# Numpy: Divide each row by a vector element

Suppose I have a numpy array:

```
data = np.array([[1,1,1],[2,2,2],[3,3,3]])
```

and I have a corresponding "vector:"

```
vector = np.array([1,2,3])
```

How do I operate on `data`

along each row to either subtract or divide so the result is:

```
sub_result = [[0,0,0], [0,0,0], [0,0,0]]
div_result = [[1,1,1], [1,1,1], [1,1,1]]
```

Long story short: How do I perform an operation on each row of a 2D array with a 1D array of scalars that correspond to each row?

Here you go. You just need to use `None`

(or alternatively `np.newaxis`

) combined with broadcasting:

```
In [6]: data - vector[:,None]
Out[6]:
array([[0, 0, 0],
[0, 0, 0],
[0, 0, 0]])
In [7]: data / vector[:,None]
Out[7]:
array([[1, 1, 1],
[1, 1, 1],
[1, 1, 1]])
```

From: stackoverflow.com/q/19602187

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