The goal of rfars is to facilitate transportation safety
analysis by simplifying the process of extracting data from official
crash databases. The National Highway
Traffic Safety Administration collects and publishes a census of
fatal crashes in the Fatality
Analysis Reporting System and a sample of fatal and non-fatal
crashes in the Crash
Report Sampling System (an evolution of the General
Estimates System). The Fatality
and Injury Reporting System Tool allows users to query these
databases, and can produce simple tables and graphs. This suffices for
simple analysis, but often leaves researchers wanting more. Digging any
deeper, however, involves a time-consuming process of downloading annual
ZIP files and attempting to stitch them together - after first combing
through immense data dictionaries to determine the required variables
and table names.
rfars allows users to download the last 10 years of FARS
and GES/CRSS data with just one line of code. The result is a full, rich
dataset ready for mapping, modeling, and other downstream analysis.
Codebooks with variable definitions and value labels support an informed
analysis of the data (see
vignette("Searchable Codebooks", package = "rfars") for
more information). Helper functions are also provided to produce common
counts and comparisons.
You can install the latest version of rfars from GitHub with:
# install.packages("devtools")
devtools::install_github("s87jackson/rfars")or the CRAN stable release with:
install.packages("rfars")Then load rfars and some helpful packages:
library(rfars)
library(dplyr)The get_fars() and get_gescrss() are the
primary functions of the rfars package. These functions
download and process data files directly from NHTSA’s
FTP Site, or pull the prepared data stored on your local machine, or
(as of Version 2.0) pull the prepared data from Zenodo. The data files
hosted on Zenodo are stable, have DOIs, and replicate the data that
would be produced by get_fars() and
get_gescrss(), but in a fraction of the time.
They take the parameters years and states
(FARS) or regions (GES/CRSS). As the source data files
follow an annual structure, years determines how many file
sets are downloaded or loaded, and
states/regions filters the resulting dataset.
Downloading and processing these files can take several minutes. Before
downloading, rfars will inform you that it’s about to
download files and asks your permission to do so. To skip this dialog,
set proceed = TRUE. You can use the dir and
cache parameters to save an RDS file to your local machine.
The dir parameter specifies the directory, and
cache names the file (be sure to include the .rds file
extension).
Executing the code below will download the prepared FARS database for 2014-2023.
myFARS <- get_fars(proceed = TRUE)We could also download the prepared GES/CRSS database:
myCRSS <- get_gescrss(proceed = TRUE)get_fars() and get_gescrss() return a list
with six tibbles: flat, multi_acc,
multi_veh, multi_per, events, and
codebook.
Each row in the flat tibble corresponds to a person
involved in a crash. As there may be multiple people and/or vehicles
involved in one crash, some variable-values are repeated within a crash
or vehicle. Each crash is uniquely identified with id,
which is a combination of year and st_case.
Note that st_case is not unique across years, for example,
st_case 510001 will appear in each year. The
id variable attempts to avoid this issue.
glimpse(myFARS$flat, width = 80)
#> Rows: 867,460
#> Columns: 227
#> $ year <dbl> 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 20…
#> $ state <fct> Alabama, Alabama, Alabama, Alabama, Alabama, Alabama, Al…
#> $ st_case <dbl> 10001, 10001, 10002, 10003, 10003, 10003, 10003, 10003, …
#> $ id <dbl> 201410001, 201410001, 201410002, 201410003, 201410003, 2…
#> $ veh_no <dbl> 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 3, 1, 1, 1, 2,…
#> $ per_no <dbl> 1, 2, 1, 1, 2, 3, 4, 1, 2, 3, 1, 1, 2, 3, 1, 1, 1, 1, 1,…
#> $ county <dbl> 71, 71, 59, 125, 125, 125, 125, 125, 125, 125, 121, 121,…
#> $ city <dbl> 0, 0, 0, 3050, 3050, 3050, 3050, 3050, 3050, 3050, 2275,…
