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prep_fars.R
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prep_fars.R
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#' Prepare downloaded FARS files for use
#'
#' @param y year, to be passed from \code{prep_fars}
#' @param wd working directory, , to be passed from \code{prep_fars}
#' @param rawfiles dataframe translating filenames into standard terms,
#' to be passed from \code{prep_fars}
#' @param prepared_dir the location where prepared files will be saved,
#' to be passed from \code{prep_fars}
#' @param states (Optional) Inherits from get_fars()
#'
#' @return Produces six files: yyyy_flat.rds, yyyy_multi_acc.rds,
#' yyyy_multi_veh.rds, yyyy_multi_per.rds, yyyy_events.rds, and codebook.rds
#'
#' @importFrom rlang .data
prep_fars <- function(y, wd, rawfiles, prepared_dir, states){
cat("Preparing raw data files...\n")
# Setup
fars.accident <- fars.vehicle <- fars.person <- NULL
fars.vsoe <- fars.distract <- fars.drimpair <- fars.factor <-
fars.maneuver <- fars.violatn <- fars.vision <- fars.damage <- fars.vehiclesf <-
fars.pvehiclesf <- fars.driverrf <- fars.pbtype <- NULL
fars.nmcrash <- fars.nmimpair <- fars.nmprior <- fars.nmdistract <-
fars.drugs <- fars.race <- fars.personrf <- NULL
my_catfile <-
data.frame(filename = list.files(wd, recursive = T, full.names = T)) %>%
filter(stringr::str_detect(.data$filename, "sas7bcat")) %>%
arrange(desc(.data$filename)) %>%
slice(1) %>%
as.character()
# if(y %in% 2016:2021) my_catfile <- paste0(wd, "format-64/formats.sas7bcat")
# if(y %in% c(2011, 2014:2015)) my_catfile <- paste0(wd, "formats.sas7bcat")
if(y %in% 2021:2022) my_catfile <- paste0(wd, "format-viya/formats.sas7bcat")
if(y %in% 2012:2013) my_catfile <- FALSE
if(!is.null(states)){
geo_filtered <-
rfars::geo_relations %>%
filter(.data$fips_state %in% states | .data$state_name_abbr %in% states | .data$state_name_full %in% states)
} else{
geo_filtered <- rfars::geo_relations
}
# Core files ----
## accident ----
if(y %in% 2015:2022){
fars.accident <-
read_basic_sas(x = "accident", wd = wd, rawfiles = rawfiles, catfile = my_catfile) %>%
dplyr::distinct()
}
if(y %in% 2011:2014){
fars.accident <-
read_basic_sas(x = "accident", wd = wd, rawfiles = rawfiles, catfile = my_catfile) %>%
dplyr::distinct() %>%
mutate(rur_urb = case_when(
grepl("Rural", .data$road_fnc) ~ "Rural",
grepl("Urban", .data$road_fnc) ~ "Urban",
TRUE ~ as.character(NA)))
}
cat(paste0("\u2713 ", "Accident file processed\n"))
## vehicle ----
fars.vehicle <-
read_basic_sas(
x = "vehicle",
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident))
) %>%
select(-starts_with("vin_")) %>%
dplyr::distinct()
cat(paste0("\u2713 ", "Vehicle file processed\n"))
## person ----
fars.person <-
read_basic_sas(
x = "person",
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident), names(fars.vehicle))
) %>%
dplyr::distinct()
cat(paste0("\u2713 ", "Person file processed\n"))
# Accident-level files ----
## weather ----
if(y %in% 2020:2022){
fars.weather <- read_basic_sas(x = "weather", wd = wd, rawfiles = rawfiles, catfile = my_catfile)
} else{
fars.weather <- select(fars.accident, "state", "st_case", "weather1", "weather2")
}
fars.accident <- select(fars.accident, -contains("weather"))
cat(paste0("\u2713 ", "Weather file(s) processed\n"))
## crashrf ----
if(y %in% 2020:2022){
