python numpy: Change the column type of a numpy matrix

Question

I have a numpy matrix X, and I tried to change the datatype of column 1 using the code below:

X[:, 1].astype('str')
print(type(X[0, 1]))

but I got the following result:

<type 'numpy.float64'>

Anyone know why the type was not changed to str ? And what is a correct way to change the column type of X?Thanks!

Answer 1

Providing a simple example will explain it better.

>>> a = np.array([[1,2,3],[4,5,6]])
array([[1, 2, 3],
       [4, 5, 6]])
>>> a[:,1]
array([2, 5])
>>> a[:,1].astype('str') # This generates copy and then cast.
array(['2', '5'], dtype='<U21')
>>> a                    # So the original array did not change.
array([[1, 2, 3],
       [4, 5, 6]])

Answer 2

More clear and straightforward answer. The type was not changed to str because NumPy array should have only one data type. The correct way to change the column type of X would be to use structured arrays or one of the solutions from this question.

I had the same problem, and I didn't want to use structured arrays. A possible option is to use pandas if it suits your task. If you're going to change just one column, possibly it means that your data is tabular. Then you can easily change the data type of column. Another compromise is to make a copy of the column and use it separately from the original array.

>>> x = np.ones((3, 3), dtype=np.float)
array([[1., 1., 1.],
       [1., 1., 1.],
       [1., 1., 1.]])
>>> x[:, 1] = x[:, 1].astype(np.int)
>>> type(x[:, 1][0])
numpy.float64
>>> x_pd = pd.DataFrame(x)
>>> x_pd[1] = x_pd[1].astype(np.int16)
>>> type(x_pd[1][0])
numpy.int16