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Categorical and fillna issues with pandas >=1.2 #190

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Oct 13, 2021
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Categorical and fillna issues with pandas >=1.2 #190

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758baa1
FIX: fillna only target
martins0n Oct 13, 2021
75877d7
FIX: changelog
martins0n Oct 13, 2021
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -47,6 +47,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

### Fixed
- Set default value of `TSDataset.head` method ([#170](https://github.com/tinkoff-ai/etna-ts/pull/170))
- Categorical and fillna issues with pandas >=1.2 ([#190](https://github.com/tinkoff-ai/etna-ts/pull/190))

## [1.1.3] - 2021-10-08
### Fixed
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2 changes: 1 addition & 1 deletion etna/transforms/pytorch_forecasting.py
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Expand Up @@ -172,7 +172,7 @@ def transform(self, df: pd.DataFrame) -> pd.DataFrame:
ts = TSDataset(df, self.freq)
df_flat = ts.to_pandas(flatten=True)
df_flat = df_flat[df_flat.timestamp >= self.min_timestamp]
df_flat = df_flat.fillna(0)
df_flat["target"] = df_flat["target"].fillna(0)
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Can you describe why is it necessary change?

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We can't fill columns with categorical types with pandas >=1.2 + fillna all -- is too strong assumption, because we mostly have nan's only in the future targets


freq_unit = self._calculate_freq_unit(self.freq)
df_flat["time_idx"] = (df_flat["timestamp"] - self.min_timestamp) / freq_unit
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