## ----message=F, warning=FALSE------------------------------------------------- library(dplyr) library(ggplot2) library(tidyr) library(rfars) ## ----include=FALSE------------------------------------------------------------ knitr::opts_chunk$set(fig.width = 7, fig.height = 5) ## ----results='asis'----------------------------------------------------------- knitr::kable(rfars::annual_counts, format = "html") ## ----fig.width = 7, fig.height=3---------------------------------------------- rfars::annual_counts %>% filter(what == "crashes", involved == "any") %>% ggplot(aes(x=year, y=n)) + geom_col() + facet_wrap(.~source, nrow=1, scales = "free_y") + labs(title = "Total annual crashes by type (FARS = fatal, CRSS = general)", x=NULL, y=NULL) + theme_minimal() ## ----------------------------------------------------------------------------- rfars::annual_counts %>% filter(source=="FARS", involved != "any") %>% ggplot(aes(x=year, y=n)) + geom_col() + facet_wrap(.~involved, scales = "free_y") + labs(title = "Annual fatal crashes by factor involved", subtitle = "Derived from FARS data files", x=NULL, y=NULL) + theme_minimal() + theme(plot.title.position = "plot") rfars::annual_counts %>% filter(source=="CRSS", involved != "any") %>% ggplot(aes(x=year, y=n)) + geom_col() + facet_wrap(.~involved, scales = "free_y") + labs(title = "Annual crashes of all severity levels by factor involved", subtitle = "Derived from CRSS data files", x=NULL, y=NULL) + theme_minimal() + theme(plot.title.position = "plot") ## ----message=FALSE, eval=F---------------------------------------------------- # myFARS <- get_fars(years = 2019:2023, proceed = T, states = "VA") ## ----include=FALSE------------------------------------------------------------ vignette_data <- rfars:::vignette_data ## ----results='asis', eval=FALSE----------------------------------------------- # my_counts <- counts( # df = myFARS, # where = list(states = "VA"), # what = "crashes", # interval = c("year", "month") # ) ## ----echo=FALSE--------------------------------------------------------------- my_counts <- vignette_data$counts_1 ## ----------------------------------------------------------------------------- knitr::kable(my_counts, format = "html") ## ----------------------------------------------------------------------------- my_counts %>% mutate_at("year", factor) %>% ggplot(aes(x=month, y=n, group=year, color=year, label=scales::comma(n))) + geom_line(linewidth = 1.5, alpha=.9) + scale_color_brewer() + labs(x=NULL, y=NULL, title = "Fatal Crashes in Virginia") + theme(plot.title.position = "plot") my_counts %>% mutate(date = lubridate::make_date(year, month)) %>% ggplot(aes(x=date, y=n, label=scales::comma(n))) + geom_col() + labs(x=NULL, y=NULL, title = "Fatal Crashes in Virginia") + theme(plot.title.position = "plot") ## ----results='asis', eval=FALSE----------------------------------------------- # counts( # myFARS, # where = list(states = "VA"), # what = "fatalities", # interval = c("year") # ) %>% # knitr::kable(format = "html") ## ----results='asis', echo=FALSE----------------------------------------------- vignette_data$counts_2 %>% knitr::kable(format = "html") ## ----results='asis', eval=FALSE----------------------------------------------- # counts( # df = myFARS, # where = list(states = "VA"), # what = "fatalities", # interval = c("year"), # involved = "speeding" # ) %>% # knitr::kable(format = "html") ## ----results='asis', echo=FALSE----------------------------------------------- vignette_data$counts_3 %>% knitr::kable(format = "html") ## ----results='asis', eval=FALSE----------------------------------------------- # counts( # myFARS, # where = list(states = "VA", urb="rural"), # what = "fatalities", # interval = c("year"), # involved = "speeding" # ) %>% # knitr::kable(format = "html") ## ----results='asis', echo=FALSE----------------------------------------------- vignette_data$counts_4 %>% knitr::kable(format = "html") ## ----results='asis', eval=FALSE----------------------------------------------- # counts( # df = myFARS, # where = list(states = "VA"), # what = "crashes", # interval = "year", # involved = "each" # ) %>% # pivot_wider(names_from = "year", values_from = "n") %>% # arrange(desc(`2023`)) %>% # knitr::kable(format = "html") ## ----results='asis', echo=FALSE----------------------------------------------- vignette_data$counts_5 %>% pivot_wider(names_from = "year", values_from = "n") %>% arrange(desc(`2023`)) %>% knitr::kable(format = "html") ## ----eval=FALSE--------------------------------------------------------------- # compare_counts( # df = myFARS, # interval = "year", # involved = "speeding", # what = "fatalities", # where = list(states = "VA", urb="rural"), # where2 = list(states = "VA", urb="urban") # ) %>% # ggplot(aes(x=factor(year), y=n, label=scales::comma(n))) + # geom_col() + # geom_label(vjust=1.2) + # facet_wrap(.~urb) + # labs(x=NULL, y=NULL, title = "Speeding-Related Fatalities in Virginia", fill=NULL) ## ----echo=FALSE--------------------------------------------------------------- vignette_data$counts_6 %>% ggplot(aes(x=factor(year), y=n, label=scales::comma(n))) + geom_col() + geom_label(vjust=1.2) + facet_wrap(.~urb) + labs(x=NULL, y=NULL, title = "Speeding-Related Fatalities in Virginia", fill=NULL) ## ----eval=FALSE--------------------------------------------------------------- # compare_counts( # df = myFARS, # where = list(states = "VA"), # interval = "year", # involved = "speeding", # involved2 = "distracted driver", # what = "crashes", # ) %>% # ggplot(aes(x=factor(year), y=n, label=scales::comma(n))) + # geom_col() + # geom_label(vjust=1.2) + # facet_wrap(.~involved) + # labs(x=NULL, y=NULL, title = "Speeding- and Distraction-Related Crashes in Virginia", fill=NULL) ## ----echo=FALSE--------------------------------------------------------------- vignette_data$counts_7 %>% ggplot(aes(x=factor(year), y=n, label=scales::comma(n))) + geom_col() + geom_label(vjust=1.2) + facet_wrap(.~involved) + labs(x=NULL, y=NULL, title = "Speeding- and Distraction-Related Crashes in Virginia", fill=NULL)