Python’s numpy.isnan() tests if an element is
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.
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. |
numpy.isnan() returns a Boolean array.
It returns True if an element is NaN.
It returns False otherwise.
If
xis scalar, the return type is also scalar.
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))
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