#> $ lon <dbl> -85.98141, -85.98141, -87.77212, -87.52591, -87.52591, -…
#> $ lat <dbl> 34.62372, 34.62372, 34.39743, 33.19717, 33.19717, 33.197…
#> $ acc_type <fct> "Drive Off Road", "Drive Off Road", "Drive Off Road", "S…
#> $ age <fct> 24 Years, 30 Years, 52 Years, 22 Years, 21 Years, 18 Yea…
#> $ air_bag <fct> "Deployed- Combination", "Deployed- Combination", "Deplo…
#> $ alc_det <fct> "Observed", "Not Reported", "Not Reported", "Not Reporte…
#> $ alc_res <fct> "0.26 % BAC", "Test Not Given", "0.31 % BAC", "Test Not …
#> $ alc_status <fct> Test Given, Test Not Given, Test Given, Test Not Given, …
#> $ arr_hour <fct> 1:00am-1:59am, 1:00am-1:59am, 1:00pm-1:59pm, 3:00am-3:59…
#> $ arr_min <fct> 35, 35, 50, 10, 10, 10, 10, 10, 10, 10, 15, 15, 15, 15, …
#> $ atst_typ <fct> "Blood", "Test Not Given", "Blood", "Test Not Given", "T…
#> $ bikecgp <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ bikectype <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ bikedir <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ bikeloc <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ bikepos <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ body_typ <fct> "4-door sedan, hardtop", "4-door sedan, hardtop", "Stand…
#> $ bus_use <fct> "Not a Bus", "Not a Bus", "Not a Bus", "Not a Bus", "Not…
#> $ cargo_bt <fct> Not Applicable (N/A), Not Applicable (N/A), Not Applicab…
#> $ cdl_stat <fct> Suspended, Suspended, No (CDL), No (CDL), No (CDL), No (…
#> $ cert_no <fct> ************, ************, ************, ************, …
#> $ day <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3,…
#> $ day_week <fct> Wednesday, Wednesday, Wednesday, Wednesday, Wednesday, W…
#> $ death_da <fct> 1, Not Applicable (Non-Fatal), 1, Not Applicable (Non-Fa…
#> $ death_hr <fct> 1:00-1:59, Not Applicable (Non-fatal), 13:00-13:59, Not …
#> $ death_mn <fct> 15, Not Applicable (Non-fatal), 45, Not Applicable (Non-…
#> $ death_mo <fct> January, Not Applicable (Non-Fatal), January, Not Applic…
#> $ death_tm <chr> "115", "8888", "1345", "8888", "8888", "8888", "8888", "…
#> $ death_yr <fct> 2014, Not Applicable (Non-fatal), 2014, Not Applicable (…
#> $ deaths <dbl> 1, 1, 1, 0, 0, 0, 0, 2, 2, 2, 1, 0, 0, 0, 0, 1, 1, 0, 1,…
#> $ deformed <fct> "Disabling Damage", "Disabling Damage", "Disabling Damag…
#> $ doa <fct> Died at Scene, Not Applicable, Not Applicable, Not Appli…
#> $ dr_drink <fct> Yes, Yes, Yes, No, No, No, No, No, No, No, No, No, No, N…
#> $ dr_hgt <fct> 64, 64, 71, 999, 999, 999, 999, 63, 63, 63, 65, 74, 74, …
#> $ dr_pres <fct> Yes, Yes, Yes, Yes, Yes, Yes, Yes, Yes, Yes, Yes, Yes, Y…
#> $ dr_wgt <fct> 135 lbs., 135 lbs., 225 lbs., Unknown, Unknown, Unknown,…
#> $ dr_zip <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ drinking <fct> Yes (Alcohol Involved), Not Reported, Yes (Alcohol Invol…
#> $ drug_det <fct> "Not Reported", "Not Reported", "Not Reported", "Not Rep…
#> $ drugs <fct> Unknown, Not Reported, No (drugs not involved), Unknown,…
#> $ drunk_dr <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,…
#> $ dstatus <fct> Test Given, Test Not Given, Test Given, Test Not Given, …
#> $ ej_path <fct> "Not Ejected/Not Applicable", "Not Ejected/Not Applicabl…
#> $ ejection <fct> Not Ejected, Not Ejected, Not Ejected, Not Ejected, Not …
#> $ emer_use <fct> "Not Applicable", "Not Applicable", "Not Applicable", "N…
#> $ extricat <fct> Extricated, Not Extricated or Not Applicable, Not Extric…
#> $ fatals <dbl> 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ fire_exp <fct> No or Not Reported, No or Not Reported, No or Not Report…
#> $ first_mo <fct> November, November, No Record, No Record, No Record, No …
#> $ first_yr <fct> 2011, 2011, No Record, No Record, No Record, No Record, …
#> $ gvwr <fct> "Not Applicable", "Not Applicable", "Not Applicable", "N…
#> $ harm_ev <fct> "Boulder", "Boulder", "Tree (Standing Only)", "Motor Veh…
#> $ haz_cno <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ haz_id <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ haz_inv <fct> No, No, No, No, No, No, No, No, No, No, No, No, No, No, …
