NumPy | prod method
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Numpy's prod(~) computes the product of the values in the input array.
Parameters
1. a | array-like
The input array for which to compute the product of values.
2. axis | None or int | optional
The axis along which to compute the product. For 2D arrays, the allowed values are as follows:
Axis | Meaning |
|---|---|
0 | Compute the product column-wise |
1 | Compute the product row-wise |
None | Compute the product of all values |
By default, axis=None.
3. dtype | string or type | optional
The desired data type of the returned array. dtype will also be the type used during the computation of the product. By default, the dtype of a is used.
4. out | Numpy array | optional
Instead of creating a new array, you can place the computed product into the array specified by out.
5. initial | scalar | optional
The initial value used for the computation of the product. By default, initial=1.
6. where | array of boolean | optional
A boolean mask, where values that are flagged as False will be ignored, while those flagged as True will be used in the computation.
Examples
Basic usage
np.prod([1,2,3,4])
24
Computing the product of a 2D array
Consider the following 2D array:
a = np.array([[1,2],[3,4]])a
array([[1, 2], [3, 4]])
All values
np.prod(a)
24
Column-wise
np.prod(a, axis=0)
array([3, 8])
Row-wise
np.prod(a, axis=1)
array([ 2, 12])
Specifying an output array
a = np.zeros(2)np.prod([[1,2],[3,4]], axis=1, out=a) # row-wise producta
array([ 2., 12.])
Here, we've outputted the results to the array a.
Specifying an initial value
np.prod([1,2,3], initial=10)
60
Here, since we set an initial value of 10, we have 10*1*2*3 = 60.
Specifying a boolean mask
np.prod([4,5,6,7], where=[False, True, True, False])
30
Here, only the second and third values were included in the computation of the product.
