Saved searches
Use saved searches to filter your results more quickly
Cancel Create saved search
Sign up Reseting focus
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session.
Airbnb Data Analysis and Visualization project is a comprehensive data exploration and presentation effort. It involves data collection, preprocessing, ETL work, and the creation of an interactive Streamlit user interface. The project aims to provide insights and make Airbnb data more accessible and understandable.
Notifications You must be signed in to change notification settings
praveendecode/Airbnb_Analysis
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Go to file
Folders and files
Last commit message
Last commit date
Latest commit
History
View all files
Repository files navigation
Airbnb Data Analysis and Visualization

Overview
The Airbnb Data Analysis and Visualization project is a comprehensive data exploration and presentation effort. It involves data collection, preprocessing, ETL work, and the creation of an interactive Streamlit user interface. The project aims to provide insights and make Airbnb data more accessible and understandable.
Features
- Data Collection: Gathered Airbnb data from various sources, including MongoDB.
- Data Preprocessing: Cleaned and prepared the data for analysis.
- ETL (Extract, Transform, Load): Converted data from MongoDB to structured DataFrames.
- Exploratory Data Analysis (EDA): Performed in-depth analysis and visualization of Airbnb data.
- Interactive Streamlit UI: Developed a user-friendly interface for data exploration and presentation.
- Tableau Dashboard : Interactive eye-catching dashboard with awesome filter
Getting Started
- Clone the repository:
https://github.com/praveendecode/Airbnb_Analysis
pip install -r requirements.txt
streamlit run app.py
http://localhost:8501
Methods
- Data Collection: Web scraping, API access, database queries.
- Data Preprocessing: Data cleaning, handling missing values, feature engineering.
- ETL Work: MongoDB data extraction, data transformation using Pandas.
- EDA: Visualization with Matplotlib, Seaborn, and Plotly.
- Streamlit UI: Streamlit library for building interactive web applications.
Skills Covered
- Data collection and integration.
- Data cleaning and preprocessing.
- ETL techniques for data transformation.
- Exploratory Data Analysis (EDA).
- Data visualization.
- Web application development with Streamlit.
- Tableau Public
Results
- The project provides a user-friendly interface for exploring Airbnb data.
- Insights and trends in the Airbnb market are presented through interactive charts and visualizations.
- Data is cleaned, organized, and ready for further analysis.
Connect Through LinkedIn For Queries