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numpy.isnan() in Python

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  • Last Updated : 28 Mar, 2022

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.

This article is contributed by Mohit Gupta_OMG 😀. If you like GeeksforGeeks and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.


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