README.txt

# Chicago Crime Data Analysis and Visualization

This package contains files for the CS6242 final project titled **"Chicago Crime Data Analysis and Visualization"**. The project leverages Python notebooks to analyze and visualize crime data in Chicago. It includes scripts for generating plots, preparing datasets for geographical analysis using GIS tools, and performing predictive analysis to uncover relationships between crime variables and socio-economic factors. 

The analysis aims to provide insights into crime patterns in Chicago, identify correlations among relevant crime and socio-economic variables, and enable geographical visualization. By combining statistical analysis, machine learning techniques, and data visualization, this project offers a comprehensive approach to understanding the dynamics of crime in urban environments.

All final analysis is put together into an interactive Tableau dashboard with four main tabs, emphasizing an intuitive UI/UX experience. This tabbed format ensures users can easily navigate the dashboard, knowing exactly where to go and what to click, creating a seamless, one-stop resource for exploring Chicago crime data. Additionally, Tableau's tooltip feature enhances the user experience by allowing them to drill down into more detailed information and address potential questions as they interact with the plots. You can view the Tableau dashboard by following [this link](https://bit.ly/cse6242_team79).

## Installation

To use the code in , you need to have the following Python libraries installed:

- `numpy`
- `pandas`
- `sklearn`
- `matplotlib`
- `jupyter notebook`

You can install them using pip:

```pip install numpy pandas scikit-learn matplotlib notebook```

## Execution

To run the analysis, follow these steps:

1. **Launch Jupyter Notebook** by running:
   ```bash
   jupyter notebook

2. **Open the `analysis.ipynb` file from the browser interface.**

3. **Run all cells in the notebook sequentially:**

   - This will generate plots.
   - Prepare datasets for GIS.
   - Perform the analysis and predictions.

4. **Explore the outputs and visualizations in the notebook for detailed insights.**

5. **The notebook contains clear explanations for each step, making it easy to follow along.**