Crime Data Analysis System

A powerful crime data analysis tool designed to explore, visualize, and predict crime trends using Python and data science techniques.

Features

• Data Preprocessing – Cleans and structures raw crime data.
• Exploratory Data Analysis (EDA) – Provides insights into crime patterns, frequency, and trends.
• Geospatial Analysis – Maps crime hotspots using GIS tools.
• Predictive Modeling – Uses machine learning to forecast future crime trends.
• Interactive Visualizations – Generates charts and graphs for better understanding.

Technologies Used

• Programming Language: Python
• Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, Folium

Installation

1. Clone the repository:

   git clone https://github.com/chan9an/crime-prediction.git
   cd crime-data-analysis

2. Run the project:

   python main.py

Usage

1. Upload crime data in CSV format.
2. Run analysis scripts to generate insights.
3. Visualize data using built-in dashboards.

Dataset

-Dataset is already provided in the repository.

• The project uses publicly available crime datasets. You can download them from Kaggle or government crime data portals.

If you have a GIF or images, replace "path/to/your-gif.gif" with the actual file path or URL. Let me know if you need modifications! 🚀