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Parameters Return value Examples 1D array 2D array All values Column-wise Row-wise Specifying a datatype

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NumPy | cumprod method

schedule Aug 11, 2023

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Parameters Return value Examples 1D array 2D array All values Column-wise Row-wise Specifying a datatype

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NumPy's cumprod(~) method returns an array holding the cumulative products of the input array.

Parameters

1. a | array_like

The input array.

2. axis | None or int | optional

The allowed values are as follows:

Axis	Meaning
0	Cumulative product is computed column-wise
1	Cumulative product is computed row-wise
None	Cumulative product is computed using entire array

By default, axis=None.

3. dtype | string or type | optional

The desired data-type of the returned array. By default, the data-type is the same as that of the input array.

4. out | NumPy array | optional

A NumPy array to place the results in.

Return value

A NumPy array holding the cumulative product of the input elements.

Examples

1D array

To compute the cumulative product of a 1D array:


        
        
            
                
                
                    x = np.array([1,2,3])
np.cumprod(x)
                
            
            array([1, 2, 6])

Here, the we are performing the following computations:


        
        
            
                
                
                    [0] 1 = 1
[1] 1 * 2 = 2
[2] 1 * 2 * 3 = 6

2D array

Suppose we have the following 2D array:


        
        
            
                
                
                    x = np.array([[1,2], [3,4]])
x
                
            
            array([[1, 2],
       [3, 4]])

All values

To compute the cumulative products of all values in the array:


        
        
            
                
                
                    x = np.array([[1,2], [3,4]])
np.cumprod(x)
                
            
            array([ 1,  2,  6, 24])

Column-wise

To compute the cumulative products column-wise, set axis=0:


        
        
            
                
                
                    x = np.array([[1,2], [3,4]])
np.cumprod(x, axis=0)
                
            
            array([[1, 2],
       [3, 8]])

Row-wise

To compute the cumulative products row-wise, set axis=1:


        
        
            
                
                
                    x = np.array([[1,2], [3,4]])
np.cumprod(x, axis=1)
                
            
            array([[ 1,  2],
       [ 3, 12]])

Specifying a datatype

To obtain an array of data-type float:


        
        
            
                
                
                    x = np.array([1,2,3])
np.cumprod(x, dtype=float)
                
            
            array([1., 2., 6.])

Here, the . means that the numbers are floats.

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Published by Isshin Inada

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