The data this week comes from US DOT. An interactive map can be used at https://www.arcgis.com/home/webmap/viewer.html?panel=gallery&layers=cc51698ab9d94d67b4ec5dc5b8d97f34 with a short article from the EIA.
Hattip to Data is Plural for sharing this resource.
stations <- read_csv("stations.csv") %>%
janitor::clean_names() %>%
mutate(year = lubridate::year(as.Date(open_date))) %>%
mutate(decade = (year%/%10)*10)
text <- c("BD: Biodiesel (B20 and above)",
"CNG: Compressed Natural Gas",
"ELEC: Electric",
"E85: Ethanol",
"HY: Hydrogen",
"LNG: Liquefied Natural Gas",
"LPG: Propane")
text <- paste0(text, collapse = "\n")
text.df <- data.frame(text)
stations %>%
filter(!(state %in% c("AK", "HI", "ON", "PR"))) %>%
filter(!is.na(state)) %>%
filter(status_code == "E") %>% # station is available
filter(latdd > 22) %>% # seems like there are some outliers
ggplot(aes(color = fuel_type_code)) +
geom_point(aes(x = longdd, y = latdd), size = .5) +
facet_wrap(~fuel_type_code) +
gganimate::transition_time(year, range = c(1980, 2022)) +
gganimate::shadow_mark(past = T, future = T, alpha = 0.6) +
theme_void() +
theme(legend.position="none") +
labs(
title = "Evolution of alternative fuel stations over time",
caption = "Tidy Tuesday Plot: @hardin47 | Data: US DOT via Data is Plural")