create new column based on two conditions from other columns

Question

I have a dataframe in pandas looking like this:

    A   B
0   2   0
1   0   3
2   1   1
3   5   0
4   3   1

I need to create a new column based on condition in column A and column B:

if column A > 0 and column B > 0 : new column value = 1
else : new column value = 0

The new column should be like this:

    A   B   new_column
0   2   0   0
1   0   3   0
2   1   1   1
3   5   0   0
4   3   1   1

I tried with np.where but return an error

df['new_column'] = np.where( (df['A']>0 & df['B']>0), 1 , 0)

This is the error:

TypeError: cannot compare a dtyped [float64] array with a scalar of type [bool]

I tried apply but return error too:

def F(x):
    if x['A'] > 0 & x['B'] > 0:
        return 1
    else:
        return 0

df['new_column'] = df.apply(F, axis=1)

This is the error:

TypeError: ("unsupported operand type(s) for &: 'int' and 'float'", 'occurred at index 0')

I already converted column A and column B to numeric

df['A'] = pd.to_numeric(df['A'])
df['B'] = pd.to_numeric(df['B'])

I tried:

df['new_column'] = df[['A','B']].gt(0).all(1)

it returns True or False, not 0 / 1