Python

What: Python is a versatile programming language known for its simplicity and readability. It offers a vast ecosystem of libraries and frameworks for various purposes, including data analysis, machine learning, web development, and automation.

When:

• Use Python for data analysis, manipulation, and machine learning tasks.
• Python’s extensive libraries such as Pandas, NumPy, and SciPy make it suitable for handling and analyzing large datasets efficiently.
• Python is commonly used in web development, scientific computing, and automation projects.

Access: Free! You can download write your code online on Google Colab. If you want a more powerful development environment, download Python here and try Spyder or the classic Jupyter notebook.

Example: Splitting a dataset into testing and training sets.

  
    # Fit and transform the training data
    X = column_transformer.fit_transform(X)
    X = X.drop(['HbA1c_level', 'blood_glucose_level'])
    # Split the dataset into 75% train and 25% test, stratifying based on y
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, stratify=y)