Bishwajit Purkaystha - 3 years ago 183
Python Question

# axis = 0 is not clearly understood in numpy.sum

I am learning Python, and have encountered

`numpy.sum`
. It has an optional parameter
`axis`
. This parameter is used to get either column-wise summation or row-wise summation. When
`axis = 0`
we imply to sum it over columns only. For example,

``````a = np.array([[1, 2, 3], [4, 5, 6]])
np.sum(a, axis = 0)
``````

This snippet of code produces output:
`array([5, 7, 9])`
, fine. But if I do:

``````a = np.array([1, 2, 3])
np.sum(a, axis = 0)
``````

I get result:
`6`
, why is that? Shouldn't I get
`array([1, 2, 3])`
? Thanks.

All that is going on is that numpy is summing across the first (0th) and only axis. Consider the following:

``````In [2]: a = np.array([1, 2, 3])

In [3]: a.shape
Out[3]: (3,)

In [4]: len(a.shape) # number of dimensions
Out[4]: 1

In [5]: a1 = a.reshape(3,1)

In [6]: a2 = a.reshape(1,3)

In [7]: a1
Out[7]:
array([[1],
[2],
[3]])

In [8]: a2
Out[8]: array([[1, 2, 3]])

In [9]: a1.sum(axis=1)
Out[9]: array([1, 2, 3])

In [10]: a1.sum(axis=0)
Out[10]: array([6])

In [11]: a2.sum(axis=1)
Out[11]: array([6])

In [12]: a2.sum(axis=0)
Out[12]: array([1, 2, 3])
``````

So, to be more explicit:

``````In [15]: a1.shape
Out[15]: (3, 1)
``````

`a1` is 2-dimensional, the "long" axis being the first.

``````In [16]: a1[:,0] # give me everything in the first axis, and the first part of the second
Out[16]: array([1, 2, 3])
``````

Now, sum along the first axis:

``````In [17]: a1.sum(axis=0)
Out[17]: array([6])
``````
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