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🏠 Airbnb Regulation Impact (Paris) & Data Analysis

By Shubham Pawar


πŸ“Š Paris Airbnb Listings & Pricing Trends


πŸ“Œ Overview

This project delivers a detailed analysis of Airbnb listing trends and pricing dynamics in Paris, with a focus on the impact of local regulations on the marketplace. The examination tracks changes in supply (number of listings) and demand (price movement) before and after regulatory interventions, uncovering key business implications for short-term rental platforms.


Project Link

AirBnB Impact of Regulations

πŸ› οΈ Tools Used

Jupyter Logo Pandas Logo NumPy Logo Matplotlib Logo Seaborn Logo

Analysis was performed using:

  • Python (Jupyter Notebook)
  • Pandas & NumPy for data manipulation
  • Matplotlib & Seaborn for robust visualizations

πŸ“ Dataset

All analysis was based on the following dataset:
πŸ”— Airbnb Paris Listings & Reviews (Kaggle)

  • File used: listings.csv (includes listing ID, host and location details, room type, pricing, and more).

🎯 Key Performance Indicators (KPIs)

  • 🏠 Total Listings
  • πŸ’΅ Average Price per Night
  • πŸ”„ Listing Growth Rate (Monthly/Yearly)
  • πŸ“‰ Listing Churn (Drop in active listings post-regulation)
  • πŸ“ˆ Post-regulation Recovery (Stabilization of listings)
  • 🧾 Distribution by Room Type & Location

πŸ“ˆ Key Insights

  • Early Growth: Listings and average prices saw a consistent rise during Airbnb’s initial expansion.
  • Regulatory Uncertainty (2015+): Listings dropped noticeably after increased regulatory scrutiny, while average prices climbed with reduced supply.
  • Post-Regulation Stabilization (2019+): Listings rebounded as hosts adapted to new rules, leading to price adjustments amid restored competition.
  • Market Adaptability: The Paris market demonstrated resilience through regulatory cycles, with supply rebounding after an initial disruption.

πŸ” Additional Insights

  • Host Support: Regulatory clarity and platform education reduced host churn and stabilized the market.
  • Pricing Power: Reduced supply temporarily raised average prices, highlighting demand in the core tourist neighborhoods.
  • Comparative Trends: These market behaviors parallel similar regulatory impacts observed in other global cities.

πŸ“š Data Story

  • Regulatory decisions have a clear, measurable impact on both supply and pricing in the short-term rental market.
  • Effective policy adaptation and communication can mitigate disruption and help both hosts and platforms adjust efficiently.

Recommendations:

  • Closely monitor global regulatory signals to anticipate market disruption.
  • Provide clear, proactive support resources for hosts during regulatory changes.
  • Adopt flexible platform policies to swiftly adapt to new market environments.
  • Use regulatory experience in one city to develop compliance playbooks for new markets.

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Data analysis of AirBnB data using Python and its Data Analysis Libraries.

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