GitHub repository: therealyash13/Stop-and-Frisk-Incidents-Prediction-at-New-York-City
Created: 2021-11-14T20:30:49Z
Description: The Fourth Amendment to the United States Constitution guarantees individuals protection from “unreasonable searches and seizures (U.S. CONST. amend. IV.). A search or a seizure is considered acceptable under the fourth amendment only when the interest of the government outweighs the meddlesomeness of the search. Stop and Frisk is a controversial policy that is followed in by the New York Police Department for a long run. It’s when a police officer temporarily detains someone based on a suspicion that the person is involved in criminal activity (the “Stop”), and, if the police officer suspects the person is armed and dangerous, pats down their outer clothing (the “Frisk”). Some people believe that the program helps catch potential criminals while others think that this policy is demoralizing. Our group is interested in analysing and manipulating the Stop and Frisk data of New York City from a specific range of years. We will use better predictive modelling techniques and evaluation methods on these incident reports to improve the safety of people in New York. The dataset our group will be using for the Capstone project is called the New York Police Department Stop-and-Frisk Policy Report provided on the Data Analysis and Social Inquiry Lab website of Grinnell College. The dataset contains information regarding the stops related to the stop-and-frisk program in New York City documented by the police officers from 2003 to 2015. Information such as the suspect’s gender, race, and the actions conducted by the police officers, and the reasons for the actions are presented in the dataset. The dataset consists of 12,012 rows and 31 columns. Within the 31 variables, there are 28 numerical variables and 3 categorical variables.