我在jupyter笔记本上工作并拥有一个pandas数据框"数据":
Question_ID | Customer_ID | Answer
1 234 Data is very important to use because ...
2 234 We value data since we need it ...
我想仔细阅读#34;答案"并获得单词" data"之前和之后的三个单词。 所以在这种情况下,我会得到"非常重要&#34 ;; "我们重视","因为我们需要"。
在pandas数据框中有没有好的方法呢?到目前为止,我只找到了解决方案,其中"答案"将是自己的文件运行python代码(没有pandas数据帧)。虽然我意识到我需要使用NLTK库,但之前我还没有使用它,所以我不知道最好的方法是什么。 (这是一个很好的例子Extracting a word and its prior 10 word context to a dataframe in Python)
答案 0 :(得分:1)
这可能有效:
<meta>
输出:
import pandas as pd
import re
df = pd.read_csv('data.csv')
for value in df.Answer.values:
non_data = re.split('Data|data', value) # split text removing "data"
terms_list = [term for term in non_data if len(term) > 0] # skip empty terms
substrs = [term.split()[0:3] for term in terms_list] # slice and grab first three terms
result = [' '.join(term) for term in substrs] # combine the terms back into substrings
print result
答案 1 :(得分:0)
使用生成器表达式,re.findall
和itertools.chain.from_iterable
函数的解决方案:
import pandas as pd, re, itertools
data = pd.read_csv('test.csv') # change with your current file path
data_adjacents = ((i for sublist in (list(filter(None,t))
for t in re.findall(r'(\w*?\s*\w*?\s*\w*?\s+)(?=\bdata\b)|(?<=\bdata\b)(\s+\w*\s*\w*\s*\w*)', l, re.I)) for i in sublist)
for l in data.Answer.tolist())
print(list(itertools.chain.from_iterable(data_adjacents)))
输出:
[' is very important', 'We value ', ' since we need']