Splitting a list into N parts of approximately equal length

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What is the best way to divide a list into roughly equal parts? For example, if the list has 7 elements and is split it into 2 parts, we want to get 3 elements in one part, and the other should have 4 elements.

I'm looking for something like even_split(L, n) that breaks L into n parts.

def chunks(L, n):
    """ Yield successive n-sized chunks from L.
    """
    for i in range(0, len(L), n):
        yield L[i:i+n]

The code above gives chunks of 3, rather than 3 chunks. I could simply transpose (iterate over this and take the first element of each column, call that part one, then take the second and put it in part two, etc), but that destroys the ordering of the items.

35 Answers

You can write it fairly simply as a list generator:

def split(a, n):
    k, m = divmod(len(a), n)
    return (a[i*k+min(i, m):(i+1)*k+min(i+1, m)] for i in range(n))

Example:

>>> list(split(range(11), 3))
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10]]

As long as you don't want anything silly like continuous chunks:

>>> def chunkify(lst,n):
...     return [lst[i::n] for i in xrange(n)]
... 
>>> chunkify(range(13), 3)
[[0, 3, 6, 9, 12], [1, 4, 7, 10], [2, 5, 8, 11]]

This code is broken due to rounding errors. Do not use it!!!

assert len(chunkIt([1,2,3], 10)) == 10  # fails

Here's one that could work:

def chunkIt(seq, num):
    avg = len(seq) / float(num)
    out = []
    last = 0.0

    while last < len(seq):
        out.append(seq[int(last):int(last + avg)])
        last += avg

    return out

Testing:

>>> chunkIt(range(10), 3)
[[0, 1, 2], [3, 4, 5], [6, 7, 8, 9]]
>>> chunkIt(range(11), 3)
[[0, 1, 2], [3, 4, 5, 6], [7, 8, 9, 10]]
>>> chunkIt(range(12), 3)
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]

Changing the code to yield n chunks rather than chunks of n:

def chunks(l, n):
    """ Yield n successive chunks from l.
    """
    newn = int(len(l) / n)
    for i in xrange(0, n-1):
        yield l[i*newn:i*newn+newn]
    yield l[n*newn-newn:]

l = range(56)
three_chunks = chunks (l, 3)
print three_chunks.next()
print three_chunks.next()
print three_chunks.next()

which gives:

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]
[36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]

This will assign the extra elements to the final group which is not perfect but well within your specification of "roughly N equal parts" :-) By that, I mean 56 elements would be better as (19,19,18) whereas this gives (18,18,20).

You can get the more balanced output with the following code:

#!/usr/bin/python
def chunks(l, n):
    """ Yield n successive chunks from l.
    """
    newn = int(1.0 * len(l) / n + 0.5)
    for i in xrange(0, n-1):
        yield l[i*newn:i*newn+newn]
    yield l[n*newn-newn:]

l = range(56)
three_chunks = chunks (l, 3)
print three_chunks.next()
print three_chunks.next()
print three_chunks.next()

which outputs:

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]
[19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37]
[38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]

This will do the split into equal parts by one single expression while keeping the order:

myList = list(range(18))  # given list
N = 5  # desired number of parts

[myList[(i*len(myList))//N:((i+1)*len(myList))//N] for i in range(N)]
# [[0, 1, 2], [3, 4, 5, 6], [7, 8, 9], [10, 11, 12, 13], [14, 15, 16, 17]]

The parts will differ in not more than one element. The split of 18 into 5 parts results in 3 + 4 + 3 + 4 + 4 = 18.

Here is one that adds None to make the lists equal length

>>> from itertools import izip_longest
>>> def chunks(l, n):
    """ Yield n successive chunks from l. Pads extra spaces with None
    """
    return list(zip(*izip_longest(*[iter(l)]*n)))

>>> l=range(54)

>>> chunks(l,3)
[(0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51), (1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31, 34, 37, 40, 43, 46, 49, 52), (2, 5, 8, 11, 14, 17, 20, 23, 26, 29, 32, 35, 38, 41, 44, 47, 50, 53)]

>>> chunks(l,4)
[(0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52), (1, 5, 9, 13, 17, 21, 25, 29, 33, 37, 41, 45, 49, 53), (2, 6, 10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50, None), (3, 7, 11, 15, 19, 23, 27, 31, 35, 39, 43, 47, 51, None)]

>>> chunks(l,5)
[(0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50), (1, 6, 11, 16, 21, 26, 31, 36, 41, 46, 51), (2, 7, 12, 17, 22, 27, 32, 37, 42, 47, 52), (3, 8, 13, 18, 23, 28, 33, 38, 43, 48, 53), (4, 9, 14, 19, 24, 29, 34, 39, 44, 49, None)]

Have a look at numpy.split:

>>> a = numpy.array([1,2,3,4])
>>> numpy.split(a, 2)
[array([1, 2]), array([3, 4])]

Let's say you want to split a list [1, 2, 3, 4, 5, 6, 7, 8] into 3 element lists

like [[1,2,3], [4, 5, 6], [7, 8]], where if the last remaining elements left are less than 3, they are grouped together.

my_list = [1, 2, 3, 4, 5, 6, 7, 8]
my_list2 = [my_list[i:i+3] for i in range(0, len(my_list), 3)]
print(my_list2)

Output: [[1,2,3], [4, 5, 6], [7, 8]]

Where length of one part is 3. Replace 3 with your own chunk size.

