Loading Libraries

library(knitr)
library(printr)
library(rCharts)

Dataset used in this document

iris

head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa

HairEyeColor

hair_eye = as.data.frame(HairEyeColor)
hair_eye
Hair Eye Sex Freq
Black Brown Male 32
Brown Brown Male 53
Red Brown Male 10
Blond Brown Male 3
Black Blue Male 11
Brown Blue Male 50
Red Blue Male 10
Blond Blue Male 30
Black Hazel Male 10
Brown Hazel Male 25
Red Hazel Male 7
Blond Hazel Male 5
Black Green Male 3
Brown Green Male 15
Red Green Male 7
Blond Green Male 8
Black Brown Female 36
Brown Brown Female 66
Red Brown Female 16
Blond Brown Female 4
Black Blue Female 9
Brown Blue Female 34
Red Blue Female 7
Blond Blue Female 64
Black Hazel Female 5
Brown Hazel Female 29
Red Hazel Female 7
Blond Hazel Female 5
Black Green Female 2
Brown Green Female 14
Red Green Female 7
Blond Green Female 8

HairEyeColor

data(tips, package = 'reshape2')
head(tips)
total_bill tip sex smoker day time size
16.99 1.01 Female No Sun Dinner 2
10.34 1.66 Male No Sun Dinner 3
21.01 3.50 Male No Sun Dinner 3
23.68 3.31 Male No Sun Dinner 2
24.59 3.61 Female No Sun Dinner 4
25.29 4.71 Male No Sun Dinner 4

Plot 1: Facetted Scatterplot

names(iris) = gsub("\\.", "", names(iris))

p1 <- rPlot(SepalLength ~ SepalWidth | Species, 
            data = iris, 
            color = 'Species', 
            type = 'point')

p1$show('inline', include_assets = TRUE)

\(\\\)

Plot 2: Facetted Barplot

p2 <- rPlot(Freq ~ Hair, 
            color = 'Eye', 
            data = hair_eye, 
            type = 'bar')

p2$show('inline', include_assets = TRUE)

\(\\\)

p2 <- rPlot(Freq ~ Hair, 
            color = 'Eye', 
            data = hair_eye, 
            type = 'bar')

p2$facet(var = 'Eye', type = 'wrap', rows = 2)

p2$show('inline', include_assets = TRUE)

\(\\\)

Plot 3: Boxplot

p3 <- rPlot(x = 'day', 
            y = 'box(tip)', 
            data = tips, 
            type = 'box')

p3$show('inline', include_assets = TRUE)

\(\\\)

Plot 4: Barplot

require(plyr)
Loading required package: plyr
dat = count(mtcars, .(gear, am))

p4 <- rPlot(x = 'bin(gear, 1)', 
            y = 'freq', 
            data = dat, 
            type = 'bar', 
            list(var = 'am', type = 'wrap'))

p4$show('inline', include_assets = TRUE)

\(\\\)

Plot 5 : Heat Map

dat = expand.grid(x = 1:5, y = 1:5)

dat = transform(dat, value = sample(1:5, 25, replace = T))

p5 <- rPlot(x = 'bin(x, 1)', 
            y = 'bin(y, 1)', 
            color = 'value', 
            data = dat, 
            type = 'tile')

p5$show('inline', include_assets = TRUE)

\(\\\)

Plot 6: NBA Heat Map

require(reshape2); require(scales); require(plyr)
Loading required package: reshape2
Loading required package: scales
nba <- read.csv('http://datasets.flowingdata.com/ppg2008.csv')
nba.m <- ddply(melt(nba), .(variable), transform, rescale = rescale(value))
Using Name as id variables
p6 <- rPlot(Name ~ variable, color = 'rescale', data = nba.m, type = 'tile', height = 600)
p6$guides("{color: {scale: {type: gradient, lower: white, upper: steelblue}}}")

p6$show('inline', include_assets = TRUE)

Reference