Analysis

This section outlines the procedures involved in acquiring, formatting, and analyzing the data for our study. We delve into the methodologies adopted for data collection, explore the nuances of the data cleaning process, and discuss the insights gleaned from visualizing the data in the context of Philadelphia.

The analysis is methodically segmented into four distinct sections:

Methods

This segment offers a detailed explanation of the techniques employed and how they were integrated to develop comprehensive neighborhood amenity profiles and clusters. It serves as a foundational overview of our analytical approach.

Data Preparation

Here, we describe the process of gathering data from the Yelp API and Zillow, complemented by supporting source code. This section is crucial for understanding the initial stages of data collection and the preliminary steps taken to ensure data quality and relevance.

Exploratory Analysis

Focusing on the core of our analysis – amenity classification – this section presents various visualizations and provides a preliminary discussion on the types of businesses identified. It includes an initial cluster analysis of these businesses and the spatial units they occupy. Additionally, this part explores the correlations between amenity frequencies and their general distribution patterns, offering a deeper insight into the urban amenity landscape.

Zillow Description Cross-Reference

In this section, we illustrate how descriptions from Zillow listings were used in conjunction with Yelp data. A notable feature is a sample cluster analysis of Philadelphia neighborhoods, suggesting how different areas might be characterized based on their amenities. It’s important to note that the Zillow data integration is not as extensive as that of Yelp. However, it serves as a valuable proof of concept for future research, demonstrating the potential of cross-referencing larger datasets and the importance of effectively communicating the insights derived from such analyses.