#> $ haz_plac <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ haz_rel <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ hispanic <fct> "Non-Hispanic", "Not A Fatality (not Applicable)", "Non-…
#> $ hit_run <fct> No, No, No, Yes, Yes, Yes, Yes, No, No, No, No, No, No, …
#> $ hosp_hr <fct> Unknown, Unknown, Unknown, Unknown, Unknown, Unknown, Un…
#> $ hosp_mn <fct> Unknown EMS Hospital Arrival Time, Unknown EMS Hospital …
#> $ hospital <fct> Not Transported, EMS Air, EMS Ground, Not Transported, N…
#> $ hour <fct> 1:00am-1:59am, 1:00am-1:59am, 1:00pm-1:59pm, 3:00am-3:59…
#> $ impact1 <fct> "11 Clock Point", "11 Clock Point", "12 Clock Point", "1…
#> $ inj_sev <fct> "Fatal Injury (K)", "Suspected Minor Injury(B)", "Fatal …
#> $ j_knife <fct> Not an Articulated Vehicle, Not an Articulated Vehicle, …
#> $ l_compl <fct> No valid license for this class vehicle, No valid licens…
#> $ l_endors <fct> "No Endorsements required for this vehicle", "No Endorse…
#> $ l_restri <fct> "No Restrictions or Not Applicable", "No Restrictions or…
#> $ l_state <fct> Alabama, Alabama, Alabama, Alabama, Alabama, Alabama, Al…
#> $ l_status <fct> Suspended, Suspended, Suspended, Not licensed, Not licen…
#> $ l_type <fct> Full Driver License, Full Driver License, Full Driver Li…
#> $ lag_hrs <fct> 0, 999, 0, 999, 999, 999, 999, 0, 0, 999, 0, 999, 999, 9…
#> $ lag_mins <fct> 0, 99, 15, 99, 99, 99, 99, 0, 13, 99, 0, 99, 99, 99, 99,…
#> $ last_mo <fct> April, April, No Record, No Record, No Record, No Record…
#> $ last_yr <fct> 2013, 2013, No Record, No Record, No Record, No Record, …
#> $ lgt_cond <fct> Dark - Not Lighted, Dark - Not Lighted, Daylight, Dark -…
#> $ location <fct> "Occupant of a Motor Vehicle", "Occupant of a Motor Vehi…
#> $ m_harm <fct> "Tree (Standing Only)", "Tree (Standing Only)", "Tree (S…
#> $ mak_mod <chr> "Toyota Corolla", "Toyota Corolla", "Dodge Ram Pickup", …
#> $ make <fct> Toyota, Toyota, Dodge, Chevrolet, Chevrolet, Chevrolet, …
#> $ man_coll <fct> Not a Collision with Motor Vehicle In-Transport, Not a C…
#> $ mcarr_i1 <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ mcarr_i2 <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ mcarr_id <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ milept <fct> None, None, None, None, None, None, None, None, None, No…
#> $ minute <fct> 15, 15, 30, 7, 7, 7, 7, 7, 7, 7, 0, 0, 0, 0, 0, 30, 0, 4…
#> $ mod_year <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ model <dbl> 32, 32, 482, 37, 37, 37, 37, 40, 40, 40, 472, 461, 461, …
#> $ month <fct> January, January, January, January, January, January, Ja…
#> $ motdir <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ motman <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ msafeqmt <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nhs <fct> This section IS NOT on the NHS, This section IS NOT on t…
#> $ not_hour <fct> Unknown, Unknown, Unknown, Unknown, Unknown, Unknown, Un…
#> $ not_min <fct> Unknown, Unknown, Unknown, Unknown, Unknown, Unknown, Un…
#> $ numoccs <fct> 02, 02, 01, 04, 04, 04, 04, 03, 03, 03, 01, 03, 03, 03, …
#> $ owner <fct> "Driver (in this crash) Not Registered Owner (Other Priv…
#> $ p_crash1 <fct> Negotiating a Curve, Negotiating a Curve, Going Straight…
#> $ p_crash2 <fct> "Off the edge of the road on the left side", "Off the ed…
#> $ p_crash3 <fct> No Avoidance Maneuver, No Avoidance Maneuver, No Avoidan…
#> $ pbcwalk <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pbswalk <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pbszone <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pcrash4 <fct> "Tracking", "Tracking", "Tracking", "Tracking", "Trackin…
#> $ pcrash5 <fct> "Departed roadway", "Departed roadway", "Departed roadwa…
#> $ pedcgp <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pedctype <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ peddir <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pedleg <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pedloc <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ pedpos <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ peds <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ pedsnr <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ per_typ <fct> "Driver of a Motor Vehicle In-Transport", "Passenger of …
