I have read Batch Geocoding with googleway R
I am attempting to geocode some addresses using googleway. I want the geocodes, address, and county returned back.
Using the answer linked to above I created the following function.
geocodes<-lapply(seq_along(res),function(x) {
coordinates<-res[[x]]$results$geometry$location
df<-as.data.frame(unlist(res[[x]]$results$address_components))
address<-paste(df[1,],df[2,],sep = " ")
city<-paste0(df[3,])
county<-paste0(df[4,])
state<-paste0(df[5,])
zip<-paste0(df[7,])
coordinates<-cbind(coordinates,address,city,county,state,zip)
coordinates<-as.data.frame(coordinates)
})
Then put it back together like so...
library(data.table)
done<-rbindlist(geocodes))
The issue is getting the address and county back out from the 'res' list. The answer linked to above pulls the address from the dataframe that was sent to google and assumes the list is in the right order and there are no multiple match results back from google (in my list there seems to be a couple). Point is, taking the addresses from one file and the coordinates from another seems rather reckless and since I need the county anyway, I need a way to pull it out of google's resulting list saved in 'res'.
The issue is that some addresses have more "types" than others which means referencing by row as I did above does not work.
I also tried including rbindlist inside the function to convert the sublist into a datatable and then pull out the fields but can't quite get it to work. The issue with this approach is that actual addresses are in a vector but the 'types' field which I would use to filter or select is in a sublist.
The best way I can describe it is like this - list <- c(long address),c(short address), types(LIST(street number, route, county, etc.))
Obviously, I'm a beginner at this. I know there's a simpler way but I am just really struggling with lists and R seems to make extensive use of them.
Edit: I definitely recognize that I cannot rbind the whole list. I need to pull specific elements out and bind just those. A big part of the problem, in my mind, is that I do not have a great handle on indexing and manipulating lists.
Here are some addresses to try - "301 Adams St, Friendship, WI 53934, USA" has an 7X3 "address components" and corresponding "types" list of 7. Compare that to "222 S Walnut St, Appleton, WI 45911, USA" which has an address components of 9X3 and "types" list of 9. The types list needs to be connected back to the address components matrix because the types list identifies what each row of the address components matrix contains.
Then there are more complexities introduced by imperfect matches. Try "211 Grand Avenue, Rothschild, WI, 54474" and you get 2 lists, one for east grand ave and one for west grand ave. Google seems to prefer the east since that's what comes out in the "formatted address." I don't really care which is used since the county will be the same for either. The "location" interestingly contains 2 sets of geocodes which, presumably, refer to the two matches. I think this complexity can be ignored since the location consisting of two coordinates is still stored as a 'double' (not a list!) so it should stack with the coordinates for the other addresses.
Edit: This should really work but I'm getting an error in the do.call(rbind,types) line of the function.
geocodes<-lapply(seq_along(res),function(x) {
coordinates<-res[[x]]$results$geometry$location
types<-res[[x]]$results$address_components[[1]]$types
types<-do.call(rbind,types)
types<-types[,1]
address<-as.data.frame(res[[x]]$results$address_components[[1]]$long_name,strings.As.Factors=FALSE)
names(address)[1]<-"V2"
address<-cbind(address,types)
address<-tidyr::spread(address,types,V2)
address<-cbind(address,coordinates)
})
R says the "types" object is not a list so it can't rbind it. I tried coercing it to a list but still get the error. I checked using the following paired down function and found #294 is null. This halts the function. I get "over query limit" as an error but I am not over the query limit.
geocodes<-lapply(seq_along(res),function(x) {
types<-res[[x]]$results$address_components[[1]]$types
print(typeof(types))
})
Ok, I'll answer it myself.
Begin with a dataframe of addresses. I called mine "addresses" and the singular column in the dataframe is also called "Addresses" (note that I capitalized it).
Use googleway to get the geocode data. I did this using apply to loop across the rows in the address dataframe
library(googleway)
res<-apply(addresses,1,function (x){
google_geocode(address=x[['Address']], key='insert your google api key here - its free to get')
})
Here is the function I wrote to get the nested lists into a dataframe.
geocodes<-lapply(seq_along(res),function(x) {
coordinates<-res[[x]]$results$geometry$location
types<-res[[x]]$results$address_components[[1]]$types
types<-do.call(rbind,types)
types<-types[,1]
address<-as.data.frame(res[[x]]$results$address_components[[1]]$long_name,strings.As.Factors=FALSE)
names(address)[1]<-"V2"
address<-cbind(address,types)
address<-tidyr::spread(address,types,V2)
address<-cbind(address,coordinates)
})
library(data.table)
geocodes<-rbindlist(geocodes,fill=TRUE)
lapply loops along the items in the list, within the function I create a coordinates dataframe and put the geocodes there. I also wanted the other address components, particularly the county, so I also created the "types" dataframe which identifies what the items in the address are. I cbind the address items with the types, then use spread from the tidyr package to reshape the dataframe into wideformat so it's just 1 row wide. I then cbind in the lat and lon from the coordinates dataframe.
The rbindlist stacks it all back together. You could use do.call(rbind, geocodes) but rbindlist is faster.