CaliforniaHousePricing

Copyright and usage notice

Copyright (c) 2026 Siddhant Jadhav. All rights reserved.

This repository is available for portfolio, review, and educational evaluation purposes only. You may view the code, but you may not copy, modify, distribute, or use it commercially without written permission from the author.

---

Software and Tools Requirements

Before getting started, ensure you have the following installed and set up:

• GitHub Account – To host and collaborate on your code repositories.
• Heroku Account – For deploying your web application.
• Visual Studio Code (VS Code) IDE – A lightweight code editor for development.
• Git CLI – To manage version control from the command line.

🔧 Setting Up the Development Environment

You can set up your Python environment using either Conda or venv (built-in Python tool). Choose one based on your preference.

---

📦 Option 1: Using conda (Recommended if Anaconda/Miniconda is installed)

✅ Prerequisites:

• Anaconda or Miniconda installed
• conda command available in terminal

⚙️ Steps:

1. Open terminal inside the project folder:

   cd CaliforniaHousePricing

2. Create a new conda environment:

   conda create -n california-housing python=3.9

3. Activate the environment:

   conda activate california-housing

4. Install required packages:

   # Install data science packages
   conda install pandas numpy matplotlib seaborn scikit-learn jupyter
   
   # Install web framework (if using Flask/Django)
   conda install flask
   
   # Install additional packages via pip if needed
   pip install streamlit plotly

5. Create requirements.txt file:

   conda list --export > requirements.txt

6. Verify installation:

   python --version
   conda list

---

🐍 Option 2: Using venv (Built-in Python Virtual Environment)

✅ Prerequisites:

• Python 3.7+ installed on your system
• python command available in terminal

⚙️ Steps:

1. Open terminal inside the project folder:

   cd CaliforniaHousePricing

2. Create a virtual environment:

   python -m venv california-housing-env

3. Activate the virtual environment:

   On Windows:

   california-housing-env\Scripts\activate

   On macOS/Linux:

   source california-housing-env/bin/activate

4. Upgrade pip:

   pip install --upgrade pip

5. Install required packages:

   pip install pandas numpy matplotlib seaborn scikit-learn jupyter flask streamlit plotly

6. Create requirements.txt file:

   pip freeze > requirements.txt

7. Verify installation:

   python --version
   pip list

---

📋 Required Python Packages

The following packages are essential for the California House Pricing project:

Core Data Science Libraries

• pandas - Data manipulation and analysis
• numpy - Numerical computing
• matplotlib - Data visualization
• seaborn - Statistical data visualization
• scikit-learn - Machine learning library

Web Development (Optional)

• flask - Lightweight web framework
• streamlit - For creating web apps quickly
• plotly - Interactive visualizations

Development Tools

• jupyter - Interactive notebooks
• ipython - Enhanced interactive Python shell