fars.crashrf <- read_basic_sas(x = "crashrf", wd = wd, rawfiles = rawfiles, catfile = my_catfile)
} else{
fars.crashrf <- select(fars.accident, "state", "st_case", "cf1", "cf2", "cf3")
}
fars.accident <- select(fars.accident, -any_of(c("cf1", "cf2", "cf3")))
cat(paste0("\u2713 ", "Crash risk factors file processed\n"))
# Vehicle-level files ----
for(i in c("vsoe",
"distract",
"drimpair",
"factor",
"maneuver",
"violatn",
"vision",
"damage",
"vehiclesf",
"pvehiclesf", #starts in 2020
"driverrf")){
if(i %in% rawfiles$cleaned){
assign(
paste0("fars.", i),
read_basic_sas(
x = i,
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident), names(fars.vehicle))
)
)
}
}
cat(paste0("\u2713 ", "Vehicle-level files processed\n"))
### driverrf ----
if(y %in% 2011:2019){
fars.driverrf <- select(fars.vehicle, "state", "st_case", "veh_no", "dr_sf1", "dr_sf2", "dr_sf3", "dr_sf4")
fars.vehicle <- select(fars.vehicle, -any_of(c("dr_sf1", "dr_sf2", "dr_sf3", "dr_sf4")))
cat(paste0("\u2713 ", "Driver risk factor file processed\n"))
}
### vehiclesf ----
if(y %in% 2011:2019){
fars.vehiclesf <- select(fars.vehicle, "state", "st_case", "veh_no", "veh_sc1", "veh_sc2")
fars.vehicle <- select(fars.vehicle, -any_of(c("veh_sc1", "veh_sc2")))
cat(paste0("\u2713 ", "Vehicle risk factor file processed\n"))
}
# Person-level files ----
## pbtype ----
if(y %in% 2014:2022){
fars.pbtype <-
read_basic_sas(
x = "pbtype",
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident), names(fars.vehicle))
) %>%
select(-any_of(c("pbptype", "pbage", "pbsex")))
cat(paste0("\u2713 ", "PBtype file processed\n"))
}
## safetyeq ----
if(y %in% 2011:2022){
fars.safetyeq <-
read_basic_sas(
x = "safetyeq",
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident), names(fars.vehicle))
)
cat(paste0("\u2713 ", "SafetyEq file processed\n"))
}
## personrf ----
if(y %in% 2011:2019){
fars.personrf <- select(fars.person, "state", "st_case", "veh_no", "per_no", "p_sf1", "p_sf2", "p_sf3")
fars.person <- select(fars.person, -any_of(c("p_sf1", "p_sf2", "p_sf3")))
cat(paste0("\u2713 ", "Person risk factor file processed\n"))
}
## drugs ----
if(y %in% 2011:2017){
fars.drugs <- select(fars.person, "state", "st_case", "veh_no", "per_no", "drugtst1", "drugtst2", "drugtst3", "drugres1", "drugres2", "drugres3")
fars.person <- select(fars.person, -any_of(c("drugtst1", "drugtst2", "drugtst3", "drugres1", "drugres2", "drugres3")))
cat(paste0("\u2713 ", "Drugs file processed\n"))
}
## multi-row files ----
for(i in c("nmcrash",
"nmimpair",
"nmprior",
"nmdistract", #starts in 2019
"drugs",
"race",
"personrf"
)){
if(i %in% rawfiles$cleaned){
assign(
paste0("fars.", i),
read_basic_sas(
x = i,
wd = wd,
rawfiles = rawfiles,
catfile = my_catfile,
omits = c(names(fars.accident), names(fars.vehicle))
)
)
}
}
cat(paste0("\u2713 ", "Person-level files processed\n"))
# Produce flat file ----
if(is.null(states)){
flat <- fars.accident
} else{
flat <- filter(fars.accident,
.data$state %in% unique(geo_filtered$state_name_full) |
.data$state %in% unique(geo_filtered$state_name_abbr) |
.data$state %in% unique(geo_filtered$fips_state)
)
}
flat <- flat %>%
left_join(fars.person, by = c("state", "st_case")) %>% #! This order (accident >> person >> vehicle) is very important for including non-motorists
left_join(fars.vehicle, by = c("state", "st_case", "veh_no"))
