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Airbnb Data Analysis Project

This project uses Docker to create a PostgreSQL database environment to analyze an Airbnb dataset. The project includes loading data from a CSV file into the database and running SQL queries to answer specific questions and a Python script that create the tables and columns with their respective data types automatically. Then the same script load the data from a CSV file into the database.

Project Structure

  • tableandcolumns.py: Python script to load data from a CSV file into a PostgreSQL database and display the table structure.
  • airbnb.csv: CSV file containing Airbnb listings data.
  • airbnb-queries.sql: SQL file containing 20 queries to analyze the data.
  • .env: Environment file storing database credentials.

Requirements

  • Docker
  • Python 3
  • PostgreSQL
  • Python libraries: pandas, sqlalchemy, dotenv

Setup

  1. Clone the repository:

    git clone https://github.com/your-username/airbnb-analysis.git
cd airbnb-analysis

  2. Create and configure the Docker container with PostgreSQL:

    docker run --name airbnb-postgres -e POSTGRES_PASSWORD=yourpassword -d -p 5432:5432 postgres

  3. Configure the .env file with your database credentials:

    DB_HOST=localhost
DB_PORT=5432
DB_NAME=airbnb
DB_USER=youruser
DB_PASSWORD=yourpassword

Usage

  1. Run the tableandcolumns.py script to load the data into the database:

    python tableandcolumns.py

    This script will:

    • Load data from the airbnb.csv file into a PostgreSQL table called airbnb_listings.
    • Display the column names of the table.

  2. Execute the SQL queries in the airbnb-queries.sql file to analyze the data:

    Connect to the PostgreSQL database and run the queries:

    psql -h localhost -U youruser -d airbnb -f airbnb-queries.sql

SQL Queries

The airbnb-queries.sql file contains 20 SQL queries to analyze the Airbnb data. Some of the included queries are:

  • Count the total number of listings.
  • Count the number of listings by neighborhood.

Add your own queries for more detailed analysis.

Contributions

Contributions are welcome. Please open an issue or a pull request to discuss any changes you would like to make.