numpy.isnan () in Python



About:
numpy.isnan (array [, out]): Tests element by element if it is NaN or not, returns the result as a boolean array … 
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 program illustrating
# numpy.isnan () method

 

import numpy as geek 

  

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

 

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

 
# not a number

print ( "Is NaN:" , geek.isnan (geek.nan), "" )

 
# infinity

print ( " Is NaN: " , geek.isnan ( geek.inf), "" )

 

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

 

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 program illustrating
# numpy.isnan ( ) method

 

import numpy as geek 

 
# Returns True / False for each element

b = geek.arange ( 20 ). reshape ( 5 , 4 )

 

print ( " " , b)

print ( "Is NaN (Not a Number ): " , geek.isnan (b))

  

 

b = [[ 1j ], 

[geek.nan]]

print ( "Is NaN (Not a Number):" , geek.isnan (b))

Outut:

 [[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]] 

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

Notes:
These codes will not work for online IDs. Please run them on your systems to see how they work. 
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This article is provided by Mohit Gupta_OMG