mask_cols(a, axis=<no value>)
This function is a shortcut to mask_rowcols
with :None:None:`axis` equal to 1.
Mask columns of a 2D array that contain masked values.
mask_rowcols
Mask rows and/or columns of a 2D array.
masked_where
Mask where a condition is met.
>>> import numpy.ma as ma
... a = np.zeros((3, 3), dtype=int)
... a[1, 1] = 1
... a array([[0, 0, 0], [0, 1, 0], [0, 0, 0]])
>>> a = ma.masked_equal(a, 1)
... a masked_array( data=[[0, 0, 0], [0, --, 0], [0, 0, 0]], mask=[[False, False, False], [False, True, False], [False, False, False]], fill_value=1)
>>> ma.mask_cols(a) masked_array( data=[[0, --, 0], [0, --, 0], [0, --, 0]], mask=[[False, True, False], [False, True, False], [False, True, False]], fill_value=1)See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.ma.core.mask_rowcols
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