A dataset that I find myself working with provides an aggregated number of times an occurance happens in a given month - say for example the number of times the 8AM morning commuter busses were late. The data may be formatted like the following:
| Bus # | January | February | March | April | May | June |
| 13N | 5 | 2 | 5 | 3 | 2 | 0 |
| 19W | 2 | 4 | 2 | 4 | 1 | 4 |
| 22E | 2 | 3 | 1 | 2 | 2 | 3 |
| 27W | 6 | 3 | 5 | 8 | 7 | 3 |
| 34S | 1 | 2 | 1 | 3 | 1 | 2 |
I need to convert the number of times per month specified into records where each bus number will have unique dates for the following year (a pseudo-forecast of what may happen next year). Since a bus would only have one 8AM start on a given day, date uniqueness is essential. The output desired is similar to the following:
| Bus # | Date |
| 13N | 2020-01-04 |
| 13N | 2020-01-06 |
| 13N | 2020-01-24 |
| 13N | 2020-01-27 |
| 13N | 2020-01-30 |
| 13N | 2020-02-05 |
| 13N | 2020-02-29 |
| 19W | 2020-01-06 |
| 19W | 2020-01-13 |
Since some busses may be late every day, I need to ensure that every calendar day within a month is available to choose from (not just stopping at 28 to account for non-leap years). 2020 is a leap year, so 2020-02-29 would be in play.
Has anyone done something like this before? If so/not, how would one go about doing this in Alteryx?
Thanks in advance for your suggestion(s).
