如何使数字的新名单不追加到自己的名单？

Question

如果我有一个多维列表称为T，我从列表中的一些数字追加到一个名为TC新的列表，我怎么把所有那些没有在自己的列表附加到新的列表，并把他们的号码，称为nonTC？例如：

t = [[1, 3, 4, 5, 6, 7],[9, 7, 4, 5, 2], [3, 4, 5]]

我写了一些条件，只有一些值从每个列表追加到创建新的列表，TC：

TC = [[3, 4, 6], [9, 7, 2], [5]]

我怎么不包括在TC值追加到自己的名单？所以，我会得到：

nonTC = [[1, 5, 7],[4, 5],[3,4]]

Answer 1

您可以使用列表内涵和集列表来过滤原始列表：

t = [[1, 3, 4, 5, 6, 7],[9, 7, 4, 5, 2], [3, 4, 5]]

# filter sets - each index corresponds to one inner list of t - the numbers in the 
# set should be put into TC - those that are not go into nonTC
getem = [{3,4,6},{9,7,2},{5}]

TC = [ [p for p in part if p in getem[i]] for i,part in enumerate(t)]
print(TC)

nonTC = [ [p for p in part if p not in getem[i]] for i,part in enumerate(t)]     
print(nonTC)

输出：

[[3, 4, 6], [9, 7, 2], [5]] # TC
[[1, 5, 7], [4, 5], [3, 4]] # nonTC

电文读出：

• list comprehensions
• sets
• enumerate(iterable)

和：Explanation of how nested list comprehension works?

---

建议其他办法做到这一点，creds到AChampion：

TC_1 = [[p for p in part if p in g] for g, part in zip(getem, t)]
nonTC_1 = [[p for p in part if p not in g] for g, part in zip(getem, t)]

见zip() - 它本质上捆绑了两个列表成为元组的迭代

( (t[0],getem[0]), (t[1],getem[1]) (t[2],getem[2])) 

---

添加为多次出现 - 福费廷列表比较，并设置：

t = [[1, 3, 4, 5, 6, 7, 3, 3, 3],[9, 7, 4, 5, 2], [3, 4, 5]]

# filter lists - each index corresponds to one inner list of t - the numbers in the list
# should be put into TC - those that are not go into nonTC - exactly with the amounts given
getem = [[3,3,4,6],[9,7,2],[5]]

from collections import Counter
TC = []
nonTC = []
for f, part in zip(getem,t):
    TC.append([])
    nonTC.append([])
    c = Counter(f) 
    for num in part:
        if c.get(num,0) > 0:
            TC[-1].append(num)
            c[num]-=1
        else:
            nonTC[-1].append(num)            

print(TC)    # [[3, 4, 6, 3], [9, 7, 2], [5]]
print(nonTC) # [[1, 5, 7, 3, 3], [4, 5], [3, 4]]

它只需1您的项目，而不是2（单独的列表谱曲）通这使得它可能更多的从长远来看，有效的...

Answer 2

只是出于好奇，用NumPy的：

import numpy as np

t = [[1, 3, 4, 5, 6, 7],[9, 7, 4, 5, 2], [3, 4, 5]]
TC = [[3, 4, 6], [9, 7, 2], [5]]

print([np.setdiff1d(a, b) for a, b in zip(t, TC)])
#=> [array([1, 5, 7]), array([4, 5]), array([3, 4])]