Load a .csv file into a numpy array as a column vector

Question

I've got a .csv file that I'm trying to load into a numpy array as a column vector. When using

temp = np.genfromtxt(location, delimiter=',')

the data is a numpy array where the entries are represented as follows:

[ 0.  ...  0.  1.  0.  ... 0.], [ 0.  ...  1.  0.  0.  ... 0.]

whereas, I would like something like this:

[array([[0],
       [0],
       [0],
       ...
       [0],
       [1],
       [0],
       ...
       [0],
       [0]]), array([[0], 
       [0],
       [0],
       ...
       [0],
       [1], 
       [0],
       ...)]

I'm able to accomplish this using

my_data = []

for i in range(len(temp)):
    foo = np.array([temp[i]]).T
    my_data.append(foo)

But am wondering if there is a more efficient way of achieving the required result.

Do you specifically want the items in the list to be arrays? Otherwise, you can do: temp[:, :, None].tolist() — Moses Koledoye
– Moses Koledoye, Commented Aug 31, 2016 at 18:38
It would be better is the items in the list were arrays, that way I wouldn't need to make alterations to my main code — Lukasz
– Lukasz, Commented Aug 31, 2016 at 18:48

Moses Koledoye · Accepted Answer · 2016-08-31 19:01:43Z

1

Add a new axis to temp, and cast sublists to np arrays:

temp = np.genfromtxt(location, delimiter=',')
my_data = map(np.array, temp[:, :, np.newaxis])

For Python 3, call list on the above result or use a list comprehension:

my_data = [np.array(arr) for arr in temp[:, :, np.newaxis]]

edited Aug 31, 2016 at 19:01

answered Aug 31, 2016 at 18:54

Moses Koledoye

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1 Comment

hpaulj Over a year ago

list(temp[...,None]) does the same thing.

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