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Data Science Salaries - Predicting Salaries with Python

Python notebook for salary prediction with Kaggle dataset + machine learning models.
This project explores data science salaries using Kaggle’s dataset with Python and machine learning models.
👉 Full annotated notebook available here: Buy on Gumroad

📘 Contents

  • Data Science Salaries Python Notebook.ipynb: The main Python notebook
  • ds_salaries.csv: The underlying dataset used for analysis and model training

⚙️ How to Open the Notebook

To run the .ipynb file, you’ll need:

  • Python 3.7+
  • Jupyter Notebook or JupyterLab

Installation Steps

  1. Go to Anaconda Download
    • Jupyter Notebook is part of Anaconda.
  2. Click Get Started
  3. Sign in using your Google account, if required.
  4. Download the installer for your operating system (Windows, Mac, or Linux).
  5. After installation, open Anaconda Navigator from your Start Menu or Applications folder.
  6. Additional installations required: xgboost, scipy, and sklearn.tree are not included with Anaconda. You can install them using the following command in the command prompt: pip install xgboost scipy scikit-learn
  7. In Anaconda Navigator, click “Launch” under Jupyter Notebook
  8. Your browser will open with the Jupyter interface. Navigate to the file Data Science Salaries Python Notebook.ipynb and start exploring. No additional installations needed - required libraries like pandas, numpy, and scikit-learn are already included with Anaconda.