From the course: Data Analysis with Python and Pandas

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Solution: pivot() and melt()

Solution: pivot() and melt()

From the course: Data Analysis with Python and Pandas

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Solution: pivot() and melt()

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- [Instructor] All right everybody, our solution code is up on the right. Let's go ahead and dive into the notebook. Alright, so we have our transactions table here. We want to build a pivot table. So we know we want to call pivot table on this transactions table, but one thing that we want to do is filter to stores that had a non-zero bonus payable, and then create a heat map. So this could have been a challenging operation if you try to filter after creating your pivot table. But one thing that we can do to get around this is just filter all rows in our base table that have a bonus not equal to zero, or we could even say equal to 100. And that will have the effect of not only filtering out any rows that don't have a bonus, right? These are going to be summed to zero. It won't affect our statistics, it will also filter out stores. So let's go ahead and do transactions.lock. And then you want to specify transactions. Bonus_payable is not equal to zero. So in the case that we had other…

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