What is numpy.isnan() in Python?
Python’s numpy.isnan() tests if an element is
Syntax
numpy.isnan() is declared as follows:
numpy.isnan(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isnan'>
In the syntax above, x is the non-optional parameter and the rest are optional parameters.
A universal function (ufunc) is a function that operates on ndarrays in an element-by-element fashion. The
isnan()method is a universal function.
Parameters
The numpy.isnan() method takes the following compulsory parameter:
x[array-like] - input array.
The numpy.isnan() method takes the following optional parameters:
Parameter | Description |
out | represents the location into which the output of the method is stored. |
where | True value indicates that a universal function should be calculated at this position. |
casting | controls the type of datacasting that should occur. The same_kind option indicates that safe casting or casting within the same kind should take place. |
order | controls the memory layout order of the output function. The option K means reading the elements in the order they occur in memory. |
dtype | represents the desired data type of the array. |
subok | decides if subclasses should be made or not. If True, subclasses will be passed through. |
Return value
numpy.isnan() returns a Boolean array.
-
It returns
Trueif an element isNaN. -
It returns
Falseotherwise.
If
xis scalar, the return type is also scalar.
Examples
The example below shows the use of numpy.isnan() on the elements a and b:
import numpy as npa = np.nanb = 20print (np.isnan(a))print (np.isnan(b))
The following example shows the use of numpy.isnan() on the array arr1:
import numpy as nparr1 = np.array([1,2,np.nan, np.log(-3)])print (np.isnan(arr1))
