Moha-cm / Airbnb-Data-Analysis

Airbnb Data retrival from MongoDb and Analying the Data

Airbnb Data Analysis Project

Overview This project aims to analyze Airbnb data using MongoDB Atlas, perform data cleaning and preparation, develop interactive geospatial visualizations, and create dynamic plots to gain insights into pricing variations, availability patterns, and location-based trends. The objectives are to:

1. Establish MongoDB Connection:

Connect to MongoDB Atlas to retrieve the Airbnb dataset. Ensure efficient data retrieval for analysis.

2. Data Cleaning and Preparation:

Address missing values, duplicates, and perform data type conversions for accurate analysis.

3.Develop Streamlit Web Application:

Create a user-friendly web application using Streamlit. Include interactive maps showcasing the distribution of Airbnb listings. Allow users to explore prices, ratings, and other relevant factors.

4.Visualization:

using dynamic plots and charts.Explore variations based on location, property type, and seasons.

6.Interactive Visualizations:

Create interactive visualizations that enable users to filter and drill down into the data.

Required Python Packages

To install the packages in python

pip install streamlit pymongo pandas plotly

MongoDB Setup:

1.Create a MongoDB AtlasAccount

2.Set Up a Cluster

3.Load the Airbnb Sample Data

4.Import Sample Data

Set up a MongoDB Atlas account and obtain connection details.

Streamlit Web Application:

Explore the dynamic plots and charts generated by running

streamlit run ./home.py