I have a 3x3 numpy array and I want to divide each column of this with a vector 3x1. I know how to divide each row by elements of the vector, but am unable to find a solution to divide each column.
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3 Answers
You can transpose your array to divide on each column
(arr_3x3.T/arr_3x1).T
Comments
Let's try several things:
In [347]: A=np.arange(9.).reshape(3,3)
In [348]: A
Out[348]:
array([[ 0., 1., 2.],
[ 3., 4., 5.],
[ 6., 7., 8.]])
In [349]: x=10**np.arange(3).reshape(3,1)
In [350]: A/x
Out[350]:
array([[ 0. , 1. , 2. ],
[ 0.3 , 0.4 , 0.5 ],
[ 0.06, 0.07, 0.08]])
So this has divided each row by a different value
In [351]: A/x.T
Out[351]:
array([[ 0. , 0.1 , 0.02],
[ 3. , 0.4 , 0.05],
[ 6. , 0.7 , 0.08]])
And this has divided each column by a different value
(3,3) divided by (3,1) => replicates x across columns.
With the transpose (1,3) array is replicated across rows.
It's important that x be 2d when using .T (transpose). A (3,) array transposes to a (3,) array - that is, no change.
Comments
The simplest seems to be
A = np.arange(1,10).reshape(3,3)
b=np.arange(1,4)
A/b
A will be
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
and b will be
array([1, 2, 3])
and the division will produce
array([[1. , 1. , 1. ],
[4. , 2.5, 2. ],
[7. , 4. , 3. ]])
The first column is divided by 1, the second column by 2, and the third by 3.
If I've misinterpreted your columns for rows, simply transform with .T - as C_Z_ answered above.