My solution, easy to understand

def split_list(lst, n):
    splitted = []
    for i in reversed(range(1, n + 1)):
        split_point = len(lst)//i
        splitted.append(lst[:split_point])
        lst = lst[split_point:]
    return splitted

And shortest one-liner on this page(written by my girl)

def split(l, n):
    return [l[int(i*len(l)/n):int((i+1)*len(l)/n-1)] for i in range(n)]

Elegant:

[x.tolist() for x in np.array_split(range(10), 3)]

Another way would be something like this, the idea here is to use grouper, but get rid of None. In this case we'll have all 'small_parts' formed from elements at the first part of the list, and 'larger_parts' from the later part of the list. Length of 'larger parts' is len(small_parts) + 1. We need to consider x as two different sub-parts.

from itertools import izip_longest

import numpy as np

def grouper(n, iterable, fillvalue=None): # This is grouper from itertools
    "grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx"
    args = [iter(iterable)] * n
    return izip_longest(fillvalue=fillvalue, *args)

def another_chunk(x,num):
    extra_ele = len(x)%num #gives number of parts that will have an extra element 
    small_part = int(np.floor(len(x)/num)) #gives number of elements in a small part

    new_x = list(grouper(small_part,x[:small_part*(num-extra_ele)]))
    new_x.extend(list(grouper(small_part+1,x[small_part*(num-extra_ele):])))

    return new_x

The way I have it set up returns a list of tuples:

>>> x = range(14)
>>> another_chunk(x,3)
[(0, 1, 2, 3), (4, 5, 6, 7, 8), (9, 10, 11, 12, 13)]
>>> another_chunk(x,4)
[(0, 1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12, 13)]
>>> another_chunk(x,5)
[(0, 1), (2, 3, 4), (5, 6, 7), (8, 9, 10), (11, 12, 13)]
>>> 
#!/usr/bin/python


first_names = ['Steve', 'Jane', 'Sara', 'Mary','Jack','Bob', 'Bily', 'Boni', 'Chris','Sori', 'Will', 'Won','Li']

def chunks(l, n):
for i in range(0, len(l), n):
    # Create an index range for l of n items:
    yield l[i:i+n]

result = list(chunks(first_names, 5))
print result

Picked from this link, and this was what helped me. I had a pre-defined list.

def evenly(l, n):
    len_ = len(l)
    split_size = len_ // n
    split_size = n if not split_size else split_size
    offsets = [i for i in range(0, len_, split_size)]
    return [l[offset:offset + split_size] for offset in offsets]

Example:

l = [a for a in range(97)] should be consist of 10 parts, each have 9 elements except the last one.

Output:

[[0, 1, 2, 3, 4, 5, 6, 7, 8],
 [9, 10, 11, 12, 13, 14, 15, 16, 17],
 [18, 19, 20, 21, 22, 23, 24, 25, 26],
 [27, 28, 29, 30, 31, 32, 33, 34, 35],
 [36, 37, 38, 39, 40, 41, 42, 43, 44],
 [45, 46, 47, 48, 49, 50, 51, 52, 53],
 [54, 55, 56, 57, 58, 59, 60, 61, 62],
 [63, 64, 65, 66, 67, 68, 69, 70, 71],
 [72, 73, 74, 75, 76, 77, 78, 79, 80],
 [81, 82, 83, 84, 85, 86, 87, 88, 89],
 [90, 91, 92, 93, 94, 95, 96]]

1>

import numpy as np

data # your array

total_length = len(data)
separate = 10
sub_array_size = total_length // separate
safe_separate = sub_array_size * separate

splited_lists = np.split(np.array(data[:safe_separate]), separate)
splited_lists[separate - 1] = np.concatenate(splited_lists[separate - 1], 
np.array(data[safe_separate:total_length]))

splited_lists # your output

2>

splited_lists = np.array_split(np.array(data), separate)
def chunkify(target_list, chunk_size):
    return [target_list[i:i+chunk_size] for i in range(0, len(target_list), chunk_size)]

>>> l = [5432, 432, 67, "fdas", True, True, False, (4324,131), 876, "ofsa", 8, 909, b'765']
>>> print(chunkify(l, 3))
>>> [[5432, 432, 67], ['fdas', True, True], [False, (4324, 131), 876], ['ofsa', 8, 909], [b'765']]

say you want to split into 5 parts:

p1, p2, p3, p4, p5 = np.split(df, 5)

