我在哪里出错呢?我正在尝试遍历数据框的每一行并对文本进行编码。
data['text'] = data.apply(lambda row:
codecs(row['text'], "r", 'utf-8'), axis=1)
我收到此错误-为什么uft编码会影响代码的一部分,如果不运行UTF编码,我不会收到错误:
TypeError Traceback (most recent call last)
<ipython-input-101-0e1d5977a3b3> in <module>
----> 1 data['text'] = codecs(data['text'], "r", 'utf-8')
2
3 data['text'] = data.apply(lambda row:
4 codecs(row['text'], "r", 'utf-8'), axis=1)
TypeError: 'module' object is not callable
当我应用解决方案时,两者都可以工作,但是出现此错误:
data['text_tokens'] = data.apply(lambda row:
nltk.word_tokenize(row['text']), axis=1)
错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-138-73972d522748> in <module>
1 data['text_tokens'] = data.apply(lambda row:
----> 2 nltk.word_tokenize(row['text']), axis=1)
~/env/lib64/python3.6/site-packages/pandas/core/frame.py in apply(self, func, axis, broadcast, raw, reduce, result_type, args, **kwds)
6485 args=args,
6486 kwds=kwds)
-> 6487 return op.get_result()
6488
6489 def applymap(self, func):
~/env/lib64/python3.6/site-packages/pandas/core/apply.py in get_result(self)
149 return self.apply_raw()
150
--> 151 return self.apply_standard()
152
153 def apply_empty_result(self):
~/env/lib64/python3.6/site-packages/pandas/core/apply.py in apply_standard(self)
255
256 # compute the result using the series generator
--> 257 self.apply_series_generator()
258
259 # wrap results
~/env/lib64/python3.6/site-packages/pandas/core/apply.py in apply_series_generator(self)
284 try:
285 for i, v in enumerate(series_gen):
--> 286 results[i] = self.f(v)
287 keys.append(v.name)
288 except Exception as e:
<ipython-input-138-73972d522748> in <lambda>(row)
1 data['text_tokens'] = data.apply(lambda row:
----> 2 nltk.word_tokenize(row['text']), axis=1)
~/env/lib64/python3.6/site-packages/nltk/tokenize/__init__.py in word_tokenize(text, language, preserve_line)
142 :type preserve_line: bool
143 """
--> 144 sentences = [text] if preserve_line else sent_tokenize(text, language)
145 return [
146 token for sent in sentences for token in _treebank_word_tokenizer.tokenize(sent)
~/env/lib64/python3.6/site-packages/nltk/tokenize/__init__.py in sent_tokenize(text, language)
104 """
105 tokenizer = load('tokenizers/punkt/{0}.pickle'.format(language))
--> 106 return tokenizer.tokenize(text)
107
108
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in tokenize(self, text, realign_boundaries)
1275 Given a text, returns a list of the sentences in that text.
1276 """
-> 1277 return list(self.sentences_from_text(text, realign_boundaries))
1278
1279 def debug_decisions(self, text):
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in sentences_from_text(self, text, realign_boundaries)
1329 follows the period.
1330 """
-> 1331 return [text[s:e] for s, e in self.span_tokenize(text, realign_boundaries)]
1332
1333 def _slices_from_text(self, text):
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in <listcomp>(.0)
1329 follows the period.
1330 """
-> 1331 return [text[s:e] for s, e in self.span_tokenize(text, realign_boundaries)]
1332
1333 def _slices_from_text(self, text):
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in span_tokenize(self, text, realign_boundaries)
1319 if realign_boundaries:
1320 slices = self._realign_boundaries(text, slices)
-> 1321 for sl in slices:
1322 yield (sl.start, sl.stop)
1323
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in _realign_boundaries(self, text, slices)
1360 """
1361 realign = 0
-> 1362 for sl1, sl2 in _pair_iter(slices):
1363 sl1 = slice(sl1.start + realign, sl1.stop)
1364 if not sl2:
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in _pair_iter(it)
316 it = iter(it)
317 try:
--> 318 prev = next(it)
319 except StopIteration:
320 return
~/env/lib64/python3.6/site-packages/nltk/tokenize/punkt.py in _slices_from_text(self, text)
1333 def _slices_from_text(self, text):
1334 last_break = 0
-> 1335 for match in self._lang_vars.period_context_re().finditer(text):
1336 context = match.group() + match.group('after_tok')
1337 if self.text_contains_sentbreak(context):
TypeError: ('cannot use a string pattern on a bytes-like object', 'occurred at index 0')
答案 0 :(得分:2)
正如第一个错误所述,codecs
是不可调用的。实际上就是模块的名称。
您可能想要:
data['text'] = data.apply(lambda row:
codecs.encode(row['text'], 'utf-8'), axis=1)
word_tokenize
引发的错误是由于该函数在先前编码的字符串上使用的事实所致:codecs.encode
将文本呈现为字节literal字符串。
来自codecs
doc:
大多数标准编解码器是文本编码,将文本编码为字节,但是也提供了将文本编码为文本,字节编码为字节的编解码器。
word_tokenize
不适用于字面量的字节,就像错误说(错误回溯的最后一行)一样。
如果删除编码段落,它将起作用。
关于您对视频的担心:前缀u
表示 unicode 。1
前缀b
表示字节常量。2如果在使用codecs.encode
之后打印数据帧,则为字符串的前缀。
在python 3中(从追溯中可以看到,您的版本是3.6),默认字符串类型为Unicode,因此u
是多余的,通常没有显示,但是字符串已经是unicode了。
因此,我非常确定您是安全的:您可以放心使用codecs.encode
。
答案 1 :(得分:2)
您甚至可以做一些更简单的事情:
df['text'] = df['text'].str.encode('utf-8')
参考:https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.encode.html