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61 lines
2.2 KiB
61 lines
2.2 KiB
#' Reverse geocode up to 10,000 coordinates
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#'
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#' @md
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#' @param coordinates data frame of coordinates with `lat` and `lon` columns
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#' @param fields vector of additional fields to return with query results. Note that these
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#' count as extra lookups and impact your dailu quota/costs. See [the official documentation](https://geocod.io/docs/#fields)
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#' for more information on costs/pricing. Can be `cd`, `cd113`, `cd114`, or `cd115` for
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#' current or historical Congressional districts (U.S.); `stateleg` for State Legislative District (House & Senate, U.S.);
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#' `school` forSchool District (elementary/secondary or unified, U.S.); `census` for
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#' Census Block/Tract & FIPS codes (U.S.) or `timezone` for timezone.
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#' @param api_key `geocod.io` API key
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#' @export
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#' @examples
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#' data.frame(
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#' lat = c(35.9746000, 32.8793700, 33.8337100, 35.4171240),
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#' lon = c(-77.9658000, -96.6303900, -117.8362320, -80.6784760)
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#' ) -> to_code
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#' gio_batch_reverse(to_code)
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#' gio_batch_reverse(to_code, fields=c("census", "stateleg"))
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gio_batch_reverse <- function(coordinates, fields, api_key=gio_auth()) {
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if (nrow(coordinates) > 10000) {
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message("Too many addresses. Submitting first 10,000")
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coordinates <- coordinates[1:10000,]
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}
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if (!("lat" %in% colnames(coordinates))) {
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stop("coordinates data frame must have a 'lat' column")
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}
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if (!("lon" %in% colnames(coordinates))) {
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stop("coordinates data frame must have a 'lon' column")
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}
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pairs <- sprintf("%s,%s", coordinates$lat, coordinates$lon)
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params <- list(api_key=api_key)
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if (!missing(fields)) params$fields <- paste0(trimws(fields), collapse=",")
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res <- httr::POST("https://api.geocod.io/v1/reverse",
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query=params, body=as.list(pairs), encode="json")
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httr::stop_for_status(res)
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res <- jsonlite::fromJSON(httr::content(res, as="text", encoding = "UTF-8"),
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flatten = TRUE)
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res <- res$results$response.results
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res <- map_df(res, ~.)
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new_names <- gsub("\\.", "_", colnames(res))
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new_names <- gsub("response_input|address_components|fields", "", new_names)
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new_names <- gsub("[_]+", "_", new_names)
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new_names <- sub("^_", "", new_names)
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res <- set_names(res, new_names)
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as_tibble(res)
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}
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