First and foremost, welcome! 🎉 Willkommen! 🎊 Bienvenue! 🎈
Thank you for visiting the HomeScope
project repository. This README file is a hub that provides essential information about our project. Feel free to jump straight to one of the sections below, or simply scroll down to learn more.
Our HomeScope
team, comprised of adept developers and data scientists, is driven by a shared passion for inclusivity and technology. Our expertise in data analysis underpins our commitment to this project.
HomeScope
is an analytical platform dedicated to illuminating the real estate market's complexities. Aimed at stakeholders such as investors, developers, market analysts, and urban planners, it provides actionable insights through the careful analysis of pivotal variables influencing property values.
As a data analytics team within a real estate development company, we strive to provide our target audience with a comprehensive tool that elucidates the various determinants of property prices.
The real estate domain is intricate, often characterized by opaque market dynamics. There's a pronounced need for transparency, especially for under-represented groups seeking equitable access to market insights.
With HomeScope
, you can explore market trends, compare housing attributes across cities, and view real-time price distributions, all through an interactive and intuitive interface.
Our HomeScope
dashboard is an empowering tool that enables:
- The exploration of housing data with customizable features and filters.
- Community-driven contributions to our database, fostering growth and inclusivity.
- The synthesis of valuable insights to facilitate well-informed real estate decisions.
The current iteration of HomeScope
boasts:
- Interactive filters for localized real estate data analysis.
- Correlative bar plots that elucidate the influence of property features on pricing.
- An interactive map to visualize geographical data and price distributions.
- A table with an implemented price range slider for interactive filtering.
We are poised to refine HomeScope
further, enhancing its interactivity and user interface. Our ambitions include the integration of advanced predictive analytics and the expansion of our dataset to encompass global markets.
Encountered an issue or have a question? Feel free to open an issue in this repository, and our team will be happy to assist you.
Our project is a collaborative endeavor, with each team member playing a pivotal role:
Our analysis is anchored in a robust dataset, Canadian house prices for top cities
, obtained from Kaggle
. You can find it here.
The HomeScope
codebase is MIT licensed, as found in the LICENSE in this repository.
To run HomeScope
locally:
-
Clone the Repository
Clone the repository using Git:
git clone git@github.com:UBC-MDS/DSCI-532_2024_5_HomeScope.git
-
Navigate to the Project Directory
Change into the project directory:
cd DSCI-532_2024_5_HomeScope
-
Create a Conda Environment
Create a Conda environment named 532_HomeScope using the environment.yaml file. This file contains all necessary dependencies:
conda env create -f environment.yaml
-
Activate the Conda Environment
Activate the newly created environment:
conda activate 532_HomeScope
-
Run the Application
Start the application with the following command:
cd src
python app.py
This will launch the application, typically at http://127.0.0.1:8050/ in your web browser.
Dive into HomeScope
and join us in forging a more transparent and inclusive real estate landscape.Your contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. Please read our Contribution Guidelines for details on our code of conduct and the process for submitting pull requests to us.
Thank you so much (Danke schön! Merci beaucoup!) for visiting our project. We hope you'll join us on this exciting journey to empower stakeholders in the real estate sector with HomeScope.
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