Load needed libraries

library(tidyverse)
library(janitor)       # cleans column names
library(USAboundaries) # Download shape files
library(sf)            # Used for spatial opperations
library(lubridate)
library(gganimate)

This data comes from https://data.ca.gov/dataset/alternative-fuel-station-locations/resource/843e18ca-7a96-4485-a9fe-1ecdd9bbb9b5

df <- read_csv('https://data.ca.gov/dataset/d2136de9-4b98-49f5-b076-022a046cd894/resource/843e18ca-7a96-4485-a9fe-1ecdd9bbb9b5/download/alternative-fuel-station-locations.csv') %>% 
  clean_names()


# get california shapefile from the USAboundaries package
cali <- us_states(resolution = "high", states = "CA")


# Clean up the gas station data and cast as a sf object
electric <- df %>% filter(fuel_type_code == "ELEC") %>% 
  filter(!str_detect(latitude, "[a-z]")) %>%
  mutate(longitude = as.numeric(longitude),
         latitude = as.numeric(latitude)) %>% 
  st_as_sf(coords=c("longitude","latitude"), crs=4326, remove=FALSE) %>% 
  mutate(open_date = mdy(open_date),
         year = year(open_date)) %>% 
  filter(!is.na(year))

in2 <- electric[cali,] # This filters for points inside of the california shape file

map <- ggplot(in2)+
  geom_sf(data = cali,
          fill = "grey30",
          color = "white")+
  geom_point(aes(x = in2$longitude, y = in2$latitude, group = seq_along(year)),
             shape = 21,
             color = "white",
             ldw = .5,
             fill = "purple") +
  labs(x = "",
       y = "") +
  theme_void() +
  theme(panel.background = element_rect(fill = "grey20"))

## Warning: Ignoring unknown parameters: ldw

map

map + transition_states(year)+
  labs(title = "Gas Stations With Electric Fueling Options {closest_state}")+
  shadow_mark(past = TRUE, alpha = .5) +
  enter_grow() +
  enter_fade()