Choose how to flatten an array (python)

Question

This is a sample of the array I am dealing with:

    records = [[[['   1'], ['   2'], ['   3'], ['   4']]], [[['   red'], ['   blue'], ['   black'], ['   white']]]]

I want to end up with a structure like this one:

    [['   1','   2','   3','   4'],['   red','   blue','   black','   white']]

I've tried the following:

    levelOne = [recs for sublist in records for recs in sublist]
    final = [recs for sublist in levelOne for recs in sublist]

And what I've got was:

    [['   1'], ['   2'], ['   3'], ['   4'], ['   red'], ['  blue'], ['   black'], ['   white']]

mcsoini · Accepted Answer · 2019-11-25 12:12:18Z

1

Use the built-in itertools.chain.from_iterable for flattening/chaining. Then it's just a matter of applying to the right nested list level:

import itertools
list(list(itertools.chain.from_iterable(rec[0])) for rec in records)

[['   1', '   2', '   3', '   4'],
 ['   red', '   blue', '   black', '   white']]

Or as a single list comprehension

[[r[0] for r in rec[0]] for rec in records]

[['   1', '   2', '   3', '   4'],
 ['   red', '   blue', '   black', '   white']]

Or if your nested list is a numpy array to begin with, you can use numpy.reshape:

np.reshape(np.array(records), (2, 4))

array([['   1', '   2', '   3', '   4'],
       ['   red', '   blue', '   black', '   white']], dtype='<U8')

edited Nov 25, 2019 at 12:12

answered Nov 25, 2019 at 12:06

mcsoini

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Akash Kumar · Accepted Answer · 2019-11-25 12:09:15Z

1

If your records array is numpy array then remove np.array(records) just put records If you want simple list then remove np.array casting in np.array(list(...)) in res

import numpy as np
res=np.array(list(map(lambda x : x.reshape(-1), np.array(records))))

answered Nov 25, 2019 at 12:09

Akash Kumar

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Mykola Zotko · Accepted Answer · 2019-11-25 12:18:25Z

1

You can use the method reshape:

records = np.array(records)
records = records.reshape(2, -1)

print(records)

Output:

array([['   1', '   2', '   3', '   4'],
       ['   red', '   blue', '   black', '   white']], dtype='<U8')

answered Nov 25, 2019 at 12:18

Mykola Zotko

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