911 Calls Data Analysis

This project involves analyzing 911 calls data to uncover patterns, trends, and insights that can help improve emergency response services. The analysis includes data cleaning, exploratory data analysis (EDA), time series analysis, geospatial analysis, and predictive modeling.

Tools and Technologies

• Python
• Pandas
• Matplotlib and Seaborn

Key Findings

• Call Distribution: Analysis of the distribution of 911 calls by type, time, and location.
• Peak Hours: Identification of peak hours for different types of emergencies.

Getting Started

Prerequisites

• Python 3.x
• Jupyter Notebook

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/911-calls-data-analysis.git
   cd 911-calls-data-analysis

2. Install the required packages:

   pip install -r requirements.txt

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Pandas
• Matplotlib
• Seaborn
• Jose (Python for Data Science and Machine Learning)