I prefer to use jsonlite for parsing JSON in R.
To parse the nested JSON list, you can do the fromJSON call inside an lapply.
jsonlite::fromJSON tries to simplify the result for you. But, as JSON is designed to handle nested data structures, you're often returned a data.frame of lists, so to get the data.frame you're after, you need to know which element of the list you want, and extract it.
For example
library(RDSTK)
library(jsonlite)
js <- coordinates2politics(Coords$Latitude, Coords$Longitude)
lst <- lapply(js, jsonlite::fromJSON)
lst[[1]]$politics
# type friendly_type name code
# 1 admin2 country Canada can
# 2 admin4 state Ontario ca08
# 3 constituency constituency Hamilton Centre 35031
# 4 constituency constituency Burlington 35010
# 5 constituency constituency Hamilton East-Stoney Creek 35032
To get the data.frame, you can construct another lapply to extract the elements you want, and then put it altogether with either a do.call(..., rbind), or my preferences is with data.table::rbindlist(...)
lst_result <- lapply(lst, function(x){
df <- x$politics[[1]]
df$lat <- x$location$latitude
df$lon <- x$location$longitude
return(df)
})
data.table::rbindlist(lst_result)
# type friendly_type name code lat lon
# 1: admin2 country Canada can 43.30528 -79.80306
# 2: admin4 state Ontario ca08 43.30528 -79.80306
# 3: constituency constituency Hamilton Centre 35031 43.30528 -79.80306
# 4: constituency constituency Burlington 35010 43.30528 -79.80306
# 5: constituency constituency Hamilton East-Stoney Creek 35032 43.30528 -79.80306
# 6: admin2 country Canada can 46.08333 -82.41667
# 7: admin4 state Ontario ca08 46.08333 -82.41667
Alternatively, to get more detail about each lat/lon you can use Google's API through library(googleway) (Disclaimer: I wrote googleway) to reverse geocode the lat/lons.
For this you need a valid Google API key (which is limited to 2,500 requests per day, unless you pay)
library(googleway)
key <- "your_api_key"
lst <- apply(Coords, 1, function(x){
google_reverse_geocode(location = c(x["Latitude"], x["Longitude"]),
key = key)
})
lst[[1]]$results$address_components
# [[1]]
# long_name short_name types
# 1 Burlington Bay James N. Allan Skyway Burlington Bay James N. Allan Skyway route
# 2 Burlington Burlington locality, political
# 3 Halton Regional Municipality Halton Regional Municipality administrative_area_level_2, political
# 4 Ontario ON administrative_area_level_1, political
# 5 Canada CA country, political
# 6 L7S L7S postal_code, postal_code_prefix
Or similarly through library(ggmap), also limited by Google's 2,500 limit.
library(ggmap)
apply(Coords, 1, function(x){
revgeocode(c(x["Longitude"], x["Latitude"]))
})
# 1
# "Burlington Bay James N. Allan Skyway, Burlington, ON L7S, Canada"
# 2
# "308 Brennan Harbour Rd, Spanish, ON P0P 2A0, Canada"
# 3
# "724 Harris Ave, San Diego, CA 92154, USA"
# 4
# "30 Cherry St, Chinook, WA 98614, USA"
# 5
# "St James Township, MI, USA"
# 6
# "US-101, Chinook, WA 98614, USA"
# 7
# "2413 II Rd, Garden, MI 49835, USA"
# 8
# "2413 II Rd, Garden, MI 49835, USA"
# 9
# "8925 S Shore Rd, Stella, ON K0H 2S0, Canada"
# 10
# "Charlevoix County, MI, USA"