#> $ permvit <dbl> 2, 2, 1, 7, 7, 7, 7, 7, 7, 7, 5, 5, 5, 5, 5, 1, 1, 2, 2,…
#> $ pernotmvit <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ persons <dbl> 2, 2, 1, 7, 7, 7, 7, 7, 7, 7, 5, 5, 5, 5, 5, 1, 1, 2, 2,…
#> $ prev_acc <fct> None, None, None, None, None, None, None, None, None, No…
#> $ prev_dwi <fct> 2, 2, None, None, None, None, None, None, None, None, No…
#> $ prev_oth <fct> 1, 1, None, None, None, None, None, None, None, None, No…
#> $ prev_spd <fct> 1, 1, None, None, None, None, None, None, None, None, No…
#> $ prev_sus <fct> 6, 6, None, None, None, None, None, None, None, None, No…
#> $ pvh_invl <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,…
#> $ race <fct> "White", "Not a Fatality (not Applicable)", "White", "No…
#> $ rail <fct> Not Applicable, Not Applicable, Not Applicable, Not Appl…
#> $ reg_stat <fct> Alabama, Alabama, Alabama, Alabama, Alabama, Alabama, Al…
#> $ rel_road <fct> On Roadside, On Roadside, On Roadside, On Roadway, On Ro…
#> $ reljct1 <fct> No, No, No, No, No, No, No, No, No, No, No, No, No, No, …
#> $ reljct2 <fct> Non-Junction, Non-Junction, Non-Junction, Intersection, …
#> $ rest_mis <fct> "No", "No", "No", "No", "No", "No", "No", "No", "No", "N…
#> $ rest_use <fct> "Shoulder and Lap Belt Used", "Shoulder and Lap Belt Use…
#> $ road_fnc <fct> Rural-Minor Collector, Rural-Minor Collector, Rural-Loca…
#> $ rolinloc <fct> On Roadside, On Roadside, No Rollover, No Rollover, No R…
#> $ rollover <fct> "Rollover, Tripped by Object/Vehicle", "Rollover, Trippe…
#> $ route <fct> County Road, County Road, County Road, U.S. Highway, U.S…
#> $ rur_urb <fct> Rural, Rural, Rural, Urban, Urban, Urban, Urban, Urban, …
#> $ sch_bus <fct> No, No, No, No, No, No, No, No, No, No, No, No, No, No, …
#> $ seat_pos <fct> "Front Seat, Left Side", "Front Seat, Right Side", "Fron…
#> $ sex <fct> Male, Female, Male, Male, Female, Male, Male, Female, Fe…
#> $ sp_jur <fct> No Special Jurisdiction, No Special Jurisdiction, No Spe…
#> $ spec_use <fct> "No Special Use", "No Special Use", "No Special Use", "N…
#> $ speedrel <fct> "Yes, Exceeded Speed Limit", "Yes, Exceeded Speed Limit"…
#> $ str_veh <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ tow_veh <fct> "No Trailing Units", "No Trailing Units", "No Trailing U…
#> $ towed <fct> "Towed Due to Disabling Damage", "Towed Due to Disabling…
#> $ trav_sp <fct> 070 MPH, 070 MPH, 040 MPH, Unknown, Unknown, Unknown, Un…
#> $ tway_id <chr> "CR-67", "CR-67", "CR-26", "US-SR 6", "US-SR 6", "US-SR …
#> $ tway_id2 <chr> NA, NA, NA, "VERTERAN'S MEMORIAL PKWY", "VERTERAN'S MEMO…
#> $ typ_int <fct> "Not an Intersection", "Not an Intersection", "Not an In…
#> $ underide <fct> "No Underride or Override Noted", "No Underride or Overr…
#> $ unittype <fct> Motor Vehicle In-Transport (Inside or Outside the Traffi…
#> $ v_config <fct> "Not Applicable", "Not Applicable", "Not Applicable", "N…
#> $ valign <fct> Curve Right, Curve Right, Straight, Straight, Straight, …
#> $ ve_forms <dbl> 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 2, 2,…
#> $ ve_total <dbl> 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 1, 1, 3, 3,…
#> $ vin <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ vnum_lan <fct> Two lanes, Two lanes, Two lanes, Five lanes, Five lanes,…
#> $ vpavetyp <fct> "Blacktop, Bituminous, or Asphalt", "Blacktop, Bituminou…
#> $ vprofile <fct> "Level", "Level", "Level", "Level", "Level", "Level", "L…
#> $ vspd_lim <fct> 45 MPH, 45 MPH, 40 MPH, 45 MPH, 45 MPH, 45 MPH, 45 MPH, …
#> $ vsurcond <fct> "Dry", "Dry", "Dry", "Dry", "Dry", "Dry", "Dry", "Dry", …
#> $ vtcont_f <fct> "No Controls", "No Controls", "No Controls", "Device Fun…
#> $ vtrafcon <fct> No Controls, No Controls, No Controls, Traffic control s…
#> $ vtrafway <fct> "Two-Way, Not Divided", "Two-Way, Not Divided", "Two-Way…
#> $ work_inj <fct> No, Not Applicable (not a fatality), No, Not Applicable …
