AirBnB Listing Analysis

AirBnB Listing Analysis Project Overview

This quick guided project analyzes AirBnB listings in Paris to assess the impact of 2015 regulations. These regulations aimed to limit the number of properties listed, responding to the platform's growing popularity. The objective is to visually summarize factors affecting pricing and evaluate how these regulations influenced the Paris market.

Objectives:

• Data Exploration and Profiling: Address any data quality issues.
• Data Preparation: Reformat and optimize the data for visualization.
• Data Visualization: Identify key insights and provide recommendations.

Methodology:

• Data Filtering: Focus on Paris listings and relevant columns.
• Data Optimization: Adjust data types for efficiency.
• Handling Missing Values: Proceed without additional manipulation due to minimal missing data.
• Anomaly Removal: Exclude zero accommodation entries to ensure accurate analysis.

Key Insight:

The visualization shows that as new host numbers increase, average prices drop, and vice versa. This aligns with supply and demand theory, suggesting the 2015 regulations reduced new hosts and led to higher average prices. While the analysis doesn't control for all variables (i.e., not discussed are the effects of the COVID pandemic, which can be seen starting in 2020), the trend indicates the regulation's significant market impact.

Conclusion:

The 2015 regulations likely caused a substantial drop in new hosts, contributing to a steady rise in average prices. This project highlights the regulatory effects on market dynamics and sets the stage for further analysis of other influencing factors.