From the course: Data Analysis with Python and Pandas

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Challenge: Series aggregation

Challenge: Series aggregation

From the course: Data Analysis with Python and Pandas

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Challenge: Series aggregation

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- [Instructor] All right, everybody. We have a new message in from Rachel. Subject line is additional metrics. She writes us, hi again. I need a few more metrics. Can you calculate the sum and mean of prices in the month of March? Next, how many prices did we have in January and February? Then calculate the 10th and 90th percentiles across all data. Finally, how often did the integer values, for example, 51 and 52, let's get rid of the float portion, occur in the data? Normalize the results to a percentage, thanks. We can see our results preview on the right. Let's go ahead and take a quick look at our notebook. All right, so this assignment should be pretty straightforward. We're just going to need to apply the aggregation methods that we've seen in the last couple of lessons. We might need to do some filtering to get down to specific time periods, but otherwise we'll just be applying the aggregation methods we just learned. So go ahead and take a shot at that, and we'll see you in a…

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