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Hello, I have this initial table:
TableA:
Row | ValueA | PCT |
1 | 100.000 | 0 |
2 | 100.000 | 8% |
3 | 100.000 | 5% |
4 | 100.000 | 7% |
5 | 100.000 | 6% |
6 | 100.000 | 3% |
7 | 100.000 | 5% |
And I need to perform the following calculation for ValueB from ValueC:
Row | ValueA | PCT | ValueB: WHEN Row=1, ValueA WHEN Row>1, (Pevious(ValueB) - Previous(ValueC)) |
ValueC = ValueB x PCT |
1 | 100.000 | 0 | 100.000 | - |
2 | 100.000 | 8% | 100.000 | 8.000,00 |
3 | 100.000 | 5% | 92.000 | 4.600,00 |
4 | 100.000 | 7% | 87.400 | 6.118,00 |
5 | 100.000 | 6% | 81.282 | 4.876,92 |
6 | 100.000 | 3% | 76.405 | 2.292,15 |
7 | 100.000 | 5% | 74.113 | 3.705,65 |
Any clues?
I couldn't find a formula that worked using Previous() neither Peek().
I have a similar need for a vectorized solution. It would be nice if pandas provided version of apply() where the user's function is able to access one or more values from the previous row as part of its calculation or at least return a value that is then passed 'to itself' on the next iteration. Wouldn't this allow some efficiency gains compared to a for loop?
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