Python libraries and custom functions
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python libraries are pre-written sets of functions and tools that help developers perform common tasks efficiently. there are many libraries available in python for various purposes, such as data manipulation, web scraping, machine learning, and more. these libraries can be installed using package managers like `pip`.
some popular python libraries include:
1. `numpy`: for numerical computing with arrays and matrices.
2. `pandas`: for data manipulation and analysis.
3. `matplotlib` and `seaborn`: for data visualization.
4. `requests`: for making http requests.
5. `scikit-learn`: for machine learning algorithms.
6. `beautifulsoup`: for web scraping.
7. `flask` and `django`: for web development.
in addition to using existing libraries, you can also create custom functions in python to encapsulate certain pieces of functionality that you may need to reuse. custom functions can take input parameters, perform certain operations, and return results.
here's an example of defining a custom function in python:
in this example, we define a custom function `calculate_circle_area` that takes the radius of a circle as input, calculates the area using the formula πr^2, and returns the result. we then use this function to calculate and print the area of a circle with a radius of 5.
custom functions can help you write more modular and reusable code in python, making your programs easier to read and maintain.
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