diff --git a/R/MilWALKeeWalks.Rmd b/R/MilWALKeeWalks.Rmd
index 3aba142..8d702bf 100644
--- a/R/MilWALKeeWalks.Rmd
+++ b/R/MilWALKeeWalks.Rmd
@@ -254,7 +254,9 @@ hex_crashes <- st_join(hexgrid,
 hex_crashes <- st_as_sf(left_join(hexgrid, hex_crashes), crs = 4326)
 
 hex_crashes <- hex_crashes %>%
-  mutate(lastyearchange = (lastyear - prior/yearsforprior)/(prior/yearsforprior))
+  mutate(prioryearlyaverage = prior/yearsforprior) %>%
+  mutate(lastyearchangepercent = (lastyear - prioryearlyaverage)/prioryearlyaverage,
+         lastyearchangecrashes = lastyear - prioryearlyaverage)
 
 hex_crashes_points <- st_centroid(hex_crashes)
 
@@ -289,7 +291,9 @@ hex_crashes_small <- st_join(hexgrid_small,
 hex_crashes_small <- st_as_sf(left_join(hexgrid_small, hex_crashes_small), crs = 4326)
 
 hex_crashes_small <- hex_crashes_small %>%
-  mutate(lastyearchange = (lastyear - prior/yearsforprior)/(prior/yearsforprior))
+  mutate(prioryearlyaverage = prior/yearsforprior) %>%
+  mutate(lastyearchangepercent = (lastyear - prioryearlyaverage)/prioryearlyaverage,
+         lastyearchangecrashes = lastyear - prioryearlyaverage)
 
 hex_crashes_small_points <- st_centroid(hex_crashes_small)
 
@@ -339,7 +343,7 @@ ggmap(basemap) +
   geom_sf(data = hex_crashes_points %>% filter(is.double(total), !is.na(total)),
           inherit.aes = FALSE,
           aes(size = total,
-              fill = lastyearchange),
+              fill = lastyearchangepercent),
           linewidth = 0,
           shape = 21,
           color = "black") +
@@ -379,9 +383,9 @@ ggmap(basemap) +
         axis.ticks=element_blank(),
         plot.caption = element_text(color = "grey", size = 8)) +
   # add crash locations
-  geom_sf(data = hex_crashes %>% mutate(lastyearchange = (lastyear - prior/yearsforprior)),
+  geom_sf(data = hex_crashes,
           inherit.aes = FALSE,
-          aes(fill = lastyearchange),
+          aes(fill = lastyearchangecrashes),
           alpha = 0.5) +
   scale_size_area() +
   scale_fill_gradient2(
@@ -389,7 +393,7 @@ ggmap(basemap) +
     mid = "white",
     high = "red",
     midpoint = 0,
-#    limits = c(-2, 2),
+#    limits = c(-20, 20),
 #    oob = scales::squish
   ) # + geom_sf(data = projects_2023, inherit.aes = FALSE)
 
@@ -429,11 +433,11 @@ ggmap(basemap) +
   # add crash locations
   geom_sf(data = hex_crashes %>% filter(ID %in% highlighted_areas),
           inherit.aes = FALSE,
-          aes(fill = lastyearchange),
+          aes(fill = lastyearchangepercent),
           alpha = 0.5) +
   geom_sf_text(data = hex_crashes_points %>% filter(ID %in% highlighted_areas),
                 inherit.aes = FALSE,
-                aes(label = paste0(ifelse(lastyearchange > 0, "+",""),round(lastyearchange * 100, 0), "%")),
+                aes(label = paste0(ifelse(lastyearchangepercent > 0, "+",""),round(lastyearchangepercent * 100, 0), "%")),
                size = 3) +
   scale_size_area() +
   scale_fill_gradient2(
@@ -482,11 +486,10 @@ ggmap(basemap) +
         plot.caption = element_text(color = "grey", size = 8)) +
 #add hexagons
   new_scale_fill() +
-  geom_sf(data = hex_crashes_small %>% 
-            mutate(lastyearchange = (lastyear - prior/yearsforprior)) %>%
-            filter(!is.na(lastyearchange)),
+  geom_sf(data = hex_crashes_small %>%
+            filter(!is.na(lastyearchangecrashes)),
           inherit.aes = FALSE,
-          aes(fill = lastyearchange),
+          aes(fill = lastyearchangecrashes),
           alpha = 0.5) +
   scale_size_area() +
   scale_fill_gradient2(
@@ -494,8 +497,8 @@ ggmap(basemap) +
     mid = "white",
     high = "red",
     midpoint = 0,
-#    limits = c(-2, 2),
-#    oob = scales::squish
+#    limits = c(-10, 10),
+#    oob = scales::squish,
   name = "Crashes last year\ncompared to previous average") +
   # add crash locations
   new_scale_fill() +
@@ -513,7 +516,7 @@ ggmap(basemap) +
                  fill = ped_inj_name),
              shape = 23,
              size = 3) +
-  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = paste0("Crashes ", previousyearstring))# + geom_sf(data = projects_2023, inherit.aes = FALSE)
+  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = paste0("Crashes ", previousyearstring)) + geom_sf(data = projects_2023, inherit.aes = FALSE)
 
