New York City traffic can be chaotic, and accidents are unfortunately a common occurrence. CrashLens provides a data-driven approach to understand these accidents, using powerful visualizations and clustering techniques to identify hotspots and uncover valuable insights.
- Data Cleaning : Handling missing values using imputation, dropping irrelevant columns
- Visualizations : Histograms, Pie Charts, Line Plots, Scatter Plots
- DBSCAN Clustering to Identify Accident Hotspots
- Adaptable to Different Crash Datasets
Ensure you have the following installed on your system:
- Python 3
-
Requirements : This
requirements.txtfile contains all the necessary Python dependencies for the project. Place any additional required dependencies here.Execute
pip install -r requirements.txtto install all the required dependencies.
Simply execute analysis.py {file_name.csv} to generate multiple visualizations of patterns in the data.
All the generated visualizations, including heatmaps, are saved in the results/ directory.
Watch the project in action! Check out the demo video:
Click the image or this link to watch the demo.