Homicides in San Francisco, California, 2018 - 2023.
Format
a dataframe with 135 rows and 7 variables:
- incident_datetime
date and time of the incident
- incident_id
unique identifier for the incident
- incident_code
incident code
- incident_category
incident category
- incident_subcategory
incident subcategory
- lat
latitude
- lon
longitude
Source
https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-2018-to-Present/wg3w-h783/data_preview Published under a Open Data Commons Public Domain Dedication and License v1.0 (PDDL).
Details
For city-level crime data, municipalities, particularly large ones, often provide the data via an open data portal. Here, the data were discovered in the San Francisco Open Data Portal. Most crime data is reported on the Uniform Crime Reports and submitted to the Federal Bureau of Investigation. You can investigate and learn more about crime in the United States via the FBI's Crime Data Explorer. Murder is usually grouped with non-negligent manslaughter in counting homicides. For that reason, the "incident_subcategory" was included.
References
San Francisco Police Department, Police Department Incident Reports: 2018 to Present (2024) last accessed October 22, 2024.
Examples
homicides
#> # A tibble: 135 × 7
#> incident_datetime incident_id incident_code incident_category
#> <dttm> <dbl> <chr> <chr>
#> 1 2023-12-28 05:38:00 1351016 01003 Homicide
#> 2 2023-12-26 06:34:00 1354814 01160 Homicide
#> 3 2023-12-26 06:34:00 1354978 01160 Homicide
#> 4 2023-12-15 11:41:00 1347453 01001 Homicide
#> 5 2023-12-13 00:00:00 1346676 01001 Homicide
#> 6 2023-12-13 00:00:00 1346899 01001 Homicide
#> 7 2023-12-13 00:00:00 1346906 01001 Homicide
#> 8 2023-12-11 14:50:00 1350508 01160 Homicide
#> 9 2023-12-06 01:46:00 1344886 01160 Homicide
#> 10 2023-11-27 00:20:00 1340297 01001 Homicide
#> # ℹ 125 more rows
#> # ℹ 3 more variables: incident_subcategory <chr>, lat <dbl>, lon <dbl>