From the course: Data Analysis with Python and Pandas

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Challenge: groupby()

Challenge: groupby()

From the course: Data Analysis with Python and Pandas

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Challenge: groupby()

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- [Presenter] All right, everybody. We have a new email in. This time, it's from Phoebe Product who works in our merchandising department. Subject line is "Top Stores by Transactions." She writes us, "Hi there, it's Phoebe. "I want to create some custom displays "for our busiest stores. "Can you return a table containing the top 10 stores "by total transactions in the data? "Make sure they're sorted from highest to lowest. "Thanks." She also says, "P.S. Let me know "if you want to hear my music." I don't know if I want to, but feel free to reply how you want. If we take a look at our results preview, we can see we have an aggregated table with our store number in our index, with Store 44 at the top, having about 7.2 million transactions. And our 10th highest selling store was Store 11 with about 3.97 million transactions. We're going to be working out of our Section Four notebook. We made it through data frames. Let's take a quick look at that. All right, so as usual you want to���

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