 ggsave(file = paste0("figures/MilWALKee_Walks/",
                      "milwaukee_map_zoomchange.png"),
@@ -523,7 +526,89 @@ ggsave(file = paste0("figures/MilWALKee_Walks/",
        units = "in",
        create.dir = TRUE)
 
+##highland ave
 
+bbox <- c(left = -87.967, 
+          bottom = 43.043, 
+          right = -87.944, 
+          top = 43.051)
+basemap <- get_stadiamap(bbox = bbox, zoom = 15, maptype = "stamen_toner_lite")
+ggmap(basemap) +
+  labs(title = paste0("Crashes between cars and pedestrians"),
+    subtitle = paste0(str_to_title(focus_county),
+                      " County | ",
+                      min(year(TOPS_data$date), na.rm = TRUE), 
+                      " - ", 
+                      max(year(TOPS_data$date), na.rm = TRUE)),
+    caption = paste0("crash data from UW TOPS lab - retrieved ",
+                     strftime(retrieve_date, format = "%m/%Y"),
+                     "\nper direction of the WisDOT Bureau of Transportation Safety",
+                     "\nbasemap from StadiaMaps and OpenStreetMap Contributers"),
+    x = NULL,
+    y = NULL,
+    size = paste0("Total crashes"),
+    fill = paste0("last 12 months\ncompared to previous\n", yearsforprior, " years")) +
+  theme(axis.text=element_blank(),
+        axis.ticks=element_blank(),
+        plot.caption = element_text(color = "grey", size = 8)) +
+  # add crash locations
+  new_scale_fill() +
+  geom_point(data = TOPS_data_filtered %>% 
+               filter(year == 2025) %>%
+               #filter(ped_inj %in% c("K", "A", "B")) %>%
+               filter(vulnerable_role %in% "Pedestrian") %>%
+               filter(longitude >= as.double(bbox[1]),
+                      latitude >= as.double(bbox[2]),
+                      longitude <= as.double(bbox[3]),
+                      latitude <= as.double(bbox[4])) %>%
+               arrange(ped_inj_name),
+             aes(x = longitude,
+                 y = latitude,
+                 fill = ped_inj_name),
+             shape = 23,
+             size = 3) +
+  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = paste0("Crashes ", previousyearstring))
+
+bbox <- c(left = -87.910, 
+          bottom = 43.032, 
+          right = -87.896, 
+          top = 43.044)
+basemap <- get_stadiamap(bbox = bbox, zoom = 15, maptype = "stamen_toner_lite")
+ggmap(basemap) +
+  labs(title = paste0("Crashes between cars and pedestrians"),
+    subtitle = paste0(str_to_title(focus_county),
+                      " County | ",
+                      min(year(TOPS_data$date), na.rm = TRUE), 
+                      " - ", 
+                      max(year(TOPS_data$date), na.rm = TRUE)),
+    caption = paste0("crash data from UW TOPS lab - retrieved ",
+                     strftime(retrieve_date, format = "%m/%Y"),
+                     "\nper direction of the WisDOT Bureau of Transportation Safety",
+                     "\nbasemap from StadiaMaps and OpenStreetMap Contributers"),
+    x = NULL,
+    y = NULL,
+    size = paste0("Total crashes"),
+    fill = paste0("last 12 months\ncompared to previous\n", yearsforprior, " years")) +
+  theme(axis.text=element_blank(),
+        axis.ticks=element_blank(),
+        plot.caption = element_text(color = "grey", size = 8)) +
+  # add crash locations
+  new_scale_fill() +
+  geom_point(data = TOPS_data_filtered %>% 
+               filter(year != 2025) %>%
+               #filter(ped_inj %in% c("K", "A", "B")) %>%
+               filter(vulnerable_role %in% "Pedestrian") %>%
+               filter(longitude >= as.double(bbox[1]),
+                      latitude >= as.double(bbox[2]),
+                      longitude <= as.double(bbox[3]),
+                      latitude <= as.double(bbox[4])) %>%
+               arrange(ped_inj_name),
+             aes(x = longitude,
+                 y = latitude,
+                 fill = ped_inj_name),
+             shape = 23,
+             size = 3) +
+  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = paste0("Crashes ", previousyearstring))
 ```