Florida Crashes by City 2012 - 2021
fl_crashes_city.RmdFlorida City Crashes by Year and Injury
| year | total_crashes | total_persons | total_injured | total_serious | total_killed |
|---|---|---|---|---|---|
| 2012 | 151946 | 406540 | 87364 | 7767 | 857 |
| 2013 | 179116 | 475429 | 97714 | 8004 | 941 |
| 2014 | 206085 | 543725 | 107590 | 7978 | 962 |
| 2015 | 228513 | 599041 | 114503 | 7377 | 1150 |
| 2016 | 238609 | 623596 | 118204 | 7211 | 1218 |
| 2017 | 245612 | 636863 | 120129 | 7107 | 1186 |
| 2018 | 213617 | 558240 | 105598 | 6210 | 1149 |
| 2019 | 83795 | 216927 | 45436 | 4509 | 879 |
| 2020 | 12234 | 25882 | 9354 | 3232 | 765 |
| 2021 | 3497 | 7465 | 3013 | 1167 | 256 |
Top 100 Florida Cities for Total Crashes in 2019
#> `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.Top 100 Florida Cities for Crashes Per 100,000 Residents
From Florida Traffic Crashes Report Manual, there were 634 city codes in fl_city_codes. Some cities have multiple codes in fl_city_codes. For example, Jacksonville is coded as both “0225” and “0238” and Miami as “0166” and “0191”. The U.S. Census bureau listed 412 unique cities in fl_city_pop. Additionally, the U.S. Census bureau also used “.” to abbreviate “Saint” to “St.” so the period was eliminated from the city field. When the two dataframes were merged, there were 383 successful matches.
#> Joining, by = c("year", "city_code")
#> `summarise()` has grouped output by 'year', 'city'. You can override using the `.groups` argument.Florida City Crashes by Day
Data was available for the calendar years 2012 through 2019. The crashes were summed by date and faceted by year. Years 2012 through 2014 were omitted to expand the vertical plotting area and make the variation more obvious. The number of crashes decreased beginning in 2019.
Top 100 Florida Cities by Motorcycle Crashes
#> Joining, by = c("year", "city_code")
#> `summarise()` has grouped output by 'year', 'city_code'. You can override using the `.groups` argument.Top 100 Florida Cities for Motorcycle Crashes Per 100,000 Residents
#> Joining, by = c("year", "city_code")
#> `summarise()` has grouped output by 'year', 'city_code', 'city'. You can override using the `.groups` argument.