if(!is.null(fars.pbtype)) flat <- left_join(flat, fars.pbtype, by = c("state", "st_case", "veh_no", "per_no"))
if(!is.null(fars.safetyeq)) flat <- left_join(flat, fars.safetyeq, by = c("state", "st_case", "veh_no", "per_no"))
names_flat <-
janitor::make_clean_names(names(flat)) %>%
setdiff(c("year", "casenum", "state", "st_case", "veh_no", "per_no", "weight", "psu", "psustrat", "region", "stratum", "pj")) %>%
sort()
flat <-
as.data.frame(flat) %>%
mutate(id = paste0(.data$year, .data$st_case)) %>% # Generate state-independent id for each crash
mutate_at(c("year", "st_case"), as.numeric) %>%
select("year", "state", "st_case",
"id", "veh_no", "per_no",
"county", "city",
lon = "longitud",
lat = "latitude",
any_of(names_flat)
)
cat(paste0("\u2713 ", "Flat file constructed\n"))
# Concatenate long files for multi-row files ----
## Accident-level ----
multi_acc <-
bind_rows(
fars.weather %>% mutate_all(as.character) %>% pivot_longer(cols = -c(1:2)),
fars.crashrf %>% mutate_all(as.character) %>% pivot_longer(cols = -c(1:2))
) %>%
as.data.frame() %>%
filter(!(.data$value %in% c("None", "Unknown", "Not Reported", "No Additional Atmospheric Conditions"))) %>%
mutate(year = y) %>%
mutate_at(c("st_case", "year"), as.numeric) %>%
inner_join(select(flat, "st_case", "year") %>% distinct(), by = c("st_case", "year"))
cat(paste0("\u2713 ", "Multi_acc file constructed\n"))
## Vehicle-level ----
multi_veh <- fars.vehiclesf %>% mutate_all(as.character) %>% pivot_longer(cols = -c(1:3))
for(i in list(fars.driverrf,
fars.drimpair,
fars.distract,
fars.factor,
fars.maneuver,
fars.pvehiclesf,
fars.violatn,
fars.vision,
fars.damage)){
if(!is.null(i)) multi_veh <- bind_rows(multi_veh, mutate_all(i, as.character) %>% pivot_longer(cols = -c(1:3)))
}
multi_veh <-
as.data.frame(multi_veh) %>%
filter(!(.data$value %in% c("None", "Unknown", "Not Reported"))) %>%
mutate(year = y) %>%
mutate_at(c("st_case", "year"), as.numeric) %>%
inner_join(select(flat, "st_case", "year") %>% distinct(), by = c("st_case", "year"))
cat(paste0("\u2713 ", "Multi_veh file constructed\n"))
## Person-level ----
multi_per <- fars.personrf %>% mutate_all(as.character) %>% pivot_longer(cols = -c(1:4))
for(i in list(fars.race,
fars.drugs,
fars.nmcrash,
fars.nmimpair,
fars.nmprior,
fars.nmdistract
)){
if(!is.null(i)){
multi_per <- bind_rows(multi_per, mutate_all(i, as.character) %>% pivot_longer(cols = -c(1:4)))
}
}
multi_per <-
as.data.frame(multi_per) %>%
filter(!(.data$value %in% c("None", "Unknown", "Not Reported"))) %>%
mutate(year = y) %>%
mutate_at(c("st_case", "year"), as.numeric) %>%
inner_join(select(flat, "st_case", "year") %>% distinct(), by = c("st_case", "year"))
cat(paste0("\u2713 ", "Multi_per file constructed\n"))
## Events ----
soe <-
as.data.frame(fars.vsoe) %>%
mutate(year = y) %>%
mutate_at(c("st_case", "year"), as.numeric) %>%
inner_join(select(flat, "st_case", "year") %>% distinct(), by = c("st_case", "year"))
cat(paste0("\u2713 ", "SOE file constructed\n"))
# return ----
saveRDS(flat, paste0(prepared_dir, "/", y, "_flat.rds"))
saveRDS(multi_acc, paste0(prepared_dir, "/", y, "_multi_acc.rds"))
saveRDS(multi_veh, paste0(prepared_dir, "/", y, "_multi_veh.rds"))
saveRDS(multi_per, paste0(prepared_dir, "/", y, "_multi_per.rds"))
saveRDS(soe, paste0(prepared_dir, "/", y, "_events.rds"))
cat(paste0("\u2713 ", "Prepared files saved in ", prepared_dir, y, "\n"))
}