The East-Coast Dataopen hosted by Citadel and Correlation One is an invite-only Datathon featuring university students across the east coast. The event started on the 21st of March and ended on the 28th, lasting about a whole week. I was in a team of two where we analyzed the non-conventional indicators and instigators of traffic. We posed the following question: "How would investments in businesses and education affect traffic and road safety in major American cities?"
In this report, we analyzed datasets and later created recommendations for which non-conventional areas municipal governments should invest in to reduce traffic congestion. The three cities of focus were New York, NY, Austin, TX, and Washington, DC. We analyzed publicly available data on 311 calls, building permits, business licenses, population education level and traffic congestion statistics.
Our final submission is in the corresponding directory, but the project has been split up to allow for better readability. The data directory includes all the datasets that were used in this report. The Jupyter Notebooks can be downloaded and run if the datasets are put in the proper directories as indicated on the first cell of each notebook, where the data is loaded.
- Download Anaconda to run the file
- Download pandas to manipulate and analyze the data
- Download plotly and seaborn to visualize the graphs for the data
Anaconda can be downloaded off the following link: https://docs.anaconda.com/anaconda/install/windows/
To install seaborn, run any of the following commands in the command prompt:
> pip install seaborn
> conda install seaborn
To install plotly, run any of the following commands in the command prompt:
> conda install -c plotly plotly
> conda install -c plotly/label/test plotly
Pandas already comes installed with Anaconda.
- Open Anaconda, then Jupyter Notebook
- Open the file and run the code whilst ensuring that the datafiles are in the correct directory
- Pandas - Tool used for data analysis
- Plotly - One of the visualization frameworks used
- Seaborn - The other visualization framework used
- Miles Zaman - Co-Author - mhzaman-cs
- William Harkless - Co-Author
This project is licensed under the MIT License - see the LICENSE.md file for details