Big Data Analysis

Academic Year $2023-2024$

Excel Application $2-$ PCA

In $2010,$ the New York Magazine published an article that discussed the most livable neighborhoods in New York. $50$ neighborhoods were evaluated based on $12$ variables, or $12$ broad categories:

Affordability $($as measured on a price$-$per$-$square$-$foot basis, for both renters and buyers$)$

Transit and proximity $($commute times to lower Manhattan and midtown, the density of subway coverage$)$

Shopping and services $($the number of neighborhood amenities, especially supermarkets$)$

Safety $($as measured by violent$-$ and nonviolent$-$crime rates$)$

Food and restaurants $($judged by density and quality of options$)$

Public schools $($test scores and parent satisfaction$)$

Diversity $($in terms of both race and income$)$

Creative capital $($arts venues as well as the number of residents engaged in the arts$)$

Housing quality $($historic districts, code violations, cockroaches$)$

Green space $($park and waterfront access, street trees$)$

Wellness $($noise$,$ air quality, overall cleanliness$)$

Bars and nightlife

Goal: The goal of this exercise is to understand how these different variables are related, and to better understand the similarities between all observations by making use of Principal Component Analysis.

Required files$/$data $($see K$2)$:

The Excel macro: "pca$\_$macro.xlsm$"$

The Excel data$-$file: $"$NY$\_$Neighborhoods.xlsx$"$

Course slides

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