How to use numpy function

numpy is a Python library for numerical calculations and data analysis, providing many powerful functions and tools. Introduction to common numpy functions: 1. np.array(), creates an array from a list or tuple; 2. np.zeros(), creates an array of all 0s; 3. np.ones(), creates an array An array of all ones; 4. np.arange(), creates an arithmetic sequence array; 5. np.shape(), returns the shape of the array, etc.

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

Numpy is a Python library for numerical calculations and data analysis. It provides many powerful functions and tools. The following is an introduction to some common numpy functions:

1. Create an array:

np.array(): Create an array from a list or tuple.

np.zeros(): Create an array of all 0s.

np.ones(): Create an array of all ones.

np.arange(): Create an arithmetic sequence array.

2. Array operations:

np.shape(): Returns the shape of the array.

np.reshape(): Change the shape of the array.

np.concatenate(): Concatenate two or more arrays.

3. Mathematical operations:

np.add(): addition operation.

np.subtract(): subtraction operation.

np.multiply(): Multiplication operation.

np.divide(): Division operation.

np.power(): Power operation.

np.sqrt(): square root operation.

np.sin(): Sine function.

np.cos(): Cosine function.

np.exp(): Exponential function.

np.log(): Logarithmic function.

4. Statistical function:

np.mean(): Calculate the average.

np.median(): Calculate the median.

np.std(): Calculate the standard deviation.

np.var(): Calculate the variance.

np.max(): Find the maximum value in the array.

np.min(): Find the minimum value in the array.

5. Array indexing and slicing:

np.shape(): Returns the shape of the array.

np.reshape(): Change the shape of the array.

np.concatenate(): Concatenate two or more arrays.

This is only a small part of numpy functions, there are many other functions and usages. You can learn more detailed information by consulting numpy's official documentation or other tutorials. I hope these simple examples can help you get started using numpy functions.

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