The ** numpy.nancumprod() function** in NumPy is used to return the cumulative product of each element of an input array over a given axis in such a way that

`NaN`

values are treated as `1`

.```
numpy.nancumprod(a, axis=None, dtype=None, out=None)
```

The `numpy.nancumprod()`

function takes the following parameter values:

(required): This is the input array containing numbers to be computed.`a`

(optional): This is the axis along which the product is determined.`axis`

(optional): This is the data type of the output array.`dtype`

(optional): This is the alternate array where the result is placed.`out`

The `numpy.nancumprod()`

function returns an output array holding the result.

import numpy as np# creating an arrayx = np.array([1, 2, np.nan, 2, np.nan])# Implementing the nancumprod() functionmyarray = np.nancumprod(x, axis=0)print(x)print(myarray)

- Line 1: We import the
`numpy`

module. - Line 4: We create an array,
`x`

, using the`array()`

method. - Line 7: We implement the
`np.nancumprod()`

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:It is worth remembering that`NaN`

values are treated as`1`

.

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