Real Estate Market Analysis in Argentina

Welcome to the Real Estate Market Analysis project for Argentina! This repository is dedicated to providing insights into the current state of the real estate market in Argentina. Through scraping data from "zonaprop," a popular real estate platform, we aim to offer valuable information and analysis regarding apartments for rent.

Overview

The primary objective of this project is to gather comprehensive data on apartments available for rent in Argentina's real estate market. By utilizing web scraping techniques, we collect detailed features and attributes of various apartments listed on "zonaprop." The gathered data serves as a foundation for conducting in-depth analysis and deriving insights into market trends, pricing dynamics, and other relevant factors.

Repository Structure

• main_scrap.py : This Python script serves as the main entry point for initiating the web scraping process. Users can specify their preferences and select the type of buildings they are interested in to gather relevant information. The scraped data is stored in the "output" folder for further analysis.
• output/ : This directory contains the output files generated by the scraping process. Each file corresponds to the data collected for a specific type of building or category.
• jupyter/ : The Jupyter notebook files within this folder are dedicated to the analysis of the scraped data. Through exploratory data analysis (EDA), visualization, and statistical techniques, we delve into the insights derived from the collected real estate data.

Getting Started

To begin exploring the real estate market analysis, follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/MartinBasualdo0/Scrap-alquileres-caba.git

2. Navigate to the project directory:

   cd real-estate-analysis

3. Set up your virtual environment and install dependencies:

   python3 -m venv ./.venv
   source .venv/bin/activate
   pip install -r requirements.txt

4. Run the main_scrap.py script:

   python main_scrap.py

   Follow the prompts to specify your preferences and initiate the scraping process.

5. Once the scraping is complete, explore the collected data in the "output" folder.
6. Utilize the Jupyter notebooks in the "jupyter" folder to perform analysis and gain insights into the real estate market trends in Argentina.

Contributing

Contributions to enhance the functionality, improve scraping techniques, or expand the analysis capabilities are welcome. If you find any bugs or have suggestions for improvements, please feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the [LICENSE]() file for details.

Acknowledgments

We express our gratitude to the developers of "zonaprop" for providing access to valuable real estate data. Additionally, we thank the open-source community for their contributions to web scraping tools and data analysis libraries, which have been instrumental in the development of this project.

Thank you for your interest in the Real Estate Market Analysis project! We hope you find the insights and information provided here valuable and informative. Happy analyzing! 🏠✨