Remove unnecessary levels from multiindex columns to fix DifferencingTransform.inverse_transform
#503
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Mr-Geekman
changed the title
DifferencingTransformDifferencingTransform.inverse_transform
Mr-Geekman
changed the title
DifferencingTransform.inverse_transformDifferencingTransform.inverse_transform
Codecov Report
@@ Coverage Diff @@
## master #503 +/- ##
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Coverage 87.80% 87.80%
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Files 115 115
Lines 5454 5455 +1
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+ Hits 4789 4790 +1
Misses 665 665
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martins0n
suggested changes
Feb 7, 2022
martins0n
reviewed
Feb 7, 2022
| @@ -96,6 +96,8 @@ def fit(self, df: pd.DataFrame) -> "_SingleDifferencingTransform": | |||
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| self._train_init_dict[current_segment] = cur_series[: self.period] | |||
| self._test_init_df = fit_df.iloc[-self.period :, :] | |||
| # make multiindex levels consistent | |||
| self._test_init_df.columns = self._test_init_df.columns.remove_unused_levels() | |||
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Can we not use remove_unused_levels?
Is it the root cause?
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It is a solution to the problem. After creation of fit_df values for old columns remains in MultiIndex and it leads to errors during set_names.
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Before submitting (must do checklist)
Type of Change
Proposed Changes
Look #499.
Related Issue
#499.
Closing issues
Closes #499.