ajschumacher

test <- data.frame(state=c("Florida", "Virginia", "Texas", "California",
                           "Georgia", "North Carolina", "New York",
                           "Missouri", "Illinois", "Maryland", "Pennsylvania",
                           "Tennessee", "Colorado", "Washington", "Arizona",
                           "Ohio", "Wisconsin", "District of Columbia",
                           "Michigan", "New Jersey", "Utah", "Louisiana",
                           "Minnesota", "Alabama", "Kansas", "Massachusetts",
                           "Indiana", "South Carolina", "Arkansas", "Oregon",
                           "Nevada", "Kentucky", "Nebraska", "(not set)",
                           "Connecticut", "New Mexico", "Oklahoma",

ajschumacher

# oh my quiz

What the what?
: Option!
: Correct option! :

ajschumacher

longest.ordered <- function(original) {
  results <- list()
  for (item in original) {
    static_results <- results
    for (stem in static_results) {
      if (stem[length(stem)] <= item) {
        results[[length(results)+1]] <- c(stem, item)
      }
    }
    results[[length(results)+1]] <- item

ajschumacher

• thing

ajschumacher

def _find_getch():
    # courtesy of Louis
    # http://stackoverflow.com/questions/510357/
    try:
        import termios
    except ImportError:
        # Non-POSIX. Return msvcrt's (Windows') getch.
        import msvcrt
        return msvcrt.getch

ajschumacher

This shows New York City subway usage based on turnstile data. Hovering over a day shows the number of entries through subway turnstiles in that day.

Notice the clear effects of hurricanes Irene and Sandy.

More details and source code available. Visualization based (heavily) on Mike Bostock's excellent example.

ajschumacher

This d3.js visualization uses public data from NYC public schools. Original data available largely at http://schools.nyc.gov/Accountability/tools/report/default.htm This is a hacked-together prototype; it does not represent best practices.

ajschumacher

oh nothing, nothing...

ajschumacher

movie_reviews = dict()
for line in open('movies.txt.small'):
  pieces = line.split(':')
  if len(pieces) > 1:
    key = pieces[0]
    value = ':'.join(pieces[1:]).strip()
    if key == 'product/productId':
      id = value
    if key == 'review/text':
      movie_reviews.setdefault(id, []).append(value)

ajschumacher

set.seed(54)
n <- rnorm(3000,0.5,0.1)
par(mar=c(1,1,3,1))
hist(c(runif(10000),runif(1900,0.35,0.65),n[abs(n-0.5)<0.15]),
     xlim=c(0,1),ylim=c(0,600),breaks=51,ylab="",#main="",
     main="Statistical Programming DC",col="#C9242D",
     axes=F, cex.main=2)