#> $ wrk_zone <fct> "None", "None", "None", "None", "None", "None", "None", …
#> $ func_sys <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ rd_owner <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ cityname <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ countyname <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ statename <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr1vin <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr2vin <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr3vin <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmhelmet <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmlight <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmothpre <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmothpro <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmpropad <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ nmrefclo <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ prev_sus1 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ prev_sus2 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ prev_sus3 <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ helm_mis <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ helm_use <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ gvwr_from <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ gvwr_to <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ icfinalbody <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr1gvwr <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr2gvwr <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ trlr3gvwr <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ vpicbodyclass <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ vpicmake <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ vpicmodel <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ underoverride <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ devmotor <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ devtype <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ acc_config <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
#> $ a1 <dbl> 26, 26, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17…
#> $ a2 <dbl> 26, 26, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 1…
#> $ a3 <dbl> 26, 26, 31, 14, 14, 14, 14, 14, 14, 14, 0, 0, 0, 0, 0, 0…
#> $ a4 <dbl> 26, 26, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17…
#> $ a5 <dbl> 26, 26, 31, 17, 17, 17, 17, 17, 17, 17, 0, 0, 0, 0, 0, 0…
#> $ a6 <dbl> 26, 26, 31, 15, 15, 15, 15, 15, 15, 15, 0, 0, 0, 0, 0, 1…
#> $ a7 <dbl> 26, 26, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17…
#> $ a8 <dbl> 26, 26, 31, 15, 15, 15, 15, 15, 15, 15, 0, 0, 0, 0, 0, 0…
#> $ a9 <dbl> 26, 26, 31, 16, 16, 16, 16, 16, 16, 16, 0, 0, 0, 0, 0, 0…
#> $ a10 <dbl> 26, 26, 31, 15, 15, 15, 15, 15, 15, 15, 0, 0, 0, 0, 0, 0…
#> $ p1 <dbl> 26, NA, 31, 0, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, 0…
#> $ p2 <dbl> 26, NA, 31, 0, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, 1…
#> $ p3 <dbl> 26, NA, 31, 14, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …
#> $ p4 <dbl> 26, NA, 31, 0, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, 0…
#> $ p5 <dbl> 26, NA, 31, 17, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …
#> $ p6 <dbl> 26, NA, 31, 15, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …
#> $ p7 <dbl> 26, NA, 31, 0, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, 0…
#> $ p8 <dbl> 26, NA, 31, 15, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …
#> $ p9 <dbl> 26, NA, 31, 16, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …
#> $ p10 <dbl> 26, NA, 31, 15, NA, NA, NA, 0, NA, NA, 0, 0, NA, NA, 0, …The multi_ tibbles contain those variables for which
there may be a varying number of values for any entity (e.g., driver
impairments, vehicle events, weather conditions at time of crash). Each
tibble has the requisite data elements corresponding to the entity:
multi_acc includes st_case and
year, multi_veh adds veh_no
(vehicle number), and multi_per adds per_no
(person number).
