# Overview
The **`numpy.nanprod()`** function in **NumPy** returns the product of each element of an input array over a given axis in a way that **`Not a Number`(`NaNs`)** are treated as ones.

## Syntax
```
numpy.nanprod(a, axis=None, dtype=None, out=None)
```
## Parameter value
The `numpy.nanprod()` function takes the following parameter values:
* **`a`**(required): This is the input array that contains the numbers to be computed. 
* **`axis`**(optional): This is the axis along which the product is determined.
* **`dtype`**(optional): This is the data type of the output array.
* **`out`**(optional): This is the alternate array where the result is placed.
## Return value
The `numpy.nanprod()` function returns an output array holding the result.
## Example


import numpy as np

# Creating an array
x = np.array([1, 2, np.nan, 2, np.nan])

# Implementing the nanprod() function 
myarray = np.nanprod(x, axis=0)

print(x)
print(myarray)

## Explanation
* **Line 1**: We import the `numpy` module.
* **Line 4**: We create an array **`x`** using the **`array()`** method.
* **Line 7**: We implement the `np.nanprod()` function on the array. The result is assigned to a variable, `myarray`.
* **Line 9**: We print the input array `x`.
* **Line 10**: We print the variable **`myarray`**.
> **Note**: We get the output `4` product of the elements as follows:
**1×2×np.nan×2×np.nan = 1×2×1×2×1 = 4**. 
This is because the `Nans` values are treated as `1`.


What  is the numpy.nanprod() function in Numpy?

Returns the product of array elements, treating NaNs as ones.