Name: San Francisco Police Stop Data 2018-2023
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

San Francisco Police Stop Data 2018-2023

This dataset provides comprehensive information on police stops conducted by the San Francisco Police Department from 2018 to 2023.

It includes details such as the date and time of the stop, duration, location, race/ethnicity of the person stopped, gender, age, reason for the stop, actions taken, search basis, property seizure, contraband or evidence found, and the results of the stop.

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Interesting Task Ideas:

Analyze racial disparities in police stops and identify any biases or discriminatory patterns.
Investigate the relationship between the reason for the stop and subsequent actions taken by the police.
Explore geographical variations in police stop patterns and their correlation with socio-economic factors.
Determine the impact of traffic violations on the likelihood of search or property seizure during a stop.
Examine the role of perceived or known disabilities in police stops and potential disparities in treatment.
Create predictive models to estimate the duration and outcome of a police stop based on various factors.
Investigate the use of force during police stops and its correlation with different variables.
Analyze changes in police stop patterns over time and identify any emerging trends or shifts in enforcement strategies.

Photo by Scott Rodgerson on Unsplash

Tables

Sfpd Stop Cleaned Data

@kaggle.asaniczka_san_francisco_police_stop_data_2018_2023.sfpd_stop_cleaned_data

14.91 MB
250,093 rows
46 columns

CREATE TABLE sfpd_stop_cleaned_data (
  "doj_record_id" VARCHAR,
  "person_number" BIGINT,
  "agency_ori" VARCHAR,
  "stop_datetime" TIMESTAMP,
  "duration_of_stop" BIGINT,
  "is_stop_response_to_call" BOOLEAN,
  "location" VARCHAR,
  "district" VARCHAR,
  "city" VARCHAR,
  "perceived_race_ethnicity" VARCHAR,
  "perceived_gender" VARCHAR,
  "is_lgbt" BOOLEAN,
  "perceived_age" BIGINT,
  "perceived_age_group" VARCHAR,
  "had_limited_or_no_english" BOOLEAN,
  "perceived_or_known_disability" VARCHAR,
  "reason_for_stop" VARCHAR,
  "traffic_violation_type" VARCHAR,
  "traffic_viol_cjis_off_code" BIGINT,
  "traffic_viol_off_code" VARCHAR,
  "traffic_viol_off_statute" VARCHAR,
  "suspicion_cjis_off_code" BIGINT,
  "suspicion_off_code_txt" VARCHAR,
  "suspicion_off_statute" VARCHAR,
  "suspicion_sub_type" VARCHAR,
  "actions_taken" VARCHAR,
  "basis_for_search" VARCHAR,
  "basis_for_property_seizure" VARCHAR,
  "type_of_property_seized" VARCHAR,
  "contraband_or_evidence" VARCHAR,
  "results_of_stop" VARCHAR,
  "longitude" DOUBLE,
  "latitude" DOUBLE,
  "supervisor_district" BIGINT,
  "analysis_neighborhoods" VARCHAR,
  "perceived_race_ethnicity_code" DOUBLE,
  "perceived_gender_code" BIGINT,
  "perceived_or_known_disability_code" DOUBLE,
  "reason_for_stop_code" BIGINT,
  "actions_taken_code" VARCHAR,
  "basis_for_search_code" DOUBLE,
  "basis_for_property_seizure_code" VARCHAR,
  "type_of_property_seized_code" DOUBLE,
  "contraband_or_evidence_code" DOUBLE,
  "suspicion_sub_type_code" DOUBLE,
  "results_of_stop_code" DOUBLE
);