Convert numpy.void to numpy.ndarray

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I have loaded a .csv file in python with numpy.genfromtxt. Now it returns a 1 dimensional numpy.ndarray with in that array, numpy.void objects which are actually just arrays of integers. However I would like to convert these from typenumpy.void to numpy.array. To clarify:

>>> print(train_data.shape)
(42000,)
>>> print(type(train_data[0]))
<class 'numpy.void'>
>>> print(train_data[0])
(9, 0, 0)

So here the array (9, 0, 0) which has type numpy.void should be a numpy.array.

How can I convert all values from train_data to be numpy arrays?

Efficiency is also somewhat important because I am working with a lot of data.

Some more code

>>> with open('filename.csv, 'rt') as raw_training_data:
>>>     train_data = numpy.genfromtxt(raw_training_data, delimiter=',', names=True, dtype=numpy.integer)
>>> print(train_data.dtype)
[('label', '<i4'), ('pixel0', '<i4'), ('pixel1', '<i4')]
>>> print(type(train_data))
<class 'numpy.ndarray'>
numpy arrays python
2 Answers

Use the numpy.asarray() method, which converts an input to an array

array=numpy.asarray(train_data[0])
user_105348420

I know it is too late to answer this. But found a solution for a similar problem I had, thanks to the solution provided in this question. If you can convert the train_data to list and then convert it to an numpy array, that would do the job for you. 

print(np.array(train_data.tolist()).shape)
user_36686270
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