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Parameters Return value Examples Basic usage Splitting via slicing Splitting 2D arrays Chop horizontally Chop vertically Slicing

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NumPy | split method

schedule Aug 10, 2023

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Python●NumPy

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Parameters Return value Examples Basic usage Splitting via slicing Splitting 2D arrays Chop horizontally Chop vertically Slicing

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Numpy's split(~) method divides up the input array as per the specified parameters.

Parameters

1. a | array-like

The input array that you want to split.

2. indices_or_sections | int

If an int, n, is given, then the input array will be split up into n equal arrays along the specified axis. To be more precise about where to split up the arrays, provide a 1D array of sorted integers instead.

3. axis | None or int | optional

The axis along which to perform the split. By default, axis=0.

Return value

A list containing the split up Numpy arrays.

Examples

Basic usage


        
        
            
                
                
                    a = np.array([4,5,6,7,8,9])
np.split(a, 2)
                
            
            [array([4, 5, 6]), array([7, 8, 9])]

When the split is not even, then an error is thrown:


        
        
            
                
                
                    a = np.array([4,5,6,7,8])
np.split(a, 2)
                
            
            ValueError: array split does not result in an equal division

Splitting via slicing


        
        
            
                
                
                    a = np.array([4,5,6,7,8,9])
np.split(a, (2,3))
                
            
            [array([4, 5]), array([6]), array([7, 8, 9])]

Here, we're slicing like follows:

Splitting 2D arrays

Consider the following 2D array:


        
        
            
                
                
                    a = np.array([[1,2,3,4],[5,6,7,8]])
a
                
            
            array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

Chop horizontally

To split a by rows:


        
        
            
                
                
                    np.split(a, 2, axis=0)
                
            
            [array([[1, 2, 3, 4]]), array([[5, 6, 7, 8]])]

Chop vertically

To split a by columns:


        
        
            
                
                
                    np.split(a, 2, axis=1)
                
            
            [array([[1, 2],
        [5, 6]]),
 array([[3, 4],
        [7, 8]])]

Slicing

To split a by columns via slicing:


        
        
            
                
                
                    np.split(a, (2,3), axis=1)
                
            
            [array([[1, 2],
        [5, 6]]),
 array([[3],
        [7]]),
 array([[4],
        [8]])]

Here, the columns we obtain are:


        
        
            
                
                
                    first two columns
third column
fourth column

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Published by Isshin Inada

Edited by 0 others

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