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Data-Science-For-Smart-Cities

This project examines NYC Subway accessibility using principal component analysis and clustering techniques.

Description

The New York City Subway is an intricate network that serves as the lifeline for millions of New Yorkers every day. Understanding its accessibility across different neighborhoods is crucial for urban planning, transportation, and ensuring equitable access for all. This project delves deep into this aspect, employing principal component analysis (PCA) and clustering techniques to provide insights into the Subway's accessibility across NYC neighborhoods.

Data Sources

The data for this analysis is available in my repo folder and it encompasses various metrics related to the NYC Subway system and its accessibility across different neighborhoods.

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This project examines NYC Subway accessibility using principal component analysis and clustering techniques.

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