Rickshaw graph

if(!file.exists("data.csv")) {
  #Download
  url<-"https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2"
  download.file(url,"data.bz2",method="curl")
  
  # Unzip
  zz <- readLines(gzfile("data.bz2"))
  zz <- iconv(zz, "latin1", "ASCII", sub="")
  writeLines(zz, "data.csv")
  rm(zz)
  }

## Read data in
data<-read.csv("data.csv", sep=",", quote = "\"", header=TRUE)

# Add a new year column to the dataset
data<-data.frame(Year=format(as.Date(data$BGN_DATE,format="%m/%d/%Y"),"%Y"),data)

# Replace Thunderstorm winds, Thunderstorm wind with TTSM WIND
data$EVTYPE = sapply(data$EVTYPE,function(x) gsub("THUNDERSTORM WINDS|MARINE TSTM WIND|THUNDERSTORM WIND","TSTM WIND",x))

require(rCharts)

Loading required package: rCharts

dat = as.data.frame(table(data[,c("Year","EVTYPE")]))

a = sort(apply(table(data[,c("Year","EVTYPE")]),2,sum),decreasing=TRUE)[1:10]

dat = dat[dat$EVTYPE %in% names(a),]

dat$Year = paste0(dat$Year,"-01-01")
dat$Year = as.numeric(
  as.POSIXct(dat$Year)
)

r2 <- Rickshaw$new()
r2$layer(
  Freq ~ Year,
  data = dat,
  type = "line",
  groups = "EVTYPE",
  height = 240,
  width = 600
)
#turn off all the nice built in features
#to match the sparse second example
r2$set(
  hoverDetail = TRUE,
  xAxis = TRUE,
  yAxis = TRUE,
  shelving = FALSE,
  legend = TRUE,
  slider = TRUE,
  highlight = TRUE
)
r2$show('iframesrc', cdn = TRUE)

# r2$show(T)