This innovative tool utilizes dynamic visualizations to provide a comprehensive analysis of various facets of motor vehicle accidents. It highlights key areas such as the total number of people injured or killed, patterns of collisions based on different times of the day, and identifying the most hazardous streets for different groups like pedestrians, cyclists, and motorists.
Getting Started:
Embark on an insightful journey with our user-friendly Streamlit application. Begin by installing the necessary Python libraries.
Simply execute:
pip install streamlit pandas numpy pydeck plotly
Next, obtain our repository by cloning or downloading it. Ensure you have the 'data.csv' file, containing crucial collision data, placed in the same directory as your script.
Once set up, navigate to your script's directory using the terminal and initiate the Streamlit application with the command: streamlit run your_script_name.py. Don’t forget to replace 'your_script_name.py' with the actual name of your Python script. Launching the command will automatically open a new browser tab where the Streamlit dashboard comes to life.
Usage:
Our dashboard is built with interactive elements to enhance your data exploration experience.
- Investigating Injury and Fatality Cases: Adjust the slider to set a minimum threshold for cases involving injuries or fatalities due to vehicle collisions.
- Analyzing Collision Times: Select an hour using the sidebar slider to scrutinize collision occurrences. The dashboard will further break down the incidents by minute within your chosen hour.
- Access to Raw Data: For those who prefer a deep-dive into the data, we provide an option to view the raw data behind our visualizations.
This Streamlit dashboard is more than just a tool; it's a gateway to understanding the significant impact of motor vehicle collisions in Canada.