diff --git a/Example_Use.R b/Example_Use.R
index 548ac955..588ac10a 100644
--- a/Example_Use.R
+++ b/Example_Use.R
@@ -9,15 +9,12 @@ historic <- historic_input(dbCon, thebb, period = "2001_2020")
 plot(historic[[1]][[2]])
 
 ##provide or create a long, lat, elev, and optionally id, dataframe - usually read from csv file
-in_xyz <- structure(list(Long = c(-127.70521, -127.62279, -127.56235, -127.7162, 
-## smaller example in BC
-                               -127.18585, -127.1254, -126.94957, -126.95507),
-                      Lat = c(55.3557, 55.38847, 55.28537, 55.25721, 54.88135, 54.65636, 54.6913, 54.61025),
-                      Elev = c(291L, 296L, 626L, 377L, 424L, 591L, 723L, 633L),
-                      ID = LETTERS[1:8],
-                      Zone = c(rep("CWH",3), rep("CDF",5)),
-                      Subzone = c("vm1","vm2","vs1",rep("mm",3),"dk","dc")),
-                 row.names = c(NA, -8L), class = "data.frame")
+in_xyz <- data.frame(Long = c(-127.70521, -127.62279, -127.56235, -127.7162, 
+                              -127.18585, -127.1254, -126.94957, -126.95507), 
+                     Lat = c(55.3557, 55.38847, 55.28537, 55.25721, 54.88135, 54.65636, 54.6913, 54.61025), 
+                     Elev = c(291L, 296L, 626L, 377L, 424L, 591L, 723L, 633L),
+                     Zone = c(rep("CWH",3), rep("CDF",5)),
+                     Subzone = c("vm1","vm2","vs1",rep("mm",3),"dk","dc")),
 
 ##show available variables:
 list_variables()
@@ -69,7 +66,7 @@ ggplot(res2[RUN != "ensembleMean",],aes(x = PERIOD, y = Tave01, col = RUN, group
 
 ##historic timeseries
 ds_results_hist <- climr_downscale(xyz = in_xyz, which_normal = "auto", 
-                                   gcm_models = c("ACCESS-ESM1-5"),
+                                   gcm_models = c("ACCESS-ESM1-5"), 
                                    gcm_hist_years = 1910:2010,
                                    historic_ts = 1910:2010,
                                    return_normal = FALSE,