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https://github.com/AriqF1/prediction_criminal

This repository contains the code and documentation for a crime data analysis project using a criminal dataset from San Francisco.
https://github.com/AriqF1/prediction_criminal

analytics heatmap-visualization jupyter-notebook python

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This repository contains the code and documentation for a crime data analysis project using a criminal dataset from San Francisco.

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README

          

# Crime Prediction (Python)

A crime data analysis project using Python and Jupyter Notebook to visualize **high-crime hours** and **geographical crime density** with interactive heatmaps.

- Dataset: San Francisco Crime Data (884K+ rows)
- Time and location-based heatmap visualization
- Structured preprocessing pipeline
- Data exploration with Pandas & Jupyter Notebook

[![Status](https://img.shields.io/badge/status-active-success)](https://github.com/AriqF1/heatmap_criminal)
[![License](https://img.shields.io/badge/license-MIT-blue)](https://opensource.org/licenses/MIT)
[![Python](https://img.shields.io/badge/python-3.10+-blue)](https://www.python.org/)

## Features

- Preprocessing of crime data from Kaggle
- Duplicate detection and cleaning for large datasets
- Crime frequency analysis by hour and district
- Professional and modular folder structure

## Requirements

- Python 3.10+
- ipynb extension
- Pandas, NumPy, Seaborn, Matplotlib, Jupyter, Folium

## Getting Started

Clone The Repository

```bash
git clone https://github.com/AriqF1/prediction_criminal.git
cd prediction_criminal
```

## Folder Structure

```bash
heatmap_criminal/
├── data/
│ ├── 01_raw/ # Raw data from Kaggle
│ ├── 02_interim/ # Cleaned data
│ └── 03_processed/ # Analysis-ready data
├── notebooks/ # Jupyter Notebooks for EDA & visualization
├── scripts/ # Python scripts for data pipeline
├── visualization/ # Generated heatmaps and charts
├── reports/ # Final analysis, charts, and documentation
├── LICENSE
├── README.md
└── requirements.txt
```