Printing columns of a list of arrays

Question

I have the following list

import numpy as np
Y = [np.array([[1, 4, 7],
        [2, 5, 8]]),
 np.array([[10, 14, 18],
        [11, 15, 19],
        [12, 16, 20],
        [13, 17, 21]]),
 np.array([[22, 26, 31],
        [24, 28, 33],
        [26, 30, 35]])]

I want to loop through and print the columns inside of all the arrays in Y.

I don't know how to access the columns of Y. Running Y[:,0] for example, does not give me

[[1]
 [2]]

Instead, it gives me the following error

TypeError: list indices must be integers or slices, not tuple

I want to print all columns of all the arrays in Y, not just the first column of the first array.

Is there a reason you are making a list of arrays rather than a single multi-dimensional array like you would get if you did np.concatenate(Y) with your current data? You can, of course, do np.concatenate(Y)[:,0], but if would make more sense to start with a structure that supports the thing you want to accomplish. — Mark
– Mark, Commented Nov 7, 2022 at 3:18
Y is a list. It doesn't have columns. The array elements are 2d, and have columns.You have to iterate on the list. — hpaulj
– hpaulj, Commented Nov 7, 2022 at 3:34
Yes, my original data contains a list of arrays and I want to operate on its columns without concatenating them. — Amelia
– Amelia, Commented Nov 7, 2022 at 4:24

S C · Accepted Answer · 2022-11-07 17:35:36Z

1

Does this help?

for i in range(3):
    l = Y[i]
    for j in range(len(np.transpose(l))):
        print(l[:,j])

This gives you:

[1 2]
[4 5]
[7 8]
[10 11 12 13]
[14 15 16 17]
[18 19 20 21]
[22 24 26]
[26 28 30]
[31 33 35]

answered Nov 7, 2022 at 17:35

S C

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1 Comment

Amelia Over a year ago

Yes, this does give me the columns. Thanks!

isCzech · Accepted Answer · 2022-11-11 18:37:38Z

1

Slight variation of SC's answer:

for array in Y:
    for row in array.T:
        print(row)

returns:

[1 2]
[4 5]
[7 8]
[10 11 12 13]
[14 15 16 17]
[18 19 20 21]
[22 24 26]
[26 28 30]
[31 33 35]

... using the fact that for iterates over rows of an array. (.T just transposes the array, so columns become rows)

edited Nov 11, 2022 at 18:37

answered Nov 11, 2022 at 18:30

isCzech

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Comments

mozway · Accepted Answer · 2022-11-07 05:08:14Z

0

You could use a pandas DataFrame as a higher level structure instead of a list:

import pandas as pd
df = pd.concat(map(pd.DataFrame, Y), keys=range(len(Y)))

df.loc[(0,), 0]

output:

0    1
1    2
Name: 0, dtype: int64

df:

      0   1   2
0 0   1   4   7
  1   2   5   8
1 0  10  14  18
  1  11  15  19
  2  12  16  20
  3  13  17  21
2 0  22  26  31
  1  24  28  33
  2  26  30  35

Other option if you don't need the second index level:

df2 = pd.concat(map(pd.DataFrame, Y), keys=range(len(Y))).droplevel(1)

df2.loc[0, 0]

output:

0    1
0    2
Name: 0, dtype: int64

df2:

    0   1   2
0   1   4   7
0   2   5   8
1  10  14  18
1  11  15  19
1  12  16  20
1  13  17  21
2  22  26  31
2  24  28  33
2  26  30  35

answered Nov 7, 2022 at 5:08

mozway

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1 Comment

Amelia Over a year ago

My original data is in the form of a list, and there are other algorithms that I need to perform on it, as a list, so I won't be able to use dataframes.

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