The top name-value pairs of each tibble are shown below.
myFARS$multi_acc %>%
filter(!is.na(value)) %>%
group_by(name, value) %>%
summarize(n=n(), .groups = "drop") %>%
arrange(desc(n)) %>% slice(1:10) %>%
select(name, value, n) %>%
knitr::kable(format = "html", caption = "Top Name-Value Pairs for the multi_acc Object")| name | value | n |
|---|---|---|
| weather1 | Clear | 140091 |
| weather | Clear | 111657 |
| crashrf | None Noted | 71250 |
| weather1 | Cloudy | 29829 |
| weather | Cloudy | 21034 |
| weather1 | Rain | 14058 |
| weather | Rain | 10382 |
| cf1 | Motor Vehicle struck by falling cargo,or something that came loose from or something that was set in motion by a vehicle | 3995 |
| crashrf | Motor Vehicle struck by falling cargo,or something that came loose from or something that was set in motion by a vehicle | 3549 |
| weather2 | Cloudy | 2205 |
myFARS$multi_veh %>%
filter(!is.na(value)) %>%
group_by(name, value) %>%
summarize(n=n(), .groups = "drop") %>%
arrange(desc(n)) %>% slice(1:10) %>%
select(name, value, n) %>%
knitr::kable(format = "html", caption = "Top Name-Value Pairs for the multi_veh Object")| name | value | n |
|---|---|---|
| mvisobsc | No Obstruction Noted | 282785 |
| drimpair | None/Apparently Normal | 253863 |
| vision | No Obstruction Noted | 220560 |
| vehiclecc | None Noted | 218470 |
| mdareas | 12 Clock Value | 211504 |
| damage | 12 Clock Value | 169994 |
| mdrdstrd | Not Distracted | 155771 |
| vehiclesf | None Noted | 118399 |
| vehiclesf | 0 | 115082 |
| mdareas | 11 Clock Value | 109333 |
myFARS$multi_per %>%
filter(!is.na(value)) %>%
group_by(name, value) %>%
summarize(n=n(), .groups = "drop") %>%
arrange(desc(n)) %>% slice(1:10) %>%
select(name, value, n) %>%
knitr::kable(format = "html", caption = "Top Name-Value Pairs for the multi_per Object")| name | value | n |
|---|---|---|
| multrace | No | 370399 |
| drugres3 | Test Not Given | 317417 |
| drugtst3 | Test Not Given | 317349 |
| drugres2 | Test Not Given | 305828 |
| drugtst2 | Test Not Given | 305735 |
| drugspec | Test Not Given | 304882 |
| drugres | Test Not Given | 304880 |
| drugspec | Whole Blood | 257238 |
| race | Not a Fatality (not Applicable) | 201623 |
| drugtst1 | Test Not Given | 199168 |
The events tibble provides a sequence of numbered events
for each vehicle in each crash. See the vignette(“Crash Sequence of
Events”, package = “rfars”) for more information.
head(myFARS$events, 10) %>%
knitr::kable(format="html", caption = "Preview of events Object")| state | st_case | veh_no | aoi | soe | veventnum | year |
|---|---|---|---|---|---|---|
| Alabama | 10001 | 1 | Non-Harmful Event | Cross Centerline | 1 | 2014 |
| Alabama | 10001 | 1 | Non-Harmful Event | Ran Off Roadway - Left | 2 | 2014 |
| Alabama | 10001 | 1 | 11 Clock Point | Boulder | 3 | 2014 |
| Alabama | 10001 | 1 | Non-Collision | Rollover/Overturn | 4 | 2014 |
| Alabama | 10001 | 1 | Top | Tree (Standing Only) | 5 | 2014 |
| Alabama | 10001 | 1 | Not Reported | Boulder | 6 | 2014 |
| Alabama | 10001 | 1 | Non-Collision | Immersion or Partial Immersion | 7 | 2014 |
| Alabama | 10002 | 1 | Non-Harmful Event | Cross Centerline | 1 | 2014 |
| Alabama | 10002 | 1 | Non-Harmful Event | Ran Off Roadway - Left | 2 | 2014 |
| Alabama | 10002 | 1 | 12 Clock Point | Tree (Standing Only) | 3 | 2014 |
The codebook tibble provides a searchable codebook for
the data, useful if you know what concept you’re looking for but not the
variable that describes it. rfars also includes pre-loaded
codebooks for FARS and GESCRSS (rfars::fars_codebook and
rfars::gescrss_codebook). See
vignette('Searchable Codebooks', package = 'rfars') for
more information.
See vignette("Counts", package = "rfars") for
information on the pre-loaded annual_counts dataframe and
the counts() function. Also see
vignette("Alcohol Counts", package = "rfars") for details
on how BAC values are imputed and reported in Traffic Safety
Facts.