# How to convert a boolean array to an int array

## Question:

I use Scilab, and want to convert an array of booleans into an array of integers:

```
>>> x = np.array([4, 3, 2, 1])
>>> y = 2 >= x
>>> y
array([False, False, True, True], dtype=bool)
```

In Scilab I can use:

```
>>> bool2s(y)
0. 0. 1. 1.
```

or even just multiply it by 1:

```
>>> 1*y
0. 0. 1. 1.
```

Is there a simple command for this in Python, or would I have to use a loop?

## Answers:

Numpy arrays have an `astype`

method. Just do `y.astype(int)`

.

Note that it might not even be necessary to do this, depending on what you’re using the array for. Bool will be autopromoted to int in many cases, so you can add it to int arrays without having to explicitly convert it:

```
>>> x
array([ True, False, True], dtype=bool)
>>> x + [1, 2, 3]
array([2, 2, 4])
```

The `1*y`

method works in Numpy too:

```
>>> import numpy as np
>>> x = np.array([4, 3, 2, 1])
>>> y = 2 >= x
>>> y
array([False, False, True, True], dtype=bool)
>>> 1*y # Method 1
array([0, 0, 1, 1])
>>> y.astype(int) # Method 2
array([0, 0, 1, 1])
```

If you are asking for a way to convert Python lists from Boolean to int, you can use `map`

to do it:

```
>>> testList = [False, False, True, True]
>>> map(lambda x: 1 if x else 0, testList)
[0, 0, 1, 1]
>>> map(int, testList)
[0, 0, 1, 1]
```

Or using list comprehensions:

```
>>> testList
[False, False, True, True]
>>> [int(elem) for elem in testList]
[0, 0, 1, 1]
```

Using numpy, you can do:

```
y = x.astype(int)
```

If you were using a non-numpy array, you could use a list comprehension:

```
y = [int(val) for val in x]
```

I know you asked for non-looping solutions, but the only solutions I can come up with probably loop internally anyway:

```
map(int,y)
```

or:

```
[i*1 for i in y]
```

or:

```
import numpy
y=numpy.array(y)
y*1
```

Most of the time you don’t need conversion:

```
>>>array([True,True,False,False]) + array([1,2,3,4])
array([2, 3, 3, 4])
```

The right way to do it is:

```
yourArray.astype(int)
```

or

```
yourArray.astype(float)
```

A funny way to do this is

```
>>> np.array([True, False, False]) + 0
np.array([1, 0, 0])
```