Assignment for OCBCHack-IT - Data & AI Track
● Use the US Traffic 2015 Dataset, publicly available on Kaggle, to visualise the traffic patterns.
● This assignment aims to clean and analyse the dataset, create appropriate models and visualise them using the proper software.
● Use the appropriate algorithms and models to find out the top 5 most obvious patterns from this data.
● Support your hypotheses with appropriate data.
● Submit a Jupyter Notebook with the data models.
● Good commenting and Documentation is essential.
● Explain why you chose this particular model for solving the problem.
● Create a new Git repo where you will upload the relevant project files.
● The analysis and models are available in the "US Traffic 2015 Analysis.ipynb" Jupyter notebook.
● Clone the repository in your local folder and install dependencies numpy, pandas, matplotlib, statsmodels & pmdarima.
● Run the cell for import of all the required modules first.
● Download the "dot_traffic_2015.txt" & "dot_traffic_stations_2015.txt" files from https://www.kaggle.com/jboysen/us-traffic-2015.
● Run the read csv cells to import the data into pandas dataframe.
● Go through each cell of the notebook serially as some dataframes are created in upper cells and referenced in lower cells.
● Additional visualizations used in initial analysis are available in Tableau Public Dashboard https://public.tableau.com/app/profile/adhir.kirtikar/viz/OCBCHackIT/USTraffic2015