dosubot[bot] commented on issue #34518:
URL: https://github.com/apache/superset/issues/34518#issuecomment-3146512557

   <!-- Answer -->
   This issue happens because, during time comparison, Superset joins the 
current and shifted dataframes using a left join keyed on the current period. 
If the current period has no data for a date, any rows that exist only in the 
shifted period are dropped at this stage. As a result, the cumulative 
post-processing step only sees the aligned dates, causing the shifted 
cumulative curve to undercount and misalign when the current period is missing 
data for those dates. The cumulative function itself fills NaNs with zero 
before summing, but it doesn't restore missing dates lost in the join. Using 
resample after the fact doesn't help, since the data is already lost by then. 
There are no configuration options or workarounds documented for this scenario, 
and no open or closed issues or PRs directly address this bug in the current 
codebase. The root cause is that the post-processing pipeline does not 
guarantee the union of all dates from both periods is preserved through to the 
cumulative ca
 lculation, so missing dates in the current period will always cause this 
misalignment in time-shifted cumulative charts 
[reference](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/common/query_context_processor.py).
   
   
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