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.
- 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
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Clone the repository:
https://github.com/praveendecode/Airbnb_Analysis -
Install required packages:
pip install -r requirements.txt -
Run the Streamlit app:
streamlit run app.py -
Access the app in your browser :
http://localhost:8501 -
Visit Tableau Dashbord : Visit Dashboard
- 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.
- 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
- 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.