alessandrob1-star/ibm-final-project-airbnb-data-analysis-2023

# Airbnb New York City - Exploratory Data Analysis    **Final Capstone Project** | IBM Programme in Data Analytics ## 📋 Project Overview This project presents a complete **Exploratory Data Analysis (EDA)** of the Airbnb market in New York City. Starting from a raw dataset, the analysis includes data cleaning, preprocessing, visualization, and the extraction of meaningful business insights regarding pricing patterns, room types, and neighbourhood performance. ## 🎯 Objectives - Assess data quality and perform thorough cleaning (missing values, duplicates, inconsistencies) - Standardize column names and data formats - Analyze pricing dynamics across room types and boroughs - Identify the most active and profitable neighbourhoods - Extract actionable insights for hosts and market stakeholders ## 🛠 Tools & Technologies - **Python** - **Pandas** & **NumPy** — Data manipulation - **Matplotlib** & **Seaborn** — Data visualization - **Jupyter Notebook** ## 📈 Key Insights - **Queens** surprisingly shows the highest average listing price, followed by Bronx and Brooklyn. - **Entire homes/apartments** are significantly more expensive than private and shared rooms. - Extremely strong positive correlation (**~0.99**) between `price` and `service_fee`. - Listings are heavily concentrated in a few popular neighbourhoods (Williamsburg, Bedford-Stuyvesant, Harlem, etc.). - The dataset was relatively clean after preprocessing, with no extreme price outliers detected. ## 📜 Certification **IBM Programme Data Analytics** - Final Project  [View Credly Badge](https://www.credly.com/badges/94cd09c5-fbca-466d-b6a5-b38ac423fbeb/linked_in?t=s3wbqe) ## 👤 Author **Alessandro Benevelli** **Feel free to explore the notebook and reach out if you have any questions!**