I've written code in this case myself:

def chunk_ports(port_start, port_end, portions):
    if port_end < port_start:
        return None

    total = port_end - port_start + 1

    fractions = int(math.floor(float(total) / portions))

    results = []

    # No enough to chuck.
    if fractions < 1:
        return None

    # Reverse, so any additional items would be in the first range.
    _e = port_end
    for i in range(portions, 0, -1):
        print "i", i

        if i == 1:
            _s = port_start
        else:
            _s = _e - fractions + 1

        results.append((_s, _e))

        _e = _s - 1

    results.reverse()

    return results

divide_ports(1, 10, 9) would return

[(1, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10)]

this code works for me (Python3-compatible):

def chunkify(tab, num):
    return [tab[i*num: i*num+num] for i in range(len(tab)//num+(1 if len(tab)%num else 0))]

example (for bytearray type, but it works for lists as well):

b = bytearray(b'\x01\x02\x03\x04\x05\x06\x07\x08')
>>> chunkify(b,3)
[bytearray(b'\x01\x02\x03'), bytearray(b'\x04\x05\x06'), bytearray(b'\x07\x08')]
>>> chunkify(b,4)
[bytearray(b'\x01\x02\x03\x04'), bytearray(b'\x05\x06\x07\x08')]

This one provides chunks of length <= n, >= 0

def

 chunkify(lst, n):
    num_chunks = int(math.ceil(len(lst) / float(n))) if n < len(lst) else 1
    return [lst[n*i:n*(i+1)] for i in range(num_chunks)]

for example

>>> chunkify(range(11), 3)
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10]]
>>> chunkify(range(11), 8)
[[0, 1, 2, 3, 4, 5, 6, 7], [8, 9, 10]]

I tried most part of solutions, but they didn't work for my case, so I make a new function that work for most of cases and for any type of array:

import math

def chunkIt(seq, num):
    seqLen = len(seq)
    total_chunks = math.ceil(seqLen / num)
    items_per_chunk = num
    out = []
    last = 0

    while last < seqLen:
        out.append(seq[last:(last + items_per_chunk)])
        last += items_per_chunk

    return out
def chunk_array(array : List, n: int) -> List[List]:
    chunk_size = len(array) // n 
    chunks = []
    i = 0
    while i < len(array):
        # if less than chunk_size left add the remainder to last element
        if len(array) - (i + chunk_size + 1) < 0:
            chunks[-1].append(*array[i:i + chunk_size])
            break
        else:
            chunks.append(array[i:i + chunk_size])
            i += chunk_size
    return chunks

here's my version (inspired from Max's)

n = len(lst)
# p is the number of parts to be divided
x = int(n/p)

i = 0
j = x
lstt = []
while (i< len(lst) or j <len(lst)):
    lstt.append(lst[i:j])
    i+=x
    j+=x
print(lstt)

This is the simplest answer if it is known that the list divides into equal parts.

If you don't mind that the order will be changed, I recommend you to use @job solution, otherwise, you can use this:

def chunkIt(seq, num):
    steps = int(len(seq) / float(num))
    out = []
    last = 0.0

    while last < len(seq):
        if len(seq) - (last + steps) < steps:
            until = len(seq)
            steps = len(seq) - last
        else:
            until = int(last + steps)
        out.append(seq[int(last): until])
        last += steps
return out

Another attempt at simple readable chunker that works.

def chunk(iterable, count): # returns a *generator* that divides `iterable` into `count` of contiguous chunks of similar size
    assert count >= 1
    return (iterable[int(_*len(iterable)/count+0.5):int((_+1)*len(iterable)/count+0.5)] for _ in range(count))

print("Chunk count:  ", len(list(         chunk(range(105),10))))
print("Chunks:       ",     list(         chunk(range(105),10)))
print("Chunks:       ",     list(map(list,chunk(range(105),10))))
print("Chunk lengths:",     list(map(len, chunk(range(105),10))))

print("Testing...")
for iterable_length in range(100):
    for chunk_count in range(1,100):
        chunks = list(chunk(range(iterable_length),chunk_count))
        assert chunk_count == len(chunks)
        assert iterable_length == sum(map(len,chunks))
        assert all(map(lambda _:abs(len(_)-iterable_length/chunk_count)<=1,chunks))
print("Okay")

Outputs:

Chunk count:   10
Chunks:        [range(0, 11), range(11, 21), range(21, 32), range(32, 42), range(42, 53), range(53, 63), range(63, 74), range(74, 84), range(84, 95), range(95, 105)]
Chunks:        [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12, 13, 14, 15, 16, 17, 18, 19, 20], [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], [53, 54, 55, 56, 57, 58, 59, 60, 61, 62], [63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73], [74, 75, 76, 77, 78, 79, 80, 81, 82, 83], [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94], [95, 96, 97, 98, 99, 100, 101, 102, 103, 104]]
Chunk lengths: [11, 10, 11, 10, 11, 10, 11, 10, 11, 10]
Testing...
Okay
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