numpy.isnan() in Python

The numpy.isnan() function tests element-wise whether it is NaN or not and returns the result as a boolean array. Syntax : 

numpy.isnan(array [, out])

Parameters : 

array : [array_like]Input array or object whose elements, we need to test for infinity
out   : [ndarray, optional]Output array placed with result.
      Its type is preserved and it must be of the right shape to hold the output.

Return : 

boolean array containing the result. For scalar input, the result is a new boolean with value
True if the input is positive or negative infinity; otherwise the value is False.
For array input, the result is a boolean array with the same shape as the input and the values
are True where the corresponding element of the input is positive or negative infinity; 
elsewhere the values are False.

Code 1 :

Python

# Python Program illustrating
# numpy.isnan() method

import numpy as geek

print("Is NaN : ", geek.isnan(1), "\n")

print("Is NaN : ", geek.isnan(0), "\n")

# not a number
print("Is NaN : ", geek.isnan(geek.nan), "\n")

#  infinity
print("Is NaN : ", geek.isnan(geek.inf), "\n")

print("Is NaN : ", geek.isnan(geek.NINF), "\n")

x = geek.array([-geek.inf, 0., geek.inf])
y = geek.array([2, 2, 2])
print("Checking for NaN : ", geek.isnan(x, y))

Output : 

Is NaN :  False 

Is NaN :  False 

Is NaN :  True 

Is NaN :  False 

Is NaN :  False 

Checking for NaN :  [0 0 0]

Code 2 :

Python

# Python Program illustrating
# numpy.isnan() method

import numpy as geek

# Returns True/False value for each element
b = geek.arange(20).reshape(5, 4)

print("\n",b)
print("\nIs NaN(Not a Number): \n", geek.isnan(b))


b = [[1j],
     [geek.nan]]
print("\nIs NaN(Not a Number) : \n", geek.isnan(b))

Output : 

 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]
 [12 13 14 15]
 [16 17 18 19]]

Is NaN(Not a Number): 
 [[False False False False]
 [False False False False]
 [False False False False]
 [False False False False]
 [False False False False]]

Is NaN(Not a Number) : 
 [[False]
 [ True]]

References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.isnan.html

Note : These codes won’t run on online IDE’s. So please, run them on your systems to explore the working.

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