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Method argpartition
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NumPy | any method

schedule Aug 10, 2023
Last updated
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Numpy's any(~) method returns True if at least one element in the input array evaluate to True. Note that missing values (np.NaN) would evaluate to True.

Parameters

1. a | array_like

The input array.

2. axis | int | optional

For 2D arrays, the allowed values are as follows:

Axis

Description

0

Performed column-wise

1

Performed row-wise

None

Performed on entire DataFrame

By default, axis=None.

3. out | Numpy array | optional

Instead of creating a new array, you can place the computed result into the array specified by out.

4. where | array of boolean | optional

Values that are flagged as False will be ignored, that is, their original value will be uninitialized. If you specified the out parameter, the behavior is slightly different - the original value will be kept intact.

Return value

If axis=None, then a boolean is returned. Otherwise, a Numpy array of booleans is returned.

Examples

Basic usage

np.any([True, False, True])
True
np.any([5, 0, 0])
True

2D arrays

Consider the following 2D array:

a = np.array([[0,np.NaN], [0,2]])
a
array([[ 0., nan],
[ 0., 2.]])

All values

np.any(a)
True

Column-wise

np.any(a, axis=0)
array([False, True])

Row-wise

np.any(a, axis=1) # remember, NaN still evaluates to True
array([ True, True])
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Published by Isshin Inada
Edited by 0 others
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