决策树建模以及超漂亮的绘图

library(e1071)
modfit <- train(Species~.,method="rpart",data=training) 
library(rattle)
fancyRpartPlot(modfit$finalModel)

有经纬度计算两点之间的距离

library(geosphere)
dist=distHaversine(matrix(c(pickup_longitude, pickup_latitude), ncol = 2),
                   matrix(c(dropoff_longitude, dropoff_latitude), ncol = 2))

把经纬度数据变成zip code/neighborhood name

You can now do this directly within R itself thanks to the rather awesomeggmappackage.

Like others mention, you'll be reverse geocoding using the google maps API (and therefore limited to 2,500 queries daily), but it's as simple as:

library("ggmap")

# generate a single example address
lonlat_sample <- as.numeric(geocode("the hollyood bowl"))
lonlat_sample  # note the order is longitude, latitiude

res <- revgeocode(lonlat_sample, output="more")
# can then access zip and neighborhood where populated
res$postal_code
res$neighborhood

或

#Geocode:

getGeoCode <- function(gcStr)  {
  library("RJSONIO") #Load Library
  gcStr <- gsub(' ','%20',gcStr) #Encode URL Parameters
 #Open Connection
 connectStr <- paste('http://maps.google.com/maps/api/geocode/json?sensor=false&address=',gcStr, sep="") 
  con <- url(connectStr)
  data.json <- fromJSON(paste(readLines(con), collapse=""))
  close(con)
  #Flatten the received JSON
  data.json <- unlist(data.json)
  if(data.json["status"]=="OK")   {
    lat <- data.json["results.geometry.location.lat"]
    lng <- data.json["results.geometry.location.lng"]
    gcodes <- c(lat, lng)
    names(gcodes) <- c("Lat", "Lng")
    return (gcodes)
  }
}
geoCodes <- getGeoCode("Palo Alto,California")
> geoCodes
           Lat            Lng 
  "37.4418834" "-122.1430195" 

#Reverse Geocode:
reverseGeoCode <- function(latlng) {
latlngStr <-  gsub(' ','%20', paste(latlng, collapse=","))#Collapse and Encode URL Parameters
  library("RJSONIO") #Load Library
  #Open Connection
  connectStr <- paste('http://maps.google.com/maps/api/geocode/json?sensor=false&latlng=',latlngStr, sep="")
  con <- url(connectStr)
  data.json <- fromJSON(paste(readLines(con), collapse=""))
  close(con)
  #Flatten the received JSON
  data.json <- unlist(data.json)
  if(data.json["status"]=="OK")
    address <- data.json["results.formatted_address"]
  return (address)
}
address <- reverseGeoCode(c(37.4418834, -122.1430195))
> address
                    results.formatted_address 
"668 Coleridge Ave, Palo Alto, CA 94301, USA"