  # numpy.nanprod () in Python

NumPy | Python Methods and Functions

`numpy.nanprod()` is used when we want to compute the product of array elements along a given axis, treating ` NaNs ` as ` NaNs `. One is returned for slices that are all NaN or empty.

Syntax: numpy.nanprod (arr, axis = None, dtype = None, out = None, keepdims = 'class numpy._globals._NoValue').

Parameters:
arr: [array_like] Array containing numbers whose sum is desired ... If arr is not an array, a conversion is attempted.
axis: Axis along which the product is computed. The default is to compute the product of the flattened array.
dtype: The type of the returned array and of the accumulator in which the elements are summed. By default, the dtype of arr is used.
out: [ndarray, optional] A location into which the result is stored.
- & gt ; If provided, it must have a shape that the inputs broadcast to.
- & gt; If not provided or None, a freshly-allocated array is returned.
keepdims: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original arr.

Return: A new array holding the result is returned unless out is specified, in which case it is returned.

Code # 1: Work

 ` # Python program explaining ` ` # numpy.nanprod () function `   ` import ` ` numpy as geek ` ` in_num ` ` = ` ` 10 `   ` print ` ` (` ` "Input number:" ` `, in_num) ` ` `  ` out_prod ` ` = ` ` geek.nanprod (in_num) ` ` print ` ` (` ` "product of array element:" ` `, out_prod) `

Output:

` Input number: 10 product of array element: 10 `

Code # 2:

 ` # Python program explaining ` ` # numpy.nanprod function ` ` `  ` import ` ` numpy as geek `   ` in_arr ` ` = ` ` geek. array ([[` ` 2 ` ` , ` ` 2 ` `, ` ` 2 ` `], [` ` 2 ` `, ` ` 2 ` `, geek.nan]]) `   ` print ` ` (` `" Input array: "` `, in_arr) `   ` out_prod ` ` = ` ` geek.nanprod (in_arr) ` ` print ` ` (` ` "product of array elements:" ` `, out_prod) `

Output:

` Input array: [[2. 2. 2 .] [2. 2. nan]] product of array elements: 32.0 `

Code # 3:

 ` # Program Python explaining ` ` # numpy.nanprod function `   ` import ` ` numpy as geek `   ` in_arr ` ` = ` ` geek.array ([[ ` ` 2 ` `, ` ` 2 ` `, ` ` 2 ` `], [` ` 2 ` `, ` ` 2 ` `, geek.nan]]) `   ` print ` ` (` `" Input array: "` `, in_arr) `   ` out_prod ` ` = ` ` geek.nanprod (in_arr, axis ` ` = ` ` 1 ` `) ` ` print ` ` (` `" product of array elements taking axis 1: "` `, out_prod) `

Output:

` Input array: [[2. 2. 2.] [2. 2. nan]] product of array elements taking axis 1: [8. 4.] `