# How to convert 2D float numpy array to 2D int numpy array?

## Question:

How to convert real numpy array to int numpy array?

Tried using map directly to array but it did not work.

## Answers:

Use the `astype`

method.

```
>>> x = np.array([[1.0, 2.3], [1.3, 2.9]])
>>> x
array([[ 1. , 2.3],
[ 1.3, 2.9]])
>>> x.astype(int)
array([[1, 2],
[1, 2]])
```

Some numpy functions for how to control the rounding: rint, floor,trunc, ceil. depending how u wish to round the floats, up, down, or to the nearest int.

```
>>> x = np.array([[1.0,2.3],[1.3,2.9]])
>>> x
array([[ 1. , 2.3],
[ 1.3, 2.9]])
>>> y = np.trunc(x)
>>> y
array([[ 1., 2.],
[ 1., 2.]])
>>> z = np.ceil(x)
>>> z
array([[ 1., 3.],
[ 2., 3.]])
>>> t = np.floor(x)
>>> t
array([[ 1., 2.],
[ 1., 2.]])
>>> a = np.rint(x)
>>> a
array([[ 1., 2.],
[ 1., 3.]])
```

To make one of this in to int, or one of the other types in numpy, astype (as answered by BrenBern):

```
a.astype(int)
array([[1, 2],
[1, 3]])
>>> y.astype(int)
array([[1, 2],
[1, 2]])
```

you can use `np.int_`

:

```
>>> x = np.array([[1.0, 2.3], [1.3, 2.9]])
>>> x
array([[ 1. , 2.3],
[ 1.3, 2.9]])
>>> np.int_(x)
array([[1, 2],
[1, 2]])
```

If you’re not sure your input is going to be a Numpy array, you can use `asarray`

with `dtype=int`

instead of `astype`

:

```
>>> np.asarray([1,2,3,4], dtype=int)
array([1, 2, 3, 4])
```

If the input array already has the correct dtype, `asarray`

avoids the array copy while `astype`

does not (unless you specify `copy=False`

):

```
>>> a = np.array([1,2,3,4])
>>> a is np.asarray(a) # no copy :)
True
>>> a is a.astype(int) # copy :(
False
>>> a is a.astype(int, copy=False) # no copy :)
True
```