwidth =1,
									ticklen = 5,
									tickcolor = "7f7f7f",
									tickfont = list(
										color = "#7f7f7f",
										face = "Arial, sans-serif",
										size = 9.6
									)
								),
					showlegend = legend,
					legend =  list(
									bgcolor = 'F2F2F2',
									bordercolor = 'rgba(0,0,0,0)',
									x = 1.4
								  ),
					margin = margins(legend)

 				)


#layout options for this plot
plotlayout <- list(
					xaxis = list(
									title = 'wt'
								),
					yaxis = list(
									title = 'mpg',
									ticks = list(500,1000)
								)

				)

layout <- appendList(gglayout,plotlayout)


response<-py$plotly(data, kwargs = list(layout=layout))

# url and filename
url <- response$url
filename <- response$filename