问题
I am working in jupyter notebook and have a pandas dataframe "data":
Question_ID | Customer_ID | Answer
1 234 Data is very important to use because ...
2 234 We value data since we need it ...
I want to go through the text in column "Answer" and get the three words before and after the word "data". So in this scenario I would have gotten "is very important"; "We value", "since we need".
Is there an good way to do this within a pandas dataframe? So far I only found solutions where "Answer" would be its own file run through python code (without a pandas dataframe). While I realize that I need to use the NLTK library, I haven't used it before, so I don't know what the best approach would be. (This was a great example Extracting a word and its prior 10 word context to a dataframe in Python)
回答1:
This may work:
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
output:
['is very important']
['We value', 'since we need']
回答2:
The solution using generator expression, re.findall
and itertools.chain.from_iterable
functions:
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)))
The output:
[' is very important', 'We value ', ' since we need']
来源:https://stackoverflow.com/questions/41127321/python-pandas-dataframe-words-in-context-get-3-words-before-and-after