Related Tables#

In some cases, an agency will split data on a topic across multiple tables to enable better representation of many-to-one relationships. For example, a single use of force incident can involve multiple subjects and/or officers. In this case, there might be 3 use of force tables for each of the following:

Incidents
Officers
Subjects

Usually, in this case, there will a unique ID for each incident that will appear in each table. This ID can be used to look up which subjects and officers were involved in the incident.

Table types for related tables in OpenPoliceData are of the form {general table type} - {sub-type} where general table type describes the type of interaction (i.e. use of force, complaints, etc.) and sub-type indicates the subset of data contained in the table (such as Incidents, Officers, and Subjects in the example above).

[2]:

import openpolicedata as opd
src = opd.Source("Tucson")
src.datasets[src.datasets['TableType'].str.contains("SHOOTING")]

[2]:

	State	SourceName	Agency	AgencyFull	TableType	coverage_start	coverage_end	last_coverage_check	Description	source_url	readme	URL	Year	DataType	date_field	dataset_id	agency_field	min_version	query
43	Arizona	Tucson	Tucson	Tucson Police Department	OFFICER-INVOLVED SHOOTINGS - INCIDENTS	2010-10-18	2018-05-18	07/06/2023	This approximately 9-year dataset of shooting ...	https://gisdata.tucsonaz.gov/datasets/cotgis::...	<NA>	https://publicgis.tucsonaz.gov/open/rest/servi...	MULTIPLE	ArcGIS	INCI_DATE	<NA>	<NA>	0.7	NaN
44	Arizona	Tucson	Tucson	Tucson Police Department	OFFICER-INVOLVED SHOOTINGS - OFFICERS	NaT	NaT	07/06/2023	This approximately 9-year dataset of suspects ...	https://gisdata.tucsonaz.gov/datasets/cotgis::...	<NA>	https://publicgis.tucsonaz.gov/open/rest/servi...	NONE	ArcGIS	<NA>	<NA>	<NA>	<NA>	NaN
45	Arizona	Tucson	Tucson	Tucson Police Department	OFFICER-INVOLVED SHOOTINGS - SUBJECTS	NaT	NaT	07/06/2023	This approximately 9-year dataset of suspects ...	https://gisdata.tucsonaz.gov/datasets/cotgis::...	<NA>	https://publicgis.tucsonaz.gov/open/rest/servi...	NONE	ArcGIS	<NA>	<NA>	<NA>	<NA>	NaN

Source.find_related_tables can be used to find tables that are related:

[3]:

# Find Tucson datasets related to the OFFICER-INVOLVED SHOOTINGS - INCIDENTS data
related_tables, corresponding_years = src.find_related_tables(opd.TableType.SHOOTINGS_INCIDENTS)
related_tables

[3]:

('OFFICER-INVOLVED SHOOTINGS - OFFICERS',
 'OFFICER-INVOLVED SHOOTINGS - SUBJECTS')

To help with analyzing related datasets, Table.merge can be used to merge related tables. Note that the left table in the merge, currently must be standardized.

[ ]:

t1 = src.load(opd.TableType.SHOOTINGS_INCIDENTS, date=opd.defs.MULTI) # Year values are from src.datasets table
t1.standardize()  # Left table in the merge must currently be standardized
t2 = src.load(opd.TableType.SHOOTINGS_SUBJECTS, date="NONE")
t3 = t1.merge(t2, std_id=True)
t3.table.head()

	INCIDENT_ID	DATE	ZIP_CODE	OBJECTID_1	X	Y	BOI_NUM	ADDRESS	CITY	STATE	...	OBJECTID	BOI_NUM_FromMerged	SUS_WEAPON	SUS_INJDEC	OFC_INJDEC	SUS_AGE	SUS_RACE	SUS_GEND	DATASOURCE_FromMerged	RAW_INCI_NUM_FromMerged
0	1010180542	2010-10-18	85701	1	9.931871e+05	445491.498380	10-0658	E Broadway Bl / S 6th Av	TUCSON	AZ	...	1	10-0658	Handgun	Deceased	No	34	Indian	Male	None	1010180542
1	1103108001	2011-03-09	85711	2	1.021717e+06	437594.379686	11-0145	5402 E 30th St	TUCSON	AZ	...	2	11-0145	Vehicle	Deceased	Injured	22	White	Male	None	1103108001
2	1103108001	2011-03-09	85711	2	1.021717e+06	437594.379686	11-0145	5402 E 30th St	TUCSON	AZ	...	3	11-0145	Vehicle	Injured	No	42	Black	Female	None	1103108001
3	1103108001	2011-03-09	85711	2	1.021717e+06	437594.379686	11-0145	5402 E 30th St	TUCSON	AZ	...	4	11-0145	Vehicle	No	No	25	Black	Male	None	1103108001
4	1105280140	2011-05-28	85714	3	9.942417e+05	424406.071054	11-0317	200 E Irvington Rd	TUCSON	AZ	...	5	11-0317	Handgun	Deceased	No	26	Hispanic	Male	None	1105280140

5 rows × 25 columns

Note that the merged table has incident details on the left (date, location) and subject demographics on the right (SUS_RACE, SUS_GENDER). std_id=True requests that the unique ID column be identified and standardized to have a standardized name (INCIDENT_ID). Additionally, Table.merge accepts the same inputs as pandas.merge. As in the above example, if no column is selected to perform on the merge on, Table.merge defaults to attempting to find a unique ID column to use (even if std_id is False).