Converting some columns of a matrix from float to int

Question

I have a matrix tempsyntheticGroup2 with 6 columns. I want to change the value of columns (0,1,2,3,5) from float to int. This is my code:

tempsyntheticGroup2=tempsyntheticGroup2[:,[0,1,2,3,5]].astype(int)

but it doesn't work properly and I loose the other columns.

Answer 1

I don't think you can have a numpy array with some element that are ints, and some that are floats (there is only one possible dtype per array). But if you just want to round to lower integer (while keeping all elements as floats) you can do this:

# define dummy example matrix
t = np.random.rand(3,4) + np.arange(12).reshape((3,4))

array([[  0.68266426,   1.4115732 ,   2.3014562 ,   3.5173022 ],
       [  4.52399807,   5.35321628,   6.95888015,   7.17438118],
       [  8.97272076,   9.51710983,  10.94962065,  11.00586511]])



# round some columns to lower int
t[:,[0,2]] = np.floor(t[:,[0,2]])
# or
t[:,[0,2]] = t[:,[0,2]].astype(int)

array([[  0.        ,   1.4115732 ,   2.        ,   3.5173022 ],
       [  4.        ,   5.35321628,   6.        ,   7.17438118],
       [  8.        ,   9.51710983,  10.        ,  11.00586511]])

otherwise you probably need to split your original array into 2 different arrays, with one containing the column that stay floats, the other containing the column that become ints.

t_int =  t[:,[0,2]].astype(int)

array([[ 0,  2],
       [ 4,  6],
       [ 8, 10]])


t_float = t[:,[1,3]]

array([[  1.4115732 ,   3.5173022 ],
       [  5.35321628,   7.17438118],
       [  9.51710983,  11.00586511]])

Note that you'll have to change your indexing accordingly to access your elements...