A quick datadr / trelliscope demo

code.R

## installation
##---------------------------------------------------------

install.packages("devtools") # if not installed
devtools::install_github("tesseradata/datadr")
devtools::install_github("tesseradata/trelliscope")
devtools::install_github("hafen/housingData")
devtools::install_github("bokeh/rbokeh")

## quick trelliscope example
##---------------------------------------------------------

# load packages
library(trelliscope)
library(rbokeh)
library(housingData)

# plot median monthly list price vs. time
panel <- function(x)
  figure() %>% ly_points(time, medListPriceSqft, data = x)

# apply this plot to each county/state in the data and view
housing %>%
  qtrellis(by = c("county", "state"), panel, layout = c(2, 4))

## more involved example
##---------------------------------------------------------

# divide housing data by county and state
byCounty <- divide(housing,
   by = c("county", "state"))

# look at byCounty object
byCounty

# look at a subset of byCounty
byCounty[[1]]

# create a panel function of list and sold price vs. time
timePanel <- function(x)
  xyplot(medListPriceSqft + medSoldPriceSqft ~ time, type = c("p", "g"),
    data = x, auto.key = TRUE, ylab = "Price / Sq. Ft.",
    par.settings = list(superpose.symbol = list(pch = 19, alpha = 0.7)))

# test function on a subset
timePanel(byCounty[[20]]$value)

# create a cognostics function of metrics of interest
priceCog <- function(x) {
  zillowString <- gsub(" ", "-", do.call(paste, getSplitVars(x)))
  list(
    slope = cog(coef(lm(medListPriceSqft ~ time, data = x))[2],
      desc = "list price slope"),
    meanList = cogMean(x$medListPriceSqft),
    meanSold = cogMean(x$medSoldPriceSqft),
    nObs = cog(length(which(!is.na(x$medListPriceSqft))),
      desc = "number of non-NA list prices"),
    zillowHref = cogHref(
      sprintf("http://www.zillow.com/homes/%s_rb/", zillowString),
      desc = "zillow link")
  )
}

# test cognostics function on a subset
priceCog(byCounty[[1]]$value)

# create the display and add to vdb
makeDisplay(byCounty,
  name = "list_sold_vs_time_quickstart",
  desc = "List and sold price over time",
  panelFn = timePanel,
  cogFn = priceCog)

# view the result
view()

# if you want to put these out on shinyapps.io:
# http://shiny.rstudio.com/articles/shinyapps.html
# deployToShinyApps()

## datadr example
##---------------------------------------------------------

# look at housing data
head(housing)

# divide by county and state
byCounty <- divide(housing,
  by = c("county", "state"), update = TRUE)

# look at result
byCounty

# look at a subset
byCounty[[1]]

# look at a subset by key
byCounty[["county=New York County|state=NY"]]

# apply a transformation to get slope of fitted line of list price vs. time
lmCoef <- function(x)
  coef(lm(medListPriceSqft ~ time, data = x))[2]

byCountySlope <- addTransform(byCounty, lmCoef)

# look at a subset
byCountySlope[[1]]

# recombine the slope coefficients into a data frame
countySlopes <- recombine(byCountySlope, combRbind)

head(countySlopes)