Python:重建嵌套列表
Python:重建嵌套列表
提问于 2018-10-18 03:17:23
我有一个嵌套的列表：
output= [('the', 'B', 'NNP'), ('wall', 'I', 'NNP'), ('street', 'I', 'NNP'), ('journal', 'I', 'NNP'), ('reported', 'O', 'VB'), ('today', 'O', 'NNP'), ('that', 'O', 'NNP'), ('apple', 'B', 'NNP'), ('corporation', 'I', 'NNP'), ('made', 'O', 'VB'), ('money', 'O', 'NNP'), ('.', 'O', '.'), ('georgia', 'B', 'NNP'), ('tech', 'I', 'NNP'), ('is', 'O', 'NNP'), ('a', 'O', '.'), ('university', 'O', 'NNP'), ('in', 'O', 'NNP'), ('georgia', 'B', 'NNP'),('.', 'O', '.')]我想将其重新格式化为以下预期格式：
new_output= [(['the', 'wall', 'street', 'journal', 'reported', 'today', 'that', 'apple', 'corporation', 'made', 'money'], ['B', 'I', 'I', 'I', 'O', 'O', 'O', 'B', 'I', 'O', 'O']), (['georgia', 'tech', 'is', 'a', 'university', 'in', 'georgia'], ['B', 'I', 'O', 'O', 'O', 'O', 'B'])]我的尝试是：
import string
word = []
token = []
result_word = []
result_token = []
result = []
for i in output[0]:
for every_word in i:
word.append(every_word)
result_word = " ".join(" ".join(word).split()[::3])怎样才能得到我想要的格式？
回答 1
Stack Overflow用户
发布于 2018-10-18 03:37:16
您可以使用groupby将非句点项分组为句子，然后使用zip从词性指示器中拆分单词：
from itertools import groupby
l = output= [('the', 'B', 'NNP'), ('wall', 'I', 'NNP'), ('street', 'I', 'NNP'), ('journal', 'I', 'NNP'), ('reported', 'O', 'VB'), ('today', 'O', 'NNP'), ('that', 'O', 'NNP'), ('apple', 'B', 'NNP'), ('corporation', 'I', 'NNP'), ('made', 'O', 'VB'), ('money', 'O', 'NNP'), ('.', 'O', '.'), ('georgia', 'B', 'NNP'), ('tech', 'I', 'NNP'), ('is', 'O', 'NNP'), ('a', 'O', '.'), ('university', 'O', 'NNP'), ('in', 'O', 'NNP'), ('georgia', 'B', 'NNP'),('.', 'O', '.')]
groups = (g for k, g in groupby(l, lambda x: x[0] != '.') if k)
zs = (zip(*g) for g in groups)
res = [(next(z), next(z)) for z in zs]然后是res
[(('the', 'wall', 'street', 'journal', 'reported', 'today', 'that', 'apple', 'corporation', 'made', 'money'),
('B', 'I', 'I', 'I', 'O', 'O', 'O', 'B', 'I', 'O', 'O')),
(('georgia', 'tech', 'is', 'a', 'university', 'in', 'georgia'),
('B', 'I', 'O', 'O', 'O', 'O', 'B'))
]页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/52862121
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