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Lazy approach

You have done some cleaning in your dataset but you are worried that there are sentences encased in parentheses that may cloud your analysis.

Again, a greedy or a lazy quantifier may lead to different results.

For example, if you want to extract a word starting with a and ending with e in the string I like apple pie, you may think that applying the greedy regex a.+e will return apple. However, your match will be apple pie. A way to overcome this is to make it lazy by using ? which will return apple.

The re module and the variable sentiment_analysis are already loaded in your session.

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Regular Expressions in Python

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# Write a greedy regex expression to match 
sentences_found_greedy = re.____(r"____", ____)

# Print out the result
print(sentences_found_greedy)
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