CODEWITHSUNDEEP
rreverse-geocodingggmap
marine8115
marine8115

Reputation: 598

Loop for Reverse Geocoding in R

I am trying to reverse geocode a large data-set (around 100k). I used the revgeocode function from the package ggmap. I got the result for 1 entry

48 Grand View Terrace, San Francisco, 
CA 94114, USA            
48 Grand View Terrace Eureka Valley San Francisco        
San Francisco County                  California United States
postal_code postal_code_suffix

, but I need to automate the process and use it for the entire data-set.

I tried

r <- lapply(revgeocode(location = (c(z$lon),c(z$lat)),
             output = "more",
            messaging = FALSE, sensor = FALSE, override_limit = FALSE,
            client = "", signature = ""))

and got the errors for unexpected ',' in each step.

I tried to write the following loop too

r <- for(i in 1:10){
  revgeocode(location = ("z$lon", "z$lat"),output = "more", messaging =      FALSE, sensor = FALSE, override_limit = FALSE,client = "", signature = "")}

and got similar errors

Please provide some material or helpful links that will help me to write the loop for reverse geocoding. How to verify the authenticity of the data?

Upvotes: 11

Views: 6833

Answers (2)

pdx
pdx

Reputation: 301

I have had a similar problem for integrating the API key. Basically it is a matter of integrating the API key in the URL that R calls. If this doesn't help you, you need to change the core code (look it up on Github) to allow for an argument calling a key.

Upvotes: 0

Steven Beaupr&#233;
Steven Beaupr&#233;

Reputation: 21621

Based on this answer, you could create new variables in your data.frame

We use mapply() to process your coordinates and return the results in a list res. 

res <- mapply(FUN = function(lon, lat) { 
  revgeocode(c(lon, lat), output = "more") 
  }, 
  df$lon, df$lat
  )

Then, we use rbindlist() from data.table to convert the list into a data.frame (with fill = TRUE since not all elements of res have the same lenghts i.e. some results do not return a street_number and a postal_code) and cbind() it to the original data

cbind(df, data.table::rbindlist(res, fill = TRUE))

Update

Following up on your comment, if you want to process more than 2500 queries, you could subscribe to Google Maps APIs Premium Plan to unlock higher quotas. Then you can pass on your credentials to revgeocode() using the signature and client parameter.

As per mentionned in the documentation:

Upon purchasing your Google Maps APIs Premium Plan license, you will receive a welcome email from Google that contains your client ID and your private cryptographic key.

Your client ID is used to access the special features of Google Maps APIs Premium Plan. All client IDs begin with a gme- prefix. Pass your client ID as the value of the client parameter. A unique digital signature is generated using your private cryptographic key. Pass this signature as the value of the signature parameter.

You can see how it works under the hood by examining the revgeocode() source and see how the URL is constructed:

sensor4url <- paste("&sensor=", sensor, sep = "")
client4url <- paste("&client=", client, sep = "")
signature4url <- paste("&signature=", signature, sep = "")
url_string <- paste("http://maps.googleapis.com/maps/api/geocode/json?latlng=", 
        loc4url, sensor4url, sep = "")
    if (userType == "business") {
        url_string <- paste(url_string, client4url, signature4url, 
            sep = "")
    }

Data

df <- structure(list(lat = c(32.31, 32.19, 34.75, 35.09, 35.35, 34.74 ), lon = 
c(119.827, 119.637, 119.381, 119.364, 119.534, 119.421 )), .Names = 
c("lat", "lon"), row.names = c(21L, 32L, 37L, 48L, 50L, 89L), class = "data.frame")

Upvotes: 8

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