### Question :

How to change array shapes in in numpy?

If I create an array `X = np.random.rand(D, 1)`

it has shape `(3,1)`

:

```
[[ 0.31215124]
[ 0.84270715]
[ 0.41846041]]
```

If I create my own array `A = np.array([0,1,2])`

then it has shape `(1,3)`

and looks like

```
[0 1 2]
```

How can I force the shape `(3, 1)`

on my array `A`

?

##
Answer #2:

```
A=np.array([0,1,2])
A.shape=(3,1)
```

or

```
A=np.array([0,1,2]).reshape((3,1)) #reshape takes the tuple shape as input
```

##
Answer #3:

The numpy module has a `reshape`

function and the ndarray has a `reshape`

method, either of these should work to create an array with the shape you want:

```
import numpy as np
A = np.reshape([1, 2, 3, 4], (4, 1))
# Now change the shape to (2, 2)
A = A.reshape(2, 2)
```

Numpy will check that the size of the array does not change, ie `prod(old_shape) == prod(new_shape)`

. Because of this relation, you’re allowed to replace one of the values in shape with `-1`

and numpy will figure it out for you:

```
A = A.reshape([1, 2, 3, 4], (-1, 1))
```

##
Answer #4:

You can set the shape directy i.e.

```
A.shape = (3L, 1L)
```

or you can use the resize function:

```
A.resize((3L, 1L))
```

or during creation with reshape

```
A = np.array([0,1,2]).reshape((3L, 1L))
```