Python 将列表拆分为长度大致相等的N个部分
将列表大致等分的最佳方法是什么?例如,如果列表有7个元素,并将其拆分为2个部分,那么我们希望在一个部分中包含3个元素,而另一个部分应该包含4个元素 我正在寻找类似于Python 将列表拆分为长度大致相等的N个部分,python,list,chunks,Python,List,Chunks,将列表大致等分的最佳方法是什么?例如,如果列表有7个元素,并将其拆分为2个部分,那么我们希望在一个部分中包含3个元素,而另一个部分应该包含4个元素 我正在寻找类似于偶数分裂(L,n)的东西,它将L分解为n部分 def chunks(L, n): """ Yield successive n-sized chunks from L. """ for i in range(0, len(L), n): yield L[i:i+n] 上面的代码给出了3个块,而
偶数分裂(L,n)
的东西,它将L
分解为n
部分
def chunks(L, n):
""" Yield successive n-sized chunks from L.
"""
for i in range(0, len(L), n):
yield L[i:i+n]
上面的代码给出了3个块,而不是3个块。我可以简单地进行转置(迭代此项并获取每列的第一个元素,调用第一部分,然后获取第二部分并将其放入第二部分,等等),但这会破坏项目的顺序。此代码因舍入错误而中断。不要用它强>
assert len(chunkIt([1,2,3], 10)) == 10 # fails
以下是一个可行的方法:
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
将代码更改为生成
n
块而不是n
块:
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()
其中:
[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]
这将把额外的元素分配给最后一组,这不是完美的,但在“大致N个相等的部分”的规范范围内:-)我的意思是,56个元素将更好地作为(19,19,18),而这将给出(18,18,20)
您可以使用以下代码获得更平衡的输出:
#!/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()
哪些产出:
[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]
下面是一个添加
None
使列表长度相等的方法
>>> 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)]
您可以相当简单地将其编写为列表生成器:
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))
例如:
>>> list(split(range(11), 3))
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10]]
只要你不想要像连续块这样愚蠢的东西:
>>> 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]]
看看:
另一种方法是这样的,这里的想法是使用石斑鱼,但不要使用
None
。在本例中,我们将使用列表第一部分的元素形成所有“小部分”,并使用列表后面部分的元素形成“大部分”。“较大零件”的长度为len(小零件)+1。我们需要考虑X作为两个不同的子部分。< /P>
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
我设置它的方式返回元组列表:
>>> 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)]
>>>
下面是另一个变体,它将“剩余”元素均匀地分布在所有块中,一次一个,直到没有剩余的元素。在这个实现中,较大的块出现在流程的开始
def chunks(l, k):
""" Yield k successive chunks from l."""
if k < 1:
yield []
raise StopIteration
n = len(l)
avg = n/k
remainders = n % k
start, end = 0, avg
while start < n:
if remainders > 0:
end = end + 1
remainders = remainders - 1
yield l[start:end]
start, end = end, end+avg
与答案相同,但考虑了大小小于chunck数的列表
def chunkify(lst,n):
[ lst[i::n] for i in xrange(n if n < len(lst) else len(lst)) ]
def chunkify(lst,n):
[lst[i::n]表示x范围内的i(如果n
如果n(块数)是7,而lst(要划分的列表)是[1,2,3],则块是[[0],[1],[2]],而不是[[0],[1],[2],[],[],[],[],[],[],[]以下是我的解决方案:
def chunks(l, amount):
if amount < 1:
raise ValueError('amount must be positive integer')
chunk_len = len(l) // amount
leap_parts = len(l) % amount
remainder = amount // 2 # make it symmetrical
i = 0
while i < len(l):
remainder += leap_parts
end_index = i + chunk_len
if remainder >= amount:
remainder -= amount
end_index += 1
yield l[i:end_index]
i = end_index
您还可以使用:
split=lambda x,n: x if not x else [x[:n]]+[split([] if not -(len(x)-n) else x[-(len(x)-n):],n)][0]
split([1,2,3,4,5,6,7,8,9],2)
[[1, 2], [3, 4], [5, 6], [7, 8], [9]]
使用numpy.linspace方法实现 只需指定阵列要分割的部分数量。分割大小几乎相等 例如: 给出:
Input array: [0 1 2 3 4 5 6 7 8 9]
Array split in to 3 parts : [array([0, 1, 2]), array([3, 4, 5]), array([6, 7, 8, 9])]
使用列表理解:
def divide_list_to_chunks(list_, n):
return [list_[start::n] for start in range(n)]
[l[i * (n // k) + min(i, n % k):(i+1) * (n // k) + min(i+1, n % k)] for i in range(k)]
如果将
n
元素分成大致k
块,则可以使n%k
块比其他块大1个元素来分配额外的元素
以下代码将为您提供块的长度:
[(n // k) + (1 if i < (n % k) else 0) for i in range(k)]
[i * (n // k) + min(i, n % k) for i in range(k)]
示例:n=11,k=3
导致[0,4,8]
使用i+1
