shift numpy array by row

Question

Array:

arr = np.ones([4,4])

array([[ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.],
       [ 1.,  1.,  1.,  1.]])

I use shift from scipy.ndimage.interpolation as follows:

shift(arr,1, cval=np.nan)

array([[ nan,  nan,  nan,  nan],
       [ nan,   1.,   1.,   1.],
       [ nan,   1.,   1.,   1.],
       [ nan,   1.,   1.,   1.]])

HOWEVER, I want:

array([[ nan,  nan,  nan,  nan],
       [ 1.,   1.,   1.,   1.],
       [ 1.,   1.,   1.,   1.],
       [ 1.,   1.,   1.,   1.]])

Basically, I want to SHIFT all columns data down the rows and boot the last row out of my data set. Pandas has the shift function that can do this but I'm not certain how it can be done in Numpy.

Stanislas Morbieu · Accepted Answer · 2019-10-29 23:26:33Z

2

You can change the shift parameter (second parameter) of the shift function from scipy.ndimage.interpolation as follows:

shift(arr, (1, 0), cval=np.nan)

Here, (1, 0) means a shift of 1 in the first dimension, and 0 in the second dimension.

answered Oct 29, 2019 at 23:26

Stanislas Morbieu

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1 Comment

Michael Over a year ago

Might also want to explicitly set mode='constant'

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