Convert numpy.void to numpy.ndarray

Question

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'>

You should show the genfromtxt call. What's train_data.dtype? My guess it is a structured array. It is 1d with multiple fields, which are accessed by field name. Whether it is easy to convert to 2d numeric dtype will depend on the field dtypes. — hpaulj
– hpaulj, Commented Oct 30, 2018 at 16:18
train_data['label'] is the first field, etc. If you want a 2d array with 3 columns, try skip_header=1 instead of names=True. Since the fields are all i4 we could convert this after loading, but loading in the desired format will be simpler. — hpaulj
– hpaulj, Commented Oct 30, 2018 at 16:34
Does this answer your question? How to slice a numpy.ndarray made up of numpy.void numbers? — Behdad Abdollahi Moghadam
– Behdad Abdollahi Moghadam, Commented Mar 2, 2022 at 9:02

nickY · Accepted Answer · 2019-10-28 00:27:25Z

3

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)

answered Oct 28, 2019 at 0:27

nickY

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samlli · Accepted Answer · 2018-10-30 14:56:28Z

0

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

array=numpy.asarray(train_data[0])

answered Oct 30, 2018 at 14:56

samlli

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1 Comment

Tristan Over a year ago

Sorry if I was unclear. I meant converting all 'void' arrays in the normal array. So by doing something creating an array with all numpy arrays in it.

SzymonO · Accepted Answer · 2023-04-18 05:48:45Z

0

You can do it by calling view with the correct dtype and shape, for your case you can do

 train_data= train_data.view((np.int_, 3))

answered Apr 18, 2023 at 5:48

SzymonO

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