# Multiplying across in a numpy array

I'm trying to multiply each of the terms in a 2D array by the corresponding terms in a 1D array. This is very easy if I want to multiply every column by the 1D array, as shown in the numpy.multiply function. But I want to do the opposite, multiply each term in the row. In other words I want to multiply:

```    [1,2,3]   [0]
[4,5,6] * [1]
[7,8,9]   [2]
```

and get

```    [0,0,0]
[4,5,6]
[14,16,18]
```

```    [0,2,6]
[0,5,12]
[0,8,18]
```

Does anyone know if there's an elegant way to do that with numpy? Thanks a lot, Alex

Normal multiplication like you showed:

```    >>> import numpy as np
>>> m = np.array([[1,2,3],[4,5,6],[7,8,9]])
>>> c = np.array([0,1,2])
>>> m * c
array([[ 0,  2,  6],
[ 0,  5, 12],
[ 0,  8, 18]])
```

If you add an axis, it will multiply the way you want:

```    >>> m * c[:, np.newaxis]
array([[ 0,  0,  0],
[ 4,  5,  6],
[14, 16, 18]])
```

You could also transpose twice:

```    >>> (m.T * c).T
array([[ 0,  0,  0],
[ 4,  5,  6],
[14, 16, 18]])
```

From: stackoverflow.com/q/18522216