Python Packages

In Python, a package is a way to organize and group related modules together in one folder. Think of a package like a toolbox with compartments — each compartment (module) handles a specific task, and together they help manage large projects cleanly.

Where a module is just a .py file, a package is a folder that contains multiple modules and must have a special file called __init__.py. This file tells Python that the folder should be treated like a package.

Why Use Packages?

As your Python project grows, organizing it into multiple files (modules) and folders (packages) makes it easier to maintain, reuse, and share your code.

Popular Python Packages

Python provides many useful packages that are widely used in data science, machine learning, statistics, and visualization:

NumPy – For working with arrays and performing numerical operations.
Pandas – For handling data in table-like structures.
Matplotlib – For plotting graphs and charts.
Seaborn – For statistical data visualization.
SciPy – For scientific computations.
sklearn (scikit-learn) – For building machine learning models.

We’ll explore these packages in detail later in this course.

Summary

A package is a folder containing one or more Python modules.
It helps organize large projects and reuse code.
Packages like NumPy, Pandas, and Matplotlib are essential tools in many Python projects.