Homicides reported to the California DOJ by local law enforcement.

openjustice.doj.ca.gov-homicide-1.1.1. Modified 2020-06-18T00:08:12

Resources

• homicides. California homicides
• homicide_justifiable. California justifiable homicides
• homicide_manslaughter. California manslaughter homicides
• precipitating_event_labels. Value labels for the Precipitating Event column
• means_of_death_labels. Value labels for the means_of_death column
• location_labels. Value labels for the location column
• gender_labels. Value labels for the gender column
• relationship_labels. Value labels for the relationship column
• race_ethnicity_labels. Value labels for the race_ethnicity column

Documentation

The Homicides in California file is publilshed by the California Department of Justices’s Open Justice site. It collects reports from local law enformcement. From the website:

Collection of mulltiple, simpler datasets from OpenJustice that don’t require special processing

openjustice.doj.ca.gov-datasets-1.1.1. Modified 2020-06-18T00:07:36

Resources

• arrests. Arrests counts aggregated to year, race, agency and other factors
• arrest_dispositions. Arrests counts aggregated to year, race, agency and other factors, but disaggregated on disposition.
• complaints. Summary of civilian complaints by agency
• crimes_clearances. Counts of reported cimes and clearances, by year and agency
• ripa_stop. RIPA Stop Data
• lea_cjp. Law Enforcement and Criminal Justice Personnel
• leap. Law Enforcement Personnel
• leoka. Law Enforcement Officers Killed or Assaulted

Documentation

Documentation Links

• Open Justice Homepage A transparency initiative led by the California Department of Justice that publishes criminal justice data so we can understand how we are doing, hold ourselves accountable, and improve public policy to make California safer.

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

San Diego Police Calls for Service, linked to related datasets

sandiego.gov-police_calls_for_service-1.1.1. Modified 2020-06-17T23:58:13

Resources

• sdpd_calls_dispositions. San Diego Police Calls for Service, 2015 to 2020
• sdpd_beats. San Diego Police beats
• sdpd_call_type. San Diego Police call type codes
• sdpd_calls_for_service. San Diego Police Calls for Service, 2015 to 2020
• ct_map. Map from call type descriptions to simpler call types.

Documentation

This dataset links to the San Dieg Police Calls for Service datasets, from multiple years, combine the years and lints to the destriptions of disposition codes and beat neighborhoods.

California’s county and agency level context data

openjustice.doj.ca.gov-agencies-1.1.1. Modified 2020-06-17T21:37:32

Resources

• ca_lea_demo. California Law Enforcement Agencies and demographic statistics for their service areas.
• ca_lea_ncic. California LEA NCIC codes, names, and years they actively reported.

Documentation

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

Data Dictionary

ca_lea_demo | ca_lea_ncic

ca_lea_demo

ca_lea_ncic

Packages

• s3 s3://library.metatab.org/openjustice.doj.ca.gov-agencies-1.1.1.csv
• csv https://library-metatab-org.s3.amazonaws.com/openjustice.doj.ca.gov-agencies-1.1.1.csv
• source https://github.com/metatab-packages/policedata-collection.git

Accessing Packages in Metapack

import metapack as mp
pkg = mp.open_package('https://library-metatab-org.s3.amazonaws.com/openjustice.doj.ca.gov-agencies-1.1.1.csv')

# Create Dataframes
ca_lea_demo_df = pkg.resource('ca_lea_demo').dataframe()
ca_lea_ncic_df = pkg.resource('ca_lea_ncic').dataframe()

Counts and rates for assaults as a cause of death, from a CDC Wonder search.

wonder.cdc.goc-underlying_cod-state-assault-1.1.2. Modified 2020-06-17T23:58:37

Resources

• assaults. Counts and rates of Assault as a cause of death, from CDC Wonder.

Documentation

This dataset is an extract from CDC Wonder, with rates and counts of deaths due to assault, by state.

Notes from the Dataset

These notes were included in the original downloaded source file:

