From cf85f8b2a86a632543bb898766cd740e97387ffa Mon Sep 17 00:00:00 2001
From: Ben Varick <ben@dendroalsia.net>
Date: Wed, 24 Sep 2025 12:06:57 -0700
Subject: [PATCH] added cumulative crash graph

---
 R/MilWALKeeWalks.Rmd | 79 +++++++++++++++++++++++++++++++++++++++-----
 1 file changed, 71 insertions(+), 8 deletions(-)

diff --git a/R/MilWALKeeWalks.Rmd b/R/MilWALKeeWalks.Rmd
index 8d702bf..0f1a421 100644
--- a/R/MilWALKeeWalks.Rmd
+++ b/R/MilWALKeeWalks.Rmd
@@ -27,10 +27,7 @@ library(ggnewscale)
 library(RColorBrewer)
 library(magick)
 library(rsvg)
-library(parallel)
 library(tidycensus)
-library(MASS)
-library(raster)
 ```
 
 
@@ -145,7 +142,8 @@ ggsave(filename = paste0("figures/MilWALKee_Walks/", "month_age.png"),
        create.dir = TRUE)
 
 ggplot(data = TOPS_data_filtered %>%
-  filter(vulnerable_role == "Pedestrian",
+  filter(
+    #vulnerable_role == "Pedestrian",
          month(date) <= 8,
          ) %>%
 #    filter(ped_age < 18,
@@ -156,7 +154,7 @@ ggplot(data = TOPS_data_filtered %>%
                y = total),
            fill = "lightblue4") +
   scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
-  labs(title = paste0("Crashes involved pedestrians"),
+  labs(title = paste0("Crashes involved pedestrians & bicyclists"),
        subtitle = paste0(str_to_title(focus_county), " County | ", "January - August"),
        x = NULL,
        y = "Crashes per year",
@@ -164,7 +162,7 @@ ggplot(data = TOPS_data_filtered %>%
                         strftime(retrieve_date, format = "%m/%Y"),
                         "\nper direction of the WisDOT Bureau of Transportation Safety")) +
       theme(plot.caption = element_text(color = "grey"))
-ggsave(filename = paste0("figures/MilWALKee_Walks/", "ped_years.png"),
+ggsave(filename = paste0("figures/MilWALKee_Walks/", "vuln_years.png"),
        device = png,
        height = 8.5,
        width = 11,
@@ -172,7 +170,38 @@ ggsave(filename = paste0("figures/MilWALKee_Walks/", "ped_years.png"),
        create.dir = TRUE)
 
 ggplot(data = TOPS_data_filtered %>%
-         filter(vulnerable_role == "Pedestrian",
+  filter(
+    #vulnerable_role == "Pedestrian",
+         month(date) <= 8,
+         ped_inj %in% c("K", "A"),
+         ) %>%
+  group_by(year, ped_inj_name) %>% 
+  summarize(total = n())) +
+  geom_col(aes(x = year,
+               y = total,
+               fill = ped_inj_name),
+           position = position_dodge()) +
+  scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
+  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = "Injury severity") +
+labs(title = paste0("Crashes involved pedestrians & bicyclists - fatal and serious injuries"),
+     subtitle = paste0(str_to_title(focus_county), " County | ", "January - August"),
+     x = NULL,
+     y = "Crashes per year",
+     caption = paste0("crash data from UW TOPS lab - retrieved ",
+                      strftime(retrieve_date, format = "%m/%Y"),
+                      "\nper direction of the WisDOT Bureau of Transportation Safety")) +
+      theme(plot.caption = element_text(color = "grey"))
+ggsave(filename = paste0("figures/MilWALKee_Walks/", "vuln_years_severe.png"),
+       device = png,
+       height = 8.5,
+       width = 11,
+       units = "in",
+       create.dir = TRUE)
+
+ggplot(data = TOPS_data_filtered %>%
+         filter(
+           #vulnerable_role == "Pedestrian",
+           ped_inj %in% c("K", "A"),
                 month(date) <= 8) %>%
          mutate(mke_city = factor(ifelse(MUNINAME %in% "MILWAUKEE", "City of Milwaukee", "Other municipalities"),
                                   levels = c("Other municipalities", "City of Milwaukee"))) %>%
@@ -183,7 +212,7 @@ ggplot(data = TOPS_data_filtered %>%
                fill = mke_city),
            position = position_dodge()) +
   scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
-  labs(title = paste0("Crashes involved pedestrians"),
+  labs(title = paste0("Crashes involved pedestrians - fatal and severe injuries"),
        subtitle = paste0(str_to_title(focus_county), " County | ", "January - August"),
        x = NULL,
        y = "Crashes",
@@ -199,6 +228,40 @@ ggsave(filename = paste0("figures/MilWALKee_Walks/", "ped_years_MKEcity.png"),
        units = "in",
        create.dir = TRUE)
 
+ggplot(data = TOPS_data_filtered %>%
+  filter(
+    #vulnerable_role == "Pedestrian",
+      #   month(date) <= 8,
+         ped_inj %in% c("K", "A"),
+         ) %>%
+  group_by(year, month) %>% 
+  summarize(total = n()) %>%
+    arrange(year, month) %>%
+    group_by(year) %>%
+    mutate(cumcrashes = cumsum(total))) +
+  geom_line(aes(x = month,
+               y = cumcrashes,
+               group = year,
+               color = year)) +
+  scale_y_continuous(expand = expansion(mult = c(0,0.1))) +
+  scale_color_brewer(palette = "Set1") +
+  scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = "Injury severity") +
+labs(title = paste0("Crashes involved pedestrians & bicyclists - fatal and serious injuries"),
+     subtitle = paste0(str_to_title(focus_county), " County"),
+     x = NULL,
+     y = "Cumulative crashes",
+     color = NULL,
+     caption = paste0("crash data from UW TOPS lab - retrieved ",
+                      strftime(retrieve_date, format = "%m/%Y"),
+                      "\nper direction of the WisDOT Bureau of Transportation Safety")) +
+      theme(plot.caption = element_text(color = "grey"))
+ggsave(filename = paste0("figures/MilWALKee_Walks/", "vuln_years_cumulative_severe.png"),
+       device = png,
+       height = 8.5,
+       width = 11,
+       units = "in",
+       create.dir = TRUE)
+
 ```
 
 ## Milwaukee maps