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Using NumPy’s np.arange() Effectively

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NumPy is the fundamental Python library for numerical computing. Its most important type is an array type called ndarray. NumPy offers a lot of array creation routines for different circumstances. arange() is one such function based on numerical ranges. It’s often referred to as np.arange() because np is a widely used abbreviation for NumPy.

Creating NumPy arrays is important when you’re working with other Python libraries that rely on them, like SciPy, Pandas, Matplotlib, scikit-learn, and more. NumPy is suitable for creating and working with arrays because it offers useful routines, enables performance boosts, and allows you to write concise code.

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By the end of this course, you’ll know:

  • What np.arange() is
  • How to use np.arange()
  • How np.arange() compares to the Python built-in class range
  • Which routines are similar to np.arange()

Let’s see np.arange() in action!

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Author: Ho Quang Dai

I am Ho Quang Dai, from Vietnam – A country that loves peace. I share completely free courses from major academic websites around the world. Hope to bring free knowledge to everyone who can’t afford to buy


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