numpy.ma.mask_rows¶
- numpy.ma.mask_rows(a, axis=None)[source]¶
Mask rows of a 2D array that contain masked values.
This function is a shortcut to mask_rowcols with axis equal to 0.
See also
- mask_rowcols
- Mask rows and/or columns of a 2D array.
- masked_where
- Mask where a condition is met.
Examples
>>> import numpy.ma as ma >>> a = np.zeros((3, 3), dtype=np.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=999999) >>> ma.mask_rows(a) masked_array(data = [[0 0 0] [-- -- --] [0 0 0]], mask = [[False False False] [ True True True] [False False False]], fill_value=999999)