CRIME ANALYSIS USING PYTHON

Project Description

The main objective of the project was to conduct Exploratory Data Analysis on crime data from 2015 to 2018 in order to grasp crime trends and patterns. The analysis encompassed data preparation, exploratory data analysis, and in-depth investigations into specific research inquiries. Through the examination of annual crime rates, daily and hourly crime incidents, and crime trends during specific hours, the goal was to offer valuable insights for law enforcement and policymakers. The project also took into account factors like types of crimes, geographical locations, and statistical significance to enrich the comprehension of crime dynamics. For the analysis, the project utilized pandas, matplotlib, and seaborn.

Project Link

#Top10offensegroups
offense_group_vals=crime.OFFENSE_CODE_GROUP.value_counts()[:10]

display(offense_group_vals/crime.shape[0])

(offense_group_vals/crime.shape[0]).plot(kind="bar");
plt.title("Top 10 Offense Groups(as % of all crimes)");