##Table of Contents
1.Introduction to Airbnb 2.About the Dataset 3.Python Libraries Used 4.Project Workflow 5.Purpose of the Analysis
Airbnb is a well-known online marketplace that connects people who want to rent out their homes with those looking for accommodations. Established in 2008 by Brian Chesky, Joe Gebbia, and Nathan Blecharczyk, Airbnb has grown to become the leading platform for home-sharing worldwide.
Through Airbnb, hosts can offer their properties—whether homes, apartments, or other spaces—for short-term rentals. Travelers can browse and book these listings, which vary from entire homes to private or shared rooms, accommodating various budgets and preferences. Airbnb is particularly popular among travelers seeking to experience destinations from a local’s perspective rather than as typical tourists. Currently, Airbnb boasts over four million listings in more than 100,000 cities.
Dataset Overview
Number of Instances: 48,895 Number of Attributes: 16 The dataset includes both categorical and numerical values, providing comprehensive information about Airbnb listings. This diverse data can help analyze trends and patterns in the New York City Airbnb market, offering insights into user preferences and behaviors.
The dataset comprises information on Airbnb bookings in New York City for the year 2019. By examining this data, one can identify usage trends and patterns within the NYC Airbnb market.
Pandas
NumPy
Matplotlib.Pyplot
Seaborn
Importing Libraries
Loading the Dataset
Exploring the Dataset
Data Cleaning and Manipulation
Handling Outliers
Data Visualization
Conclusion
The primary goal of this analysis is to understand the factors that influence Airbnb prices in New York City and to identify patterns across various variables. The insights gained will be valuable for both travelers and hosts, providing essential information for making informed decisions. Moreover, the analysis offers strategic insights for Airbnb's business operations in the city.