Replace missing values with random values from dataset #715
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Codecov ReportAll modified lines are covered by tests ✅
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## main #715 +/- ##
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Coverage 100.00% 100.00%
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Files 17 17
Lines 1791 1799 +8
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+ Hits 1791 1799 +8
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pvk-developer
requested review from
fealho and
R-Palazzo
and removed request for
a team
pvk-developer
commented
Oct 3, 2023
| @@ -1353,8 +1379,9 @@ def test_random_seed(self): | |||
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| # Run | |||
| ht.fit(data) | |||
| transformed = ht.transform(data) | |||
| reversed1 = ht.reverse_transform(transformed) | |||
| ht.reset_randomization() | |||
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I think that this should be solved before going any further, this should be called after fit on the hypertransformer as per #716
fealho
reviewed
Oct 3, 2023
R-Palazzo
reviewed
Oct 3, 2023
| @@ -73,7 +75,7 @@ def _get_missing_value_replacement(self, data): | |||
| if self._missing_value_replacement is None: | |||
| return None | |||
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| if self._missing_value_replacement in {'mean', 'mode'} and pd.isna(data).all(): | |||
| if self._missing_value_replacement in {'mean', 'mode', 'random'} and pd.isna(data).all(): | |||
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Update docstring to include random l73, l21
fealho
approved these changes
Oct 3, 2023
amontanez24
reviewed
Oct 4, 2023
rdt/transformers/null.py
Outdated
Comment on lines
121
to
122
| self._min_value = data.min() | ||
| self._max_value = data.max() |
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Kind of an edge case, but what happens if all the values are nan? I think the min and max would be set to nan as well.
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If all values are nan we do 0
if self._missing_value_replacement in {'mean', 'mode', 'random'} and pd.isna(data).all():
msg = (
f"'missing_value_replacement' cannot be set to '{self._missing_value_replacement}'"
' when the provided data only contains NaNs. Using 0 instead.'
)
LOGGER.info(msg)
return 0
pvk-developer
deleted the
issue-606-replace-missing-values-with-random-values-from-dataset
branch
This was referenced Oct 18, 2023
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Resolves #606