问题
I want to calculate the distance between approx. 100,000 different ZIP codes. I know about the mapdist
function in the ggmap
package
mapdist
works perfectly:
library(ggmap)
mapdist('Washington', 'New York', mode = 'driving')
# from to m km miles seconds minutes hours
# 1 Washington New York 366284 366.284 227.6089 13997 233.2833 3.888056
mapdist('20001', '10001', mode = 'driving')
# from to m km miles seconds minutes hours
# 1 20001 10001 363119 363.119 225.6421 13713 228.55 3.809167
However, mapdist
relies on the Google Geocoding API which is subject to a query limit of 2,500 geolocation requests per day.
Are you aware of any alternative r code to calculate the distance between two points using another service which has a higher request limit (such as Nokia Maps or Bing)?
回答1:
taRifx.geo::georoute
(only available here until I push out another update, at which point it will be available via install.packages
) can use Bing Maps (which supports I believe 25k per day) and can return a distance.
georoute( c("3817 Spruce St, Philadelphia, PA 19104",
"9000 Rockville Pike, Bethesda, Maryland 20892"),
verbose=TRUE, returntype="time",
service="bing" )
You'll have to get a Bing Maps API key and set it in your R global options (ideal placement is in .Rprofile
), but the key is free:
options(BingMapsKey="whateverBingGivesYouForYourKey")
回答2:
This might be trivial, but one completely free option is to use Census ZCTA geography data to get co-ordinates for each zip code, and then calculate Haversine distances (or some similar distance metric) between coordinates.
回答3:
If you start a new R session and run library(ggmap)
in the new session, you can make another 2500 queries.
Function distQueryCheck()
shows how many queries are remaining.
来源:https://stackoverflow.com/questions/17361909/determining-the-distance-between-two-zip-codes-alternatives-to-mapdist