Nothing
#' @title Create an empty known location table
#'
#' @description Creates an empty known location tibble with the following
#' columns of core metadata:
#'
#' \itemize{
#' \item{locationID}
#' \item{locationName}
#' \item{longitude}
#' \item{latitude}
#' \item{elevation}
#' \item{countryCode}
#' \item{stateCode}
#' \item{countyName}
#' \item{timezone}
#' \item{houseNumber}
#' \item{street}
#' \item{city}
#' \item{postalCode}
#' }
#'
#' @return Empty known location tibble with the specified metadata columns.
#'
#' @examples
#' library(MazamaLocationUtils)
#'
#' # Create an empty Tbl
#' emptyTbl <- table_initialize()
#' dplyr::glimpse(emptyTbl)
#'
#' @rdname table_initialize
#' @export
#' @importFrom MazamaCoreUtils stopIfNull
#' @importFrom dplyr tibble filter
#' @importFrom rlang .data
table_initialize <- function() {
# ----- Validate parameters --------------------------------------------------
# ----- Create empty tibble --------------------------------------------------
# Build up a tibble with a single record full of NAs
locationTbl <- dplyr::tibble(
"locationID" = as.character(NA),
"locationName" = as.character(NA),
"longitude" = as.numeric(NA),
"latitude" = as.numeric(NA),
"elevation" = as.numeric(NA),
"countryCode" = as.character(NA),
"stateCode" = as.character(NA),
"countyName" = as.character(NA),
"timezone" = as.character(NA),
"houseNumber" = as.character(NA),
"street" = as.character(NA),
"city" = as.character(NA),
"postalCode" = as.character(NA)
)
# Now search for an ID we won't find to end up with an empty tibble with
# the correct column names.
locationTbl <-
locationTbl %>%
dplyr::filter(.data$locationID == "Rumplestiltskin")
# ----- Return ---------------------------------------------------------------
return(locationTbl)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.