Comments (3)
jmoralez
commented on July 29, 2024
1
Hey @iamyihwa, if your series have missing points I suggest you run the fill_gaps function first with start='global', end='global', fill the missing values with zero (which is what the previous version did) and then aggregate.
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iamyihwa
commented on July 29, 2024
When using previous version (0.3.0) , for the same dataframe, I get all time series balanced.
However taking much longer to perform aggregate() then the most recent version.
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iamyihwa
commented on July 29, 2024
Yes ! @jmoralez ! It works fine with this method! Thanks for pointing me to it! It would perhaps be helpful to have this also in the documentation of the hierarchicalforecast and other libraries.
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Related Issues (20)
- [utils] aggregate doesn't work correctly with most recent version of the code HOT 1
- `MinTrace` fails for zero-inflated Time Series with `res_methods` in `['wls_var', 'mint_cov', 'mint_shrink']` HOT 2
- Update evaluation example in `README`
- hierarchicalforecast.core - 'list' object has no attribute 'insample' - HOT 2
- Sparse Methods Missing from 0.3.0 HOT 3
- StatsForecast models producing NotImplementedError: tiny datasets in 0.4.0 HOT 5
- MinTraceSparse(nonnegative=True) HOT 1
- [Core][Enhancement]: Add dummies to Aggregate
- Add temporal hierarchies HOT 2
- [Core] KaTex parse error: Can't use function '$' in math mode
- Wrong argument name in evaluation section of README
- [utils] HierarchicalPlot is not plotting HOT 1
- TopDown method (proportion_averages, average_proportions) broken in 0.3.0, 0.4.0 and 0.4.1 HOT 6
- TopDown returns NaN HOT 10
- dependency on `quadprog` HOT 6
- [Core] Possible issue with core.py HOT 4
- [Methods] Undesired conversion to a dense matrix HOT 3
- KeyError when trying to get prediction intervals with MiddleOut HOT 1
- Package does not work with 3.12 HOT 1
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