numpy.in1d() function in Python
numpy.in1d()
function test whether each element of a 1-D array is also present in a second array and return a boolean array the same length as arr1 that is True where an element of arr1 is in arr2 and False otherwise.
Syntax : numpy.in1d(arr1, arr2, assume_unique = False, invert = False)
Parameters :
arr1 : [array_like] Input array.
arr2 : [array_like] The values against which to test each value of arr1.
assume_unique : [bool, optional] If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
invert : [bool, optional] If True, the values in the returned array are inverted. Default is False.Return : [ndarray, bool] The values arr1[in1d] are in arr2.
Code #1 :
# Python program explaining # numpy.in1d() function # importing numpy as geek import numpy as geek arr1 = geek.array([ 0 , 1 , 2 , 3 , 0 , 4 , 5 ]) arr2 = [ 0 , 2 , 5 ] gfg = geek.in1d(arr1, arr2) print (gfg) |
Output :
[ True False True False True False True]
Code #2 :
# Python program explaining # numpy.in1d() function # importing numpy as geek import numpy as geek arr1 = geek.array([ 0 , 1 , 2 , 3 , 0 , 4 , 5 ]) arr2 = [ 0 , 2 , 5 ] gfg = geek.in1d(arr1, arr2, invert = True ) print (gfg) |
Output :
[False True False True False True False]
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