 # numpy.where () in Python

The numpy.where (condition [, x, y]) function returns the indices of the elements in the input array where the given condition is met.

Parameters:
condition: When True, yield x, otherwise yield y.
x, y: Values ​​from which to choose. x, y and condition need to be broadcastable to some shape.

Returns:
out: [ndarray or tuple of ndarrays] If both x and y are specified, the output array contains elements of x where condition is True, and elements from y elsewhere.

If only condition is given, return the tuple condition.nonzero (), the indices where condition is True.

Code # 1:

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``` # Python program explaining # where () function   import numpy as np   np.where ([[ True , False ], [  True , True ]], [[[ 1 , 2 ], [ 3 , 4 ]], [[ 5 , 6 ], [ 7 , 8 ] ]) ```

Output:

` array ([[1, 6], [3, 4]]) `

Code # 2:

 ` # Python program explaining ` ` # where () function ` ` `  ` import ` ` numpy as np `   ` # a is an array of integers. ` ` a ` ` = ` ` np.array ([[` ` 1 ` `, ` ` 2 ` `, ` ` 3 ` `], [` ` 4 ` `, ` ` 5 ` `, ` ` 6 ` `]]) `   ` print ` ` (a) `   ` print ` ` (` ` `Indices of elements & lt; 4` ` `) `   ` b ` ` = ` ` np.where (a & lt; ` ` 4 ` `) ` ` print ` ` (b) `   ` print ` ` (` ` "Elements which are & lt; 4" ` `) ` ` print ` ` (a [b]) `

Output:

` [[1 2 3] [4 5 6]] Indices of elements & lt; 4 (array ([0 , 0, 0], dtype = int64), array ([0, 1, 2], dtype = int64)) Elements which are & lt; 4 array ([1, 2, 3]) `