Add scratch.R file.

scratch.R

@@ -0,0 +1,45 @@
+library(readr)
+raw <- read_csv("data/alt_fuel_stations (Sep 25 2024)_joined.csv")
+
+library(tidyverse)
+dataset <- raw %>%
+  select(
+    `Station Name`, 
+    `City`, 
+    `EV Level2 EVSE Num`, 
+    `EV DC Fast Count`, 
+    `Latitude`, 
+    `Longitude`, 
+    `EV Connector Types`, 
+    `EV Workplace Charging`, 
+    `UR20`
+  )
+
+has_null_ur20 <- dataset %>%
+  summarise(any_null = any(is.na(UR20)))
+
+dataset <- dataset %>%
+  filter(!is.na(UR20)) %>% 
+  mutate(UR20 = recode(UR20, "R" = "Rural", "U" = "Urban"))
+
+library(ggplot2)
+library(scales)
+ggplot(dataset, aes(y = factor(UR20))) + 
+  geom_bar(aes(x = after_stat(count))) +
+  geom_text(stat = 'count', aes(label = comma(after_stat(count))),  # Use comma for thousands separators
+            position = position_stack(vjust = 0.5), 
+            color = "white") +  # Set label color to white
+  labs(title = "Urban-Rural Station Histogram",
+       x = "Classification",
+       y = "Count") +
+  theme_minimal()
+
+ggplot(dataset, aes(y = factor(UR20))) + 
+  geom_bar(aes(x = after_stat(count))) +
+  geom_text(stat = 'count', aes(label = comma(after_stat(count))),  # Use comma for thousands separators
+            position = position_stack(vjust = 0.5), 
+            color = "white") +  # Set label color to white
+  labs(title = "Urban-Rural Charger Histogram",
+       x = "Classification",
+       y = "Count") +
+  theme_minimal()