在Python中将文本文件中的列数据转换为嵌套列表？
我有一个在Python中将文本文件中的列数据转换为嵌套列表？,python,type-conversion,nested-lists,named-entity-recognition,Python,Type Conversion,Nested Lists,Named Entity Recognition,我有一个txt文件，其中包含按列书写的句子和标签，如下所示： O are O there O any O good B-GENRE romantic I-GENRE comedies O out B-YEAR right I-YEAR now O show O me O a O movie O about B-PLOT cars I-PLOT that I-PLOT talk 我想将这个txt文件中的数据读入两个嵌套列表。 所需的输出应如下所
txtO are
O there
O any
O good
B-GENRE romantic
I-GENRE comedies
O out
B-YEAR right
I-YEAR now
O show
O me
O a
O movie
O about
B-PLOT cars
I-PLOT that
I-PLOT talk
txtlabels = [['O','O','O','O','B-GENRE','I-GENRE','O','B-YEAR','I-YEAR'],['O','O','O','O','O','B-PLOT','I-PLOT','I-PLOT']]
sentences = [['are','there','any','good','romantic','comedies','out','right','now'],['show','me','a','movie','about','cars','that','talk']]
with open("engtrain.bio.txt", "r") as f:
lsta = []
for line in f:
lsta.append([x for x in line.replace("\n", "").split()])
with open("engtest.bio.txt", "r") as f:
lines = f.readlines()
labels = []
sentences = []
for l in lines:
as_list = l.split("\t")
labels.append(as_list[0])
sentences.append(as_list[1].replace("\n", ""))
[['O', 'are'],
['O', 'there'],
['O', 'any'],
['O', 'good'],
['B-GENRE', 'romantic'],
['I-GENRE', 'comedies'],
['O', 'out'],
['B-YEAR', 'right'],
['I-YEAR', 'now'],
[],
['O', 'show'],
['O', 'me'],
['O', 'a'],
['O', 'movie'],
['O', 'about'],
['B-PLOT', 'cars'],
['I-PLOT', 'that'],
['I-PLOT', 'talk']]
with open("engtrain.bio.txt", "r") as f:
lsta = []
for line in f:
lsta.append([x for x in line.replace("\n", "").split()])
with open("engtest.bio.txt", "r") as f:
lines = f.readlines()
labels = []
sentences = []
for l in lines:
as_list = l.split("\t")
labels.append(as_list[0])
sentences.append(as_list[1].replace("\n", ""))
IndexError Traceback (most recent call last)
<ipython-input-66-63c266df6ace> in <module>()
6 as_list = l.strip().split("\t")
7 labels.append(as_list[0])
----> 8 sentences.append(as_list[1].replace("\n", ""))
IndexError: list index out of range
索引器错误回溯（最近一次调用）
在（）
6 as_list=l.strip（）.split（“\t”）
7标签。追加（作为列表[0]）
---->8个句子。追加（如列表[1]。替换（“\n”，”）
索引器：列表索引超出范围
提前感谢迭代每一行，并按
选项卡将其拆分all_labels, all_sentences = [], []
with open('inp', 'r') as f:
lines = f.readlines()
lines.append('') # make sure we process the last sentence
labels, sentences = [], []
for line in lines:
line = line.strip()
if not line: # detect the end of a sentence
if len(labels): # make sure we got some words here
all_labels.append(labels)
all_sentences.append(sentences)
labels, sentences = [], []
continue
# extend the current sentence
label, sentence = line.split()
labels.append(label)
sentences.append(sentence)
print(all_labels)
print(all_sentences)
labels = [[]]
sentences = [[]]
with open('engtrain.bio', 'r') as f:
for line in f.readlines():
line = line.rstrip()
if line:
label, sentence = line.split('\t')
labels[-1].append(label)
sentences[-1].append(sentence)
else:
labels.append([])
sentences.append([])
标签[['O', 'O', 'O', 'B-ACTOR', 'I-ACTOR'], ['O', 'O', 'O', 'O', 'B-ACTOR', 'I-ACTOR', 'O', 'O', 'B-YEAR'] ...
[['what', 'movies', 'star', 'bruce', 'willis'], ['show', 'me', 'films', 'with', 'drew', 'barrymore', 'from', 'the', '1980s'] ...
迭代每行并按
选项卡将其拆分：
labels = [[]]
sentences = [[]]
with open('engtrain.bio', 'r') as f:
for line in f.readlines():
line = line.rstrip()
if line:
label, sentence = line.split('\t')
labels[-1].append(label)
sentences[-1].append(sentence)
else:
labels.append([])
sentences.append([])
输出标签
：
[['O', 'O', 'O', 'B-ACTOR', 'I-ACTOR'], ['O', 'O', 'O', 'O', 'B-ACTOR', 'I-ACTOR', 'O', 'O', 'B-YEAR'] ...
输出句子[['what', 'movies', 'star', 'bruce', 'willis'], ['show', 'me', 'films', 'with', 'drew', 'barrymore', 'from', 'the', '1980s'] ...
文件中的行可以按逻辑分组为多个部分，并用分隔符分隔 空行。因此，实际上您有一个两级数据结构，您需要 处理一个分区列表，在每个分区内，您需要处理一个列表 一行行。当然，文本文件是一个简单的行列表，所以我们需要 重新构建两个级别 这是一种非常通用的模式，因此这里有一种方法可以对其进行编码，无论您在每个部分中需要做什么，都可以重用：
labels = []
sentences = []
# Prepare next section
inner_labels = []
inner_sentences = []
with open('engtrain.bio.txt') as f:
for line in f.readlines():
if len(line.strip()) == 0:
# Finish previous section
labels.append(inner_labels)
sentences.append(inner_sentences)
# Prepare next section
inner_labels = []
inner_sentences = []
continue
# Process line in section
l, s = line.strip().split()
inner_labels.append(l)
inner_sentences.append(s)
# Finish previous section
labels.append(inner_labels)
sentences.append(inner_sentences)
可能有一种更具python风格的方式来预处理行列表等，但这是完成工作的可靠模式。文件中的行可以按逻辑分组为多个部分，以 空行。因此，实际上您有一个两级数据结构，您需要 处理一个分区列表，在每个分区内，您需要处理一个列表 一行行。当然，文本文件是一个简单的行列表，所以我们需要 重新构建两个级别 这是一种非常通用的模式，因此这里有一种方法可以对其进行编码，无论您在每个部分中需要做什么，都可以重用：
labels = []
sentences = []
# Prepare next section
inner_labels = []
inner_sentences = []
with open('engtrain.bio.txt') as f:
for line in f.readlines():
if len(line.strip()) == 0:
# Finish previous section
labels.append(inner_labels)
sentences.append(inner_sentences)
# Prepare next section
inner_labels = []
inner_sentences = []
continue
# Process line in section
l, s = line.strip().split()
inner_labels.append(l)
inner_sentences.append(s)
# Finish previous section
labels.append(inner_labels)
sentences.append(inner_sentences)
可能有一种更具python风格的方法来预处理行列表等，但这是一种可靠的模式，可以完成工作。感谢您的回答！但是，在原始数据集上应用此代码会产生以下错误：
索引器：列表索引超出范围words\u 2d=[line.split（），如果line！='\n']索引器：列表索引超出范围。words_2d=[line.split（）（如果line！='\n']）txt另存为，然后选择所有文件类型
选项谢谢！我有一个小问题：你怎么能用as.bio下载文件？我使用复制粘贴到txt
文件，因为直接下载的结构不正确哇！你用12行代码完成了我在25行中所做的工作，我在投票：-）@AliF在浏览器中单击另存为
，然后选择所有文件类型
选项