NumPy | prod method
prod(~) computes the product of the values in the input array.
The input array for which to compute the product of values.
The axis along which to compute the product. For 2D arrays, the allowed values are as follows:
Compute the product column-wise
Compute the product row-wise
Compute the product of all values
The desired data type of the returned array.
dtype will also be the type used during the computation of the product. By default, the
a is used.
Numpy array |
Instead of creating a new array, you can place the computed product into the array specified by
The initial value used for the computation of the product. By default,
A boolean mask, where values that are flagged as False will be ignored, while those flagged as True will be used in the computation.
Computing the product of a 2D array
Consider the following 2D array:
a = np.array([[1,2],[3,4]])aarray([[1, 2],[3, 4]])
np.prod(a, axis=0)array([3, 8])
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 productaarray([ 2., 12.])
Here, we've outputted the results to the array
Specifying an initial value
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.