Totally, the display() function is a lifesaver when you're working with large datasets. It's like having a little cheat sheet right there in your notebook. *chuckles* Though I guess if the dataset is really huge, the 'missing' and 'unique' values might not fit on the screen. Guess you'd have to scroll down to see the whole summary.
Good point about the ordinal attribute. That could be useful information, especially if you're doing any sort of analysis or modeling on the data. As for the other options, I think you guys have the right idea. The display() function is really handy for getting a quick overview of your data.
I agree with you on C) and D), but I'm not so sure about B) range. I think that's more of a SQL thing, and this is asking about Spark Dataframes specifically. I'd say E) ordinal might be a better choice, since that could tell us if the columns have an inherent order to them.
Hmm, this question looks pretty straightforward. The display() function in Spark Dataframes typically returns a summary of the data, including things like the data type, missing values, and unique values. I'd say the correct answers are C) missing, D) unique, and possibly B) range as well.
Hmm, I'm leaning towards options A, C, and D. 'type' and 'missing' seem like obvious choices, and 'unique' could be useful for understanding the data distribution.
Yeah, I agree. The options seem to cover a range of different data attributes, so we'll need to think carefully about which ones are actually returned by the display() function.
Whoa, this question is tricky! I'm not too familiar with the display() function in Azure Synapse Analytics, but I think it's going to test our understanding of the different attributes it can return.
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