R/nest_locations.R

In weed: Wrangler for Emergency Events Database

#' Nest Location Data into a column of Tibbles
#'
#' @param . Locationized data frame (see ``weed::split_locations``)
#' @param key_column Column name for Column that uniquely IDs each observation
#' @param columns_to_nest Column names for Columns to nest inside the mini-dataframes
#' @param keep_nested_cols Boolean to Keep the nested columns externally or not.
#'
#' @return Data Frame with A column of data frames
#' @export
#'
#' @examples
#' d <- tibble::tribble(
#' ~value,  ~location_word,                    ~Country,    ~lat,   ~lng,
#' "city of new york","new york","USA",  c(40.71427, 40.6501),   c(-74.00597, -73.94958),
#' "kerala", "kerala", "India",c(10.41667, 8.4855), c(76.5, 76.94924),
#' "chennai municipality","chennai","India", c(13.08784, 12.98833),c(80.27847, 80.16578),
#' "san francisco", "san francisco","USA", c(37.77493, 37.33939), c(-122.41942, -121.89496))
#' nest_locations(d, key_column = "value")
#'
#' @importFrom magrittr %>%
nest_locations <- function(.,
                           key_column = "Dis No",
                           columns_to_nest = c("location_word","lat","lng"),
                           keep_nested_cols = FALSE) {
  df <- .

  naming_func <- function(argument) {
    return(key_column)
  }

  bud <- df %>%
    dplyr::select(c(columns_to_nest,key_column)) %>%
    dplyr::group_nest(get(key_column)) %>%
    dplyr::rename_with(.fn = naming_func, .cols = "get(key_column)")
  joint <- df %>%
    dplyr::left_join(y = bud, by = key_column) %>%
    dplyr::rename("location_data" = "data")
  if (keep_nested_cols) {
    return(joint)
  }
  else {
    joint %>%
      dplyr::select(!columns_to_nest) %>%
      return()
  }
}