This project is designed to assist Maryland’s Department of Public Safety in analyzing crime trends, patterns, and potential hotspots. Check it out on GitHub Here

SafeMaryland: Maryland Crime Data Analysis (1975-2020)

Overview

Welcome to the SafeMaryland repository. This project focuses on analyzing historical crime data in Maryland from 1975 to 2020. The goal is to identify trends, patterns, and hotspots to inform strategic planning for crime reduction, aiming to decrease overall crime rates by 10% within the next five years.

Project Features

• Trend Analysis: Evaluate crime rate trends across Maryland over the past decades.
• Crime Distribution: Determine the most common crime types and their distribution changes over time.
• Geographical Analysis: Identify jurisdictions with the highest and lowest crime rates compared to the state average.
• Population Correlation: Investigate the relationship between population size and crime rates in various areas.
• Crime Rate Changes: Highlight the most significant increases or decreases in different types of crimes.
• Crime Hotspots: Locate areas with high crime concentrations for targeted interventions.

Repository Structure

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SafeMaryland/
├── .ipynb_checkpoints/
│   ├── cleaned_MD_Crime_Data-checkpoint.html
│   ├── profiling&cleaning-checkpoint.ipynb
├── cleaned_MD_Crime_Data.html
├── Crime Distribution.ipynb
├── Crime Hotspots.ipynb
├── Crime Rate Changes.ipynb
├── data/
│   ├── cleaned_MD_Crime_Data.csv
│   ├── MD_Crime_Data.csv
├── Geographical Analysis.ipynb
├── main.py
├── Population Correlation.ipynb
├── profiling&cleaning.ipynb
├── requirements.txt
├── simple.ipynb
├── Trend Analysis.ipynb

The main file is a Streamlit app.

Streamlit App

Explore our interactive Streamlit app to gain insights and support strategic decision-making for crime reduction in Maryland.

Acknowledgment

We acknowledge Data in Motion for providing this challenging crime analysis project and the opportunity to showcase data visualization techniques.

Getting Started

To get started with the project, clone the repository and install the required dependencies listed in requirements.txt.

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git clone https://github.com/Mohammed-Mebarek-Mecheter/Data-in-Motion.git
cd SafeMaryland
pip install -r requirements.txt

Usage

Explore the Jupyter notebooks for detailed analysis:

• profiling&cleaning.ipynb
• Trend Analysis.ipynb
• Crime Distribution.ipynb
• Geographical Analysis.ipynb
• Population Correlation.ipynb
• Crime Rate Changes.ipynb
• Crime Hotspots.ipynb

Author

• LinkedIn: Mohammed Mebarek Mecheter
• Email: mohammedmecheter@gmail.com