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Parameters Return value Examples Creating an one-dimensional Numpy array Creating a Numpy array of type int Creating a two-dimensional Numpy array Using a tuple Using an array

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NumPy | zeros method

schedule Aug 12, 2023

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Parameters Return value Examples Creating an one-dimensional Numpy array Creating a Numpy array of type int Creating a two-dimensional Numpy array Using a tuple Using an array

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Numpy's zeros(~) method creates a Numpy array with all zeros as its entries.

Parameters

1. shape | int or array-like

The desired shape of the Numpy array. Providing an int would return a one-dimensional flattened array.

2. dtypelink | string or type | optional

The desired data type for the Numpy array. By default, dtype=numpy.float64. If you're sure that the new Numpy array will only contain integers, you should want to specify dtype=int.

Return value

A Numpy array of zeroes, with the shape and type specified by the parameters.

Examples

Creating an one-dimensional Numpy array

To create a flattened Numpy array with 3 zeros:


        
        
            
                
                
                    np.zeros(3)
                
            
            array([0., 0., 0.])

Creating a Numpy array of type int

To create a flattened Numpy array with 3 zeroes of type int:


        
        
            
                
                
                    np.zeros(3, int)
                
            
            array([0, 0, 0])

Creating a two-dimensional Numpy array

Using a tuple

To create a 2 by 3 (i.e. 2 rows and 3 columns) matrix filled with zeros using a tuple:


        
        
            
                
                
                    np.zeros((2,3))
                
            
            array([[0., 0., 0.],
       [0., 0., 0.]])

Using an array

To create a 2 by 3 (i.e. 2 rows and 3 columns) matrix filled with zeros using an array:


        
        
            
                
                
                    np.zeros([2,3])
                
            
            array([[0., 0., 0.],
       [0., 0., 0.]])

Note that you could also use Numpy arrays as well.

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Published by Isshin Inada

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