crime-data

Visualization and download tools for exploring the FBI’s Uniform Crime Reporting (UCR) data

Moved to https://github.com/fbi-cde

A Los Angeles Times analysis of serious assaults misclassified by LAPD

A Los Angeles Times analysis of arrests of the homeless by the LAPD

Crime detection in cctv footage using deep learning

🚓 Crime dataset for the City of Buenos Aires, Argentina

RESTful API service providing Uniform Crime Reporting (UCR) data for the United States

Association Rule Mining from Spatial Data for Crime Analysis

R package for accessing data from the Crime Open Database

Exploring public Chicago crimes data set in Python

Open crime data from US cities in a harmonised format

Research Project I completed under Dr Vinti Agrawal at BITS Pilani.

This book introduces the programming language R and is meant for undergrads or graduate students studying criminology. R is a programming language that is well-suited to the type of work frequently done in criminology - taking messy data and turning it into useful information. While R is a useful tool for many fields of study, this book focuses on the skills criminologists should know and uses crime data for the example data sets.Notes for using R in criminology research

This repository contains the script and figures of the conference paper selected for presentation at the Latin American Conference of Computationa Intelligence 2018. The abstract of the paper is as follows: Crime is an important social and economic problem of South Africa. Though certain categories of crimes are of serious proportions, yet on aggregate the overall crime situation in the country has considerably improved in the last decade or so. A number of previous studies across other countries have shown a positive or negative relationship between crime and economic growth. On a microeconomic/provincial scale, this paper studies the relationship between various categories of crimes and economic growth using the non-linear modeling technique of Generalized Additive Models. Such a modeling approach helps in understanding how various categories of crimes complexly affect GDP.

Crime Investigation - Explore connections in crime data using the POLE - Person, Object, Location, Event - model in a public dataset from Manchester, U.K.

This Problem Data set of San Francisco Contains information about the crime in San Francisco, We are going to analyze the data, Visualize the data using folium maps for geographical understanding. In other words It is called Geo spatial Mapping. This Problem is the final assignment for Coursera and IBM's Data Visualization Course.

Data Mart based on Vancouver and Denver crimes data

Visualizing crime in Edmonton

Analyzing and forecasting crime in Mexico (Project done as part of a course at UChicago - Winter 2017)

a cli for searching interpol's red notice list

Dades delinqüencials Catalunya segons Àrees Bàsiques Policials

Contrary to the general belief that crimes happen at night or dark, in the nations capital most offenses or crimes happen during the evening.The Lab @ DC Consulting Project

An open-source tool that retrieves information from the FBI Wanted Persons Program, this includes lists of wanted criminals, unidentified victims, etc.

Historical data on crime in Los Angeles from 1988-2014 as scanned from the Los Angeles Public Library Archive and from LAPD incident files

Look at American crime data from the UCR (1960-2016)

Final Project for a computer Science course.

Analysis of the violence and local business in the city of Tijuana

👮 Crime Reports UK is the app for open-data about crime and policing in England, Wales, and Northern Ireland.

This is Project on Visualizing the Crime Data (2017-2019), taken from "Crime in India-Volume 1" from NCRB.

Unsupervised machine learning using U.S. crime data and k-means clustering. Crime categories: murder, assault & rape in all 50 states in 1973.