Merge pull request #108 from nationalparkservice/sarah-dev

add documentation to generate_ll_from_utm

DESCRIPTION

@@ -59,7 +59,9 @@ Imports:
     tidyselect,
     glue,
     sp,
-    withr
+    withr,
+    cli,
+    purrr
 RoxygenNote: 7.3.1
 Suggests: 
     knitr,

NAMESPACE

@@ -20,6 +20,7 @@ export(get_taxon_rank)
 export(get_utm_zone)
 export(long2UTM)
 export(order_cols)
+export(removeEmptyTables)
 export(replace_blanks)
 export(te_check)
 export(utm_to_ll)

R/geography.R

@@ -353,6 +353,11 @@ fuzz_location <- function(lat,
 #' of your dataframe. Note that some parameter names are not in snake_case but
 #' instead reflect DarwinCore naming conventions.
 #'
+#' This function uses tidy evaluation (i.e. you can provide column name arguments
+#' as strings or you can leave them unquoted). If you wish to store column names
+#' as strings in variables, you must enclose the variables in double curly braces
+#' when you pass them into the function. See code examples below.
+#'
 #' @param df - The dataframe with UTM coordinates you would like to convert.
 #' Input the name of your dataframe.
 #' @param EastingCol - The name of your Easting UTM column. You may input the name
@@ -372,6 +377,7 @@ fuzz_location <- function(lat,
 #' @examples
 #' \dontrun{
 #'
+#' # Using magrittr pipe (%>%) and unquoted column names
 #' my_dataframe %>%
 #' generate_ll_from_utm(
 #'   EastingCol = UTM_X,
@@ -380,6 +386,7 @@ fuzz_location <- function(lat,
 #'   DatumCol = Datum
 #' )
 #'
+#' # Providing column names as strings (in quotes)
 #' generate_ll_from_utm(
 #'   df = mydataframe,
 #'   EastingCol = "EastingCoords",
@@ -388,6 +395,23 @@ fuzz_location <- function(lat,
 #'   DatumCol = "datum",
 #'   latlong_datum = "WGS84"
 #' )
+#'
+#' # Column names stored as strings in separate variables
+#' easting <- "EastingCoords"
+#' northing <- "NorthingCoords"
+#' zonecol <- "zone"
+#' datumcol <- "datum"
+#' latlong_dat <- "WGS84"
+#'
+#' generate_ll_from_utm(
+#'   df = mydataframe,
+#'   EastingCol = {{easting}},  # enclose variables that store column names in {{}}
+#'   NorthingCol = {{northing}},
+#'   ZoneCol = {{zonecol}},
+#'   DatumCol = {{datumcol}},
+#'   latlong_datum = latlong_dat  # this isn't a column name so it doesn't need {{}}
+#' )
+#'
 #' }
 generate_ll_from_utm <- function(df,
                               EastingCol,
@@ -404,12 +428,12 @@ generate_ll_from_utm <- function(df,
     dplyr::select(`_UTMJOINCOL`, {{EastingCol}}, {{NorthingCol}}, {{ZoneCol}}, {{DatumCol}})
 
   withr::with_envvar(c("PROJ_LIB" = ""), {  # This is a fix for the proj library bug in R (see pinned post "sf::st_read() of geojson not getting CRS" in IMData General Discussion).
-    # filter out rows that are missing UTM, zone, or datum
-    coord_df <- coord_df %>%
-      dplyr::filter(!is.na({{EastingCol}}) &
-                      !is.na({{NorthingCol}}) &
-                      !is.na({{ZoneCol}}) &
-                      !is.na({{DatumCol}}))
+      coord_df <- coord_df %>%
+        dplyr::filter(!is.na(!!rlang::ensym(EastingCol)) &
+                        !is.na(!!rlang::ensym(NorthingCol)) &
+                        !is.na(!!rlang::ensym(ZoneCol)) &
+                        !is.na(!!rlang::ensym(DatumCol)))
+
 
     na_row_count <- nrow(df) - nrow(coord_df)
     if (na_row_count > 0) {

R/remove_empty_tables.R

@@ -0,0 +1,26 @@
+#' Remove empty tables from a list
+#'
+#' @param df_list A list of tibbles or dataframes.
+#'
+#' @return The same list but with empty tables removed.
+#' @export
+#'
+#' @examples
+#'
+#' test_list <- list(item_a = tibble::tibble,
+#'                   item_b = mtcars,
+#'                   item_c = iris)
+#'
+#' tidy_list <- removeEmptyTables(test_list)
+#'
+removeEmptyTables <- function(df_list) {
+  non_empty_list <- purrr::compact(df_list)  # Remove empty dataframes
+  tables_removed <- setdiff(names(df_list), names(non_empty_list))  # Get names of removed dataframes
+
+  # Warn about removed empty dataframes
+  if (length(tables_removed) > 0) {
+    warning(cli::pluralize("{length(tables_removed)} empty table{?s} {?was/were} omitted from dataset. Affected table{?s}: {paste(tables_removed, collapse = ", ")}"))
+  }
+
+  return(non_empty_list)
+}