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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']]

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')

NumPy Array manipulation: ndarray.flatten()function, Return value: ndarray - A copy of the input array, flattened to one dimension. Example-1: numpy.ndarray.flatten() >>� 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']]

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))))

numpy.ndarray.flatten — NumPy v1.19 Manual, numpy.ndarray.flatten�. method. ndarray. flatten (order='C')�. Return a copy of the array collapsed into one dimension. Parameters. order{'C'� numpy.ndarray.flatten() function. The flatten() function is used to get a copy of an given array collapsed into one dimension. Syntax: ndarray.flatten(order='C') Version: 1.15.0. Parameter:

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')

Numpy ndarray.flatten() function, numpy.ndarray.flatten() function return a copy of the array collapsed into one dimension. 'A' means to flatten in column-major order if a is Fortran contiguous in numpy.ma.where() function - Python � numpy.ma.choose() function - Python � Python | Flatten a 2d numpy array into 1d array Given a 2d numpy array, the task is to flatten a 2d numpy array into a 1d array. Below are a few methods to solve the task. Method #1 : Using np.flatten ()

Python: numpy.flatten() – Function Tutorial with examples , How to Reverse a 1D & 2D numpy array using np.flip() and [] operator in Python � Python Numpy : Select an element or sub array by index from a� I would like to get some code review for my recursive implementation of python flatten array method. Write a piece of functioning code that will flatten an array of arbitrarily nested arrays of integers into a flat array of integers. e.g. [[1,2,[3]],4] -> [1,2,3,4]. I'm particularly looking for some feedback on the following:

NumPy Array Manipulation. A practical guide to modify the shape , Reshape; Expand_dims; Ravel and Flatten. If you would like to Reshape. Numpy provides flexible tools to change the dimension of an array. Introduction. NumPy is a Python library consisting of multi-dimensional array objects and a collection of routines for processing of array. It stands for Numerical Python.

Changing Dimensions of Arrays, Flatten and Reshape Arrays. There are two methods to flatten a multidimensional array: flatten(); ravel()� ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’. Returns: y: ndarray. A copy of the input array, flattened to one dimension.