Consumer Price Index (CPI) Network Analysis using Python & Graph Theory

This video presents our Discrete Mathematics project on CPI (Consumer Price Index) Network Analysis. In this project, we analyze relationships between different consumer items based on their price change patterns across multiple cities over a period of three years. Using graph theory, items are represented as nodes and similarities in price behavior are represented as edges. We used Python libraries such as pandas, NumPy, NetworkX, and scikit-learn to preprocess the data, compute cosine similarity, and construct both unweighted and weighted graphs.