如何将任意长度的列表拆分为大小相等的块?
请参阅如果数据结果将直接用于循环,并且不需要存储,则如何以块形式遍历列表。
对于字符串输入的同一问题,请参见每n个字符拆分字符串?。相同的技术通常适用,但也有一些变化。
如何将任意长度的列表拆分为大小相等的块?
请参阅如果数据结果将直接用于循环,并且不需要存储,则如何以块形式遍历列表。
对于字符串输入的同一问题,请参见每n个字符拆分字符串?。相同的技术通常适用,但也有一些变化。
当前回答
我不喜欢按块大小拆分元素的想法,例如,脚本可以将101到3个块划分为[50,50,1]。为了我的需要,我需要按比例分配,保持秩序不变。首先我写了自己的剧本,效果很好,而且很简单。但我后来看到了这个答案,剧本比我的好,我想是这样的。这是我的脚本:
def proportional_dividing(N, n):
"""
N - length of array (bigger number)
n - number of chunks (smaller number)
output - arr, containing N numbers, diveded roundly to n chunks
"""
arr = []
if N == 0:
return arr
elif n == 0:
arr.append(N)
return arr
r = N // n
for i in range(n-1):
arr.append(r)
arr.append(N-r*(n-1))
last_n = arr[-1]
# last number always will be r <= last_n < 2*r
# when last_n == r it's ok, but when last_n > r ...
if last_n > r:
# ... and if difference too big (bigger than 1), then
if abs(r-last_n) > 1:
#[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 7] # N=29, n=12
# we need to give unnecessary numbers to first elements back
diff = last_n - r
for k in range(diff):
arr[k] += 1
arr[-1] = r
# and we receive [3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2]
return arr
def split_items(items, chunks):
arr = proportional_dividing(len(items), chunks)
splitted = []
for chunk_size in arr:
splitted.append(items[:chunk_size])
items = items[chunk_size:]
print(splitted)
return splitted
items = [1,2,3,4,5,6,7,8,9,10,11]
chunks = 3
split_items(items, chunks)
split_items(['a','b','c','d','e','f','g','h','i','g','k','l', 'm'], 3)
split_items(['a','b','c','d','e','f','g','h','i','g','k','l', 'm', 'n'], 3)
split_items(range(100), 4)
split_items(range(99), 4)
split_items(range(101), 4)
和输出:
[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11]]
[['a', 'b', 'c', 'd'], ['e', 'f', 'g', 'h'], ['i', 'g', 'k', 'l', 'm']]
[['a', 'b', 'c', 'd', 'e'], ['f', 'g', 'h', 'i', 'g'], ['k', 'l', 'm', 'n']]
[range(0, 25), range(25, 50), range(50, 75), range(75, 100)]
[range(0, 25), range(25, 50), range(50, 75), range(75, 99)]
[range(0, 25), range(25, 50), range(50, 75), range(75, 101)]
其他回答
这是一个生成大小均匀的块的生成器:
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
for i in range(0, len(lst), n):
yield lst[i:i + n]
import pprint
pprint.pprint(list(chunks(range(10, 75), 10)))
[[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]]
对于Python 2,使用xrange代替range:
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
for i in xrange(0, len(lst), n):
yield lst[i:i + n]
下面是一行理解列表。不过,上面的方法更可取,因为使用命名函数使代码更容易理解。对于Python 3:
[lst[i:i + n] for i in range(0, len(lst), n)]
对于Python 2:
[lst[i:i + n] for i in xrange(0, len(lst), n)]
如果您知道列表大小:
def SplitList(mylist, chunk_size):
return [mylist[offs:offs+chunk_size] for offs in range(0, len(mylist), chunk_size)]
如果没有(迭代器):
def IterChunks(sequence, chunk_size):
res = []
for item in sequence:
res.append(item)
if len(res) >= chunk_size:
yield res
res = []
if res:
yield res # yield the last, incomplete, portion
在后一种情况下,如果您可以确保序列始终包含给定大小的整数个块(即没有不完整的最后一个块),则可以用更漂亮的方式重新表述。
就像@AaronHall我来这里找的是大小大致均匀的大块。对此有不同的解释。在我的例子中,如果期望的大小是N,我希望每个组的大小>=N。因此,在上述大多数情况下产生的孤儿应重新分配给其他群体。
这可以通过以下方式完成:
def nChunks(l, n):
""" Yield n successive chunks from l.
Works for lists, pandas dataframes, etc
"""
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:]
(通过将列表拆分为N个长度大致相等的部分),只需将其称为nChunks(l,l/N)或nChunk(l,floor(l/N))
def chunk(lst):
out = []
for x in xrange(2, len(lst) + 1):
if not len(lst) % x:
factor = len(lst) / x
break
while lst:
out.append([lst.pop(0) for x in xrange(factor)])
return out
与任何可迭代的内部数据是生成器对象(不是列表)一个衬垫
In [259]: get_in_chunks = lambda itr,n: ( (v for _,v in g) for _,g in itertools.groupby(enumerate(itr),lambda (ind,_): ind/n)) In [260]: list(list(x) for x in get_in_chunks(range(30),7)) Out[260]: [[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]]