Q:

How to convert from boolean array to int array in python

I have a Numpy 2-D array in which one column has Boolean values i.e. True/False. I want to convert it to integer 1 and 0 respectively, how can I do it?
E.g. my data[0::,2] is  boolean, I tried
data[0::,2]=int(data[0::,2])

, but it is giving me error:
TypeError: only length-1 arrays can be converted to Python scalars
My first 5 rows of array are:
[['0', '3', 'True', '22', '1', '0', '7.25', '0'],
 ['1', '1', 'False', '38', '1', '0', '71.2833', '1'],
 ['1', '3', 'False', '26', '0', '0', '7.925', '0'],
 ['1', '1', 'False', '35', '1', '0', '53.1', '0'],
 ['0', '3', 'True', '35', '0', '0', '8.05', '0']]

A:

Ok, the easiest way to change a type of any array to float is doing:
data.astype(float)
The issue with your array is that float('True') is an error, because 'True' can't be parsed as a float number. So, the best thing to do is fixing your array generation code to produce floats (or, at least, strings with valid float literals) instead of bools.
In the meantime you can use this function to fix your array:
def boolstr_to_floatstr(v):
    if v == 'True':
        return '1'
    elif v == 'False':
        return '0'
    else:
        return v

And finally you convert your array like this:
new_data = np.vectorize(boolstr_to_floatstr)(data).astype(float)

A:

boolarrayvariable.astype(int) works:
data = np.random.normal(0,1,(1,5))
threshold = 0
test1 = (data>threshold)
test2 = test1.astype(int)

Output:
data = array([[ 1.766, -1.765,  2.576, -1.469,  1.69]])
test1 = array([[ True, False,  True, False,  True]], dtype=bool)
test2 = array([[1, 0, 1, 0, 1]])

