Police Call Prediction Based on Weather

This project analyzes the relationship between weather conditions and police call volumes using linear regression and gradient boosting techniques.

Data Introduction

The data used in this project includes police call data obtained from the San Jose CA Open Data Portal and weather data collected from the VisualCrossing Weather Data & API. The police call dataset contains information about individual calls made to the police department, while the weather dataset provides daily weather information.

• Police Call Dataset: https://data.sanjoseca.gov/dataset/police-calls-for-service/resource/
• Weather Dataset: https://www.visualcrossing.com/weather-data

Code and File Structure

• PoliceCalls_PreProcessing.ipynb: Jupyter Notebook containing the preprocessing of police calls data.
• Weather_PreProcessing.ipynb: Jupyter Notebook containing the preprocessing of weather data.
• Linear_Regression.ipynb: Jupyter Notebook containing the linear regression model.
• Gradient_Boosting.ipynb: Jupyter Notebook containing the gradient boosting model.
• README.md: This README file.

How to Run

To run the analysis, follow these steps:

1. Clone this repository to your local machine.
2. Open Linear_Regression.ipynb, Gradient_Boosting.ipynb in Jupyter Notebook and execute the code cells.