Python Create vertical Numpy array

Question

I have created a code in which from my lists I create an array, which must be vertical, like a vector, the problem is that using the reshape method I don't get anything.

import numpy as np

data = [[ 28,    29,    30,    19,    20,    21],
        [ 31,    32,    33,    22,    23,      24],
        [  1,    34,    35,    36,    25,    26],
        [  2,    19,    20,    21,    10,    11],
        [  3,     4,     5,     6,     7,    8 ]]

index = []
for i in range(len(data)):
    index.append([data[i][0], data[i][1], data[i][2],
                    data[i][3], data[i][4], data[i][5]])   
    y = np.array([index[i]])
#    y.reshape(6,1)

Is there any solution for these cases? Thank you.

I'm looking for something like this to remain:

Mad Physicist · Accepted Answer · 2020-05-15 02:06:15Z

1

If you want to view each row as a column, transpose the array in any one of the following ways:

index = data.T
index = np.transpose(data)
index = data.transpose()
index = np.swapaxes(data, 0, 1)
index = np.moveaxis(data, 1, 0)
...

Each column of index will be a row of data. If you just want to access one column at a time, you can do that too. For example, to get row 3 (4th row) of the original array, any of the following would work:

y = data[3, :]
y = data[3]
y = index[:, 3]

You can get a column vector from the result by explicitly reshaping it to one:

y = y.reshape(-1, 1)
y = np.reshape(y, (-1, 1))
y = np.expand_dims(y, 1)

Remember that reshaping creates a new array object which views the same data as the original. The only way I know to reshape an array in-place is to assign to its shape attribute:

y.shape = (y.size, 1)

answered May 15, 2020 at 2:06

Mad Physicist

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Zabir Al Nazi Nabil · Accepted Answer · 2020-05-15 01:59:33Z

0

You can use flatten() from numpy https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flatten.html

(if you want a copy of the original array without modifying the original)

import numpy as np

data = [[ 28,    29,    30,    19,    20,    21],
        [ 31,    32,    33,    22,    23,      24],
        [  1,    34,    35,    36,    25,    26],
        [  2,    19,    20,    21,    10,    11],
        [  3,     4,     5,     6,     7,    8 ]]

data = np.array(data).flatten()

print(data.shape)

(30,)

You can also use ravel()

(if you don't want a copy)

data = np.array(data).ravel()

If your array always has 2-d, this also works,

data = data.reshape(-1)

edited May 15, 2020 at 1:59

answered May 15, 2020 at 1:52

Zabir Al Nazi Nabil

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1 Comment

Mad Physicist Over a year ago

Use ravel to avoid copying the data

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