15. Python Packages
Python packages play a crucial role in organizing and reusing code efficiently. They allow developers to access a wide range of powerful tools and libraries that enhance productivity in Python programming, particularly in fields like Artificial Intelligence and Data Science. Additionally, creating custom packages helps streamline code management, ensuring better organization and reusability.
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What we have learnt
- A Python package is a collection of modules used to organize and reuse code.
- Pip is the standard tool for installing Python packages.
- You can import packages into your programs to access various functions and tools.
- Common packages like NumPy, Pandas, and Matplotlib are essential in AI and Data Science.
- You can also create your own packages for better code management.
Key Concepts
- -- Python Package
- A collection of Python modules organized in a directory with an init.py file for easier management.
- -- Pip
- The package installer for Python, used to install and manage software packages written in Python.
- -- NumPy
- A library used for numerical operations and array handling that is efficient for mathematical computations.
- -- Pandas
- A library used for data manipulation and analysis, particularly for structured data like tables.
- -- Matplotlib
- A plotting library for creating static, animated, and interactive visualizations in Python.
- -- Creating Custom Packages
- The process of building your own package by organizing modules and making them reusable.
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