Consider a data frame df with columns ['A', 'B', 'C', 'D'] and rows ['r1', 'r2', 'r3']. What does the ex-pression df[lambda x : x.index.str.endswith('3')] do?
This is a tough one, but I think I've got it. The lambda function is checking the row index, so the correct answer must be D. Though I can't help but wonder if the data frame is secretly a sentient being, just waiting to surprise us all.
Easy peasy! The lambda function is looking for rows where the index ends with '3', so the answer has to be D. Though I do wonder if the data frame has a sense of humor and will throw an error just to mess with us.
Haha, the lambda function is like a secret code that only data scientists can crack! I'm going to go with D, because filtering rows seems like the most logical choice here.
Hmm, I'm not so sure about this one. It could be C, since the lambda function might be selecting the third column. But I'm leaning towards D, just to be safe.
This is a tricky one! I think the correct answer is D, since the lambda function checks if the row index ends with '3', which would filter out just the row labeled 'r3'.
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