---
Dataset: Underlying Cause of Death, 1999-2018
Query Parameters:
ICD-10 Codes: X85-Y09 (Assault)
Group By: State; Year; Race
Show Totals: Disabled
Show Zero Values: True
Show Suppressed: False
Standard Population: 2000 U.S. Std. Population
Calculate Rates Per: 100,000
Rate Options: Default intercensal populations for years 2001-2009 (except Infant Age Groups)
---
Help: See http://wonder.cdc.gov/wonder/help/ucd.html for more information.
---
Query Date: Jun 11, 2020 11:35:55 AM
---
Suggested Citation: Centers for Disease Control and Prevention, National Center for Health Statistics. Underlying Cause of Death
1999-2018 on CDC WONDER Online Database, released in 2020. Data are from the Multiple Cause of Death Files, 1999-2018, as
compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Accessed
at http://wonder.cdc.gov/ucd-icd10.html on Jun 11, 2020 11:35:55 AM
---
Messages:
1. Totals are not available for these results due to suppression constraints. More Information:
http://wonder.cdc.gov/wonder/help/faq.html#Privacy.
2. Rows with suppressed Deaths are hidden. Use Quick Options above to show suppressed rows.
---
Caveats:
1. As of April 3, 2017, the underlying cause of death has been revised for 125 deaths in 2014. More information:
http://wonder.cdc.gov/wonder/help/ucd.html#2014-Revision.
2. Circumstances in Georgia for the years 2008 and 2009 have resulted in unusually high death counts for the ICD-10 cause of
death code R99, "Other ill-defined and unspecified causes of mortality." Caution should be used in interpreting these data.
More information: http://wonder.cdc.gov/wonder/help/ucd.html#Georgia-Reporting-Anomalies.
3. Circumstances in New Jersey for the year 2009 have resulted in unusually high death counts for the ICD-10 cause of death code
R99, "Other ill-defined and unspecified causes of mortality" and therefore unusually low death counts in other ICD-10 codes,
most notably R95, "Sudden Infant Death Syndrome" and X40-X49, "Unintentional poisoning." Caution should be used in
interpreting these data. More information: http://wonder.cdc.gov/wonder/help/ucd.html#New-Jersey-Reporting-Anomalies.
4. Circumstances in California resulted in unusually high death counts for the ICD-10 cause of death code R99, "Other
ill-defined and unspecified causes of mortality" for deaths occurring in years 2000 and 2001. Caution should be used in
interpreting these data. More information: http://wonder.cdc.gov/wonder/help/ucd.html#California-Reporting-Anomalies.
5. Data are Suppressed when the data meet the criteria for confidentiality constraints. More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Assurance of Confidentiality.
6. Death rates are flagged as Unreliable when the rate is calculated with a numerator of 20 or less. More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Unreliable.
7. The populations used to calculate standard age-adjusted rates are documented here: More information:
http://wonder.cdc.gov/wonder/help/ucd.html#2000 Standard Population.
8. The method used to calculate age-adjusted rates is documented here: More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Age-Adjusted Rates.
9. Deaths for persons of unknown age are included in counts and crude rates, but are not included in age-adjusted rates.
10. Information included on the death certificate about the race and Hispanic ethnicity of the decedent is reported by the
funeral director as provided by an informant, often the surviving next of kin, or, in the absence of an informant, on the basis
of observation. Race and ethnicity information from the census is by self-report. To the extent that race and Hispanic origin
are inconsistent between these two data sources, death rates will be biased. More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Racial Differences.
11. The method used to calculate 95% confidence intervals is documented here: More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Confidence-Intervals.
12. The method used to calculate standard errors is documented here: More information:
http://wonder.cdc.gov/wonder/help/ucd.html#Standard-Errors.
13. The population figures for year 2018 are bridged-race estimates of the July 1 resident population, from the Vintage 2018
postcensal series released by NCHS on June 25, 2019. The population figures for year 2017 are bridged-race estimates of the July
1 resident population, from the Vintage 2017 postcensal series released by NCHS on June 27, 2018. The population figures for
year 2016 are bridged-race estimates of the July 1 resident population, from the Vintage 2016 postcensal series released by NCHS
on June 26, 2017. The population figures for year 2015 are bridged-race estimates of the July 1 resident population, from the
Vintage 2015 postcensal series released by NCHS on June 28, 2016. The population figures for year 2014 are bridged-race
estimates of the July 1 resident population, from the Vintage 2014 postcensal series released by NCHS on June 30, 2015. The
population figures for year 2013 are bridged-race estimates of the July 1 resident population, from the Vintage 2013 postcensal
series released by NCHS on June 26, 2014. The population figures for year 2012 are bridged-race estimates of the July 1 resident
population, from the Vintage 2012 postcensal series released by NCHS on June 13, 2013. The population figures for year 2011 are
bridged-race estimates of the July 1 resident population, from the Vintage 2011 postcensal series released by NCHS on July 18,
2012. Population figures for 2010 are April 1 Census counts. The population figures for years 2001 - 2009 are bridged-race
estimates of the July 1 resident population, from the revised intercensal county-level 2000 - 2009 series released by NCHS on
October 26, 2012. Population figures for 2000 are April 1 Census counts. Population figures for 1999 are from the 1990-1999
intercensal series of July 1 estimates. Population figures for the infant age groups are the number of live births.
<br/><b>Note:</b> Rates and population figures for years 2001 - 2009 differ slightly from previously published reports, due to
use of the population estimates which were available at the time of release.
14. The population figures used in the calculation of death rates for the age group 'under 1 year' are the estimates of the
resident population that is under one year of age. More information: http://wonder.cdc.gov/wonder/help/ucd.html#Age Group.

Documentation Links

• Underlying Cause of Death 1999-2018 Dataset documentation

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

Austin Police Department response to police resistance incidents.

austintexas.gov-response_to_resistance-1.1.4. Modified 2020-06-17T23:53:20

Resources

• r2r_2015. Response to Resistance, 2015
• r2r_2016. Response to Resistance, 2016
• r2r_2017. Response to Resistance, 2017
• r2r_2018. Response to Resistance, 2018
• r2r_2015_2018. Combined R2R files, 2015 to 2018

Documentation

This data package collects multiple years of the Response to Resistance dataset from the Austin, TX Police department. It includes each of the four source files and a fifth file that combines the four source files.

Boundary shapes for San Diego neighborhoods, beats and divisions, with ACS 2019 estimates for populations, by race.

sandiego.gov-police_regions-2.1.2. Modified 2021-02-25T19:08:44

Resources

• pd_beats. Police beats
• pd_divisions. Police Divisions
• pd_neighborhoods. Police Neighborhoods
• beat_demographics. Counts of people in the beat, by race.

Documentation

This package links shapefiles for San Diego police beats to Census tracts and merges in ACS estimates for population, by race, from the 2016 5 year ACS. When a police beat boundry crosses a tract, the tract population is allocated to beats by the proportion of the overlap by area. See the Jupyter notebook that performs the procedure for details.