Python is an incredibly versatile programming language, with a wide range of tools and modules to perform all sorts of tasks. Among these tasks is the creation of a zero matrix, a matrix in which all elements are zeros. This matrix is quite useful in various computations, especially in linear algebra.

In this tutorial, we will learn how to create a zero matrix in Python using two methods: using simple Python code and using the Numpy module.

### Method 1: Using Pure Python

In this method, we will create the zero matrix using a nested for loop. The inner loop creates a list of zeros for each row. Then, the outer loop creates the matrix by repeating this row as many times as we need. Below is the code snippet for this method:

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def zero_matrix(rows, cols): return [[0]*cols for _ in range(rows)] |

You can call this function by passing the number of rows and columns as parameters:

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print(zero_matrix(3, 3)) |

**Output:**

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[[0, 0, 0], [0, 0, 0], [0, 0, 0]] |

### Method 2: Using NumPy

NumPy is a Python module that provides many functions for numerical computations. One of its functions, `numpy.zeros()`

, is specifically designed to create a zero matrix. Here is how you can use it:

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import numpy as np def zero_matrix_Numpy(rows, cols): return np.zeros((rows, cols)) |

you can call this function by passing the number of rows and columns as parameters:

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print(zero_matrix_Numpy(3,3)) |

**Output:**

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array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]]) |

## Full Code:

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def zero_matrix(rows, cols): return [[0]*cols for _ in range(rows)] def zero_matrix_Numpy(rows, cols): import numpy as np return np.zeros((rows, cols)) print(zero_matrix(3, 3)) print(zero_matrix_Numpy(3,3)) |

## Conclusion

And there you have it! You can now create a zero matrix in Python with ease, whether you’re using pure Python or the NumPy library.

Remember that while creating a zero matrix through pure Python might be a good exercise in understanding how matrices work, in practice, you’ll probably want to use NumPy as it’s designed for handling numerical computations efficiently.