th块作为边界,我们得到lenn
的列表l
的i
th块是
l[i * (n // k) + min(i, n % k):(i+1) * (n // k) + min(i+1, n % k)]
最后一步,使用列表理解从所有区块创建列表:
def divide_list_to_chunks(list_, n):
return [list_[start::n] for start in range(n)]
[l[i * (n // k) + min(i, n % k):(i+1) * (n // k) + min(i+1, n % k)] for i in range(k)]
示例:
n=11,k=3,l=range(n)
导致[范围(0,4),范围(4,8),范围(8,11)]
将邻域四舍五入并将其用作索引比amit12690提出的解决方案更简单
function chunks=chunkit(array,num)
index = round(linspace(0,size(array,2),num+1));
chunks = cell(1,num);
for x = 1:num
chunks{x} = array(:,index(x)+1:index(x+1));
end
end
这就是*存在的理由:
*这是一个生成器,可以处理任何正(整数)数量的块。如果区块数大于输入列表长度,则某些区块将为空。该算法在短块和长块之间交替,而不是将它们分开 我还包含了一些测试
ragged_chunks
函数的代码
''' Split a list into "ragged" chunks
The size of each chunk is either the floor or ceiling of len(seq) / chunks
chunks can be > len(seq), in which case there will be empty chunks
Written by PM 2Ring 2017.03.30
'''
def ragged_chunks(seq, chunks):
size = len(seq)
start = 0
for i in range(1, chunks + 1):
stop = i * size // chunks
yield seq[start:stop]
start = stop
# test
def test_ragged_chunks(maxsize):
for size in range(0, maxsize):
seq = list(range(size))
for chunks in range(1, size + 1):
minwidth = size // chunks
#ceiling division
maxwidth = -(-size // chunks)
a = list(ragged_chunks(seq, chunks))
sizes = [len(u) for u in a]
deltas = all(minwidth <= u <= maxwidth for u in sizes)
assert all((sum(a, []) == seq, sum(sizes) == size, deltas))
return True
if test_ragged_chunks(100):
print('ok')
这将通过一个表达式将其拆分为相等的部分,同时保持顺序:
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]]
各部分的差异不超过一个元素。将18分为5部分,结果是3+4+3+4+4=18。我的解决方案,简单易懂
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
这一页上最短的一行(我女儿写的)
见:
安装通过
从中挑选,这就是帮助我的原因。我有一个预定义的列表。假设您想分成5部分:
p1, p2, p3, p4, p5 = np.split(df, 5)
在这种情况下,我自己编写了代码:
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
此代码适用于我(与Python 3兼容):
例如(对于bytearray类型,但它也适用于lists):
这一个提供长度为0的块 def
我尝试了大部分解决方案,但它们不适用于我的情况,因此我制作了一个新函数,适用于大多数情况和任何类型的数组:
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
导入数学
def chunkIt(序号,数字):
seqLen=len(seq)
total_chunks=math.ceil(seqLen/num)
每个区块的项目数=num
out=[]
最后一个=0
而最后一个
def均匀(l,n):
len=len(l)
拆分大小=长度//n
拆分大小=n如果不拆分大小,则为其他拆分大小
偏移量=[i代表范围内的i(0,长度,分割大小)]
返回[l[偏移量:偏移量+分割大小]用于偏移量中的偏移量]
示例:
[[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]]
l=[a代表范围(97)]
应由10个部分组成,每个部分有9个元素,最后一个除外
输出:
[[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]]
假设您要将列表[1,2,3,4,5,6,7,8]拆分为3个元素列表 与[[1,2,3],[4,5,6],[7,8]]类似,如果最后剩下的元素少于3,则将它们分组在一起
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)
输出:[[1,2,3]、[4,5,6]、[7,8]]
其中一个零件的长度为3。用您自己的块大小替换3。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>
埃尔
#!/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
p1, p2, p3, p4, p5 = np.split(df, 5)
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
[(1, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10)]
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))]
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')]
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)]
>>> 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]]
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
[[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]]
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)
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
splited_lists = np.array_split(np.array(data), separate)
[x.tolist() for x in np.array_split(range(10), 3)]