question: percent_rank vs cume_dist

It seems the Ibis percent_rank operation is in fact the cume_dist SQL operation as explained at [1].

So how could we implement percent_rank SQL operation?

Suggestion 1:

• maybe ibis percent_rank could have one optional argument like cume_dist (default: True)
• and if it is false maybe we can test that using [2], but it means that we should add scipy as a dependence.

any thoughts about this issue?

refs:
[1] https://github.com/ibis-project/ibis/blob/ae71b3a96a514ab599d92382bb55fd247803deac/ibis/tests/all/test_window.py#L43 [2] https://stackoverflow.com/questions/39823470/getting-postgresql-percent-rank-and-scipy-stats-percentileofscore-results-to-mat

extra ref: https://riptutorial.com/sql/example/27456/percent-rank-and-cume-dist

[cpcloud]

We’re now correctly implementing percent_rank everywhere, and we have #3590 for adding cume_dist, closing this out.

[xmnlab]

hi @cpcloud I created this PR long time ago: https://github.com/ibis-project/ibis/pull/2224

so basically the percent_rank tests uses pandas df.rank(pct=True) … but this works as SQL CumeDist.

So, the easiest way would be to rename the operation to CumeDist. and for PercentRank the test should be implemented manually as described in that old PR. also some backend should change the translation to percent_rank to cume_dist.

let me know if you want more information about that.