A complete list of commonly used functions in the numpy library

Commonly used functions in the numpy library include numpy.array, numpy.zeros, numpy.ones, numpy.arange, numpy.linspace, numpy.shape, numpy.reshape, numpy.transpose, numpy.split, numpy.add , numpy.subtract, numpy.multiply, numpy.divide, etc.

The operating system for this tutorial: Windows 10 system, Python version 3.11.4, DELL G3 computer.

The numpy library is a Python library for scientific computing that provides a large number of numerical calculations and array operation functions. The following are some commonly used numpy functions:

1. Create an array:

numpy.array: Create a numpy array.

numpy.zeros: Create an array of all zeros.

numpy.ones: Create an array of all ones.

numpy.arange: Create an array that increases by a specified step size.

numpy.linspace: Create an array evenly distributed within the specified range.

2. Array operations:

numpy.shape: Returns the dimensions of the array.

numpy.reshape: Change the shape of the array.

numpy.transpose: Swap the dimensions of the array.

numpy.concatenate: Concatenate arrays along the specified axis.

numpy.split: Split an array into multiple subarrays.

3. Mathematical operations:

numpy.add: Add array elements.

numpy.subtract: Subtract array elements.

numpy.multiply: Multiply array elements.

numpy.divide: Perform division operation on array elements.

numpy.power: Exponentiates array elements.

4. Statistical function:

numpy.mean: Calculate the average of the array.

numpy.median: Calculate the median of an array.

numpy.std: Calculate the standard deviation of an array.

numpy.min: Returns the minimum value of the array.

numpy.max: Returns the maximum value of the array.

5. Array indexing and slicing:

numpy.argmax: Returns the index of the maximum value in the array.

numpy.argmin: Returns the index of the minimum value in the array.

numpy.where: Returns the index of the array element that satisfies the condition based on the specified condition.

numpy.take: Take out array elements according to the specified index.

This is just a small part of the commonly used functions in the numpy library. numpy also provides many other powerful functions and methods. You can consult numpy official documentation or other tutorials to learn more about how to use functions based on your specific needs.

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