Make Timegapsplit dataframe-agnostic #668
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MarcoGorelli
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MarcoGorelli
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May 12, 2024
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| X_train_df = X_index_df[ | ||
| (X_index_df["__date__"] >= start_date) & (X_index_df["__date__"] < current_date + self.train_duration) | ||
| ] | ||
| X_valid_df = X_index_df[ | ||
| (X_index_df["__date__"] >= current_date + self.train_duration + self.gap_duration) | ||
| & ( | ||
| X_index_df["__date__"] | ||
| < current_date + self.train_duration + self.valid_duration + self.gap_duration | ||
| ) | ||
| ] | ||
| X_train_df = X_index_df.filter( | ||
| nw.col("__date__") >= start_date, nw.col("__date__") < current_date + self.train_duration | ||
| ) | ||
| X_valid_df = X_index_df.filter( | ||
| nw.col("__date__") >= current_date + self.train_duration + self.gap_duration, | ||
| nw.col("__date__") < current_date + self.train_duration + self.valid_duration + self.gap_duration, | ||
| ) |
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I find this diff so pleasing 😍
MarcoGorelli
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May 12, 2024
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| if not date_serie.index.is_unique: | ||
| raise ValueError("date_serie doesn't have a unique index") |
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this is checked as part of nw.maybe_align_index
FBruzzesi
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May 12, 2024
FBruzzesi
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May 12, 2024
sklego/model_selection.py
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| - Modin | ||
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Is CuDF breaking for some reason? It seems we are not doing any checking on X (check_array I am looking at you)
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again, thanks for asking - indeed, cuDF should be in the list, as to_numpy() is called explicitly here, and they do support that https://docs.rapids.ai/api/cudf/nightly/user_guide/api_docs/api/cudf.dataframe.to_numpy/
it's __array__ (which gets triggered when you call np.asarray on an object) which they don't support they don't support #665 (comment) . So, indeed, they should be included here
koaning
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May 24, 2024
* placeholder to develop narwhals features * feat: make `ColumnDropper` dataframe-agnostic (#655) * feat: make ColumnDropped dataframe-agnostic * use narwhals[polars] in pyproject.toml, link to list of supported libraries * note that narwhals is used for cross-dataframe support * test refactor * docstrings --------- Co-authored-by: FBruzzesi <[email protected]> * feat: make ColumnSelector dataframe-agnostic (#659) * columnselector with test rufformatted * adding whitespace * fixed the fit and transform * removed intendation in examples * font:false * feat: make `add_lags` dataframe-agnostic (#661) * make add_lags dataframe-agnostic * try getting tests to run? * patch: cvxpy 1.5.0 support (#663) --------- Co-authored-by: Francesco Bruzzesi <[email protected]> * Make `RegressionOutlier` dataframe-agnostic (#665) * make regression outlier df-agnostic * need to use eager-only for this one * pass native to check_array * remove cudf, link to check_X_y * feat: Make InformationFilter dataframe-agnostic * Make Timegapsplit dataframe-agnostic (#668) * make timegapsplit dataframe-agnostic * actually, include cuDF * feat: make FairClassifier data-agnostic (#669) * start all over * fixture working * wip * passing tests - again * pre-commit complaining * changed fixture on test_demographic_parity * feat: Make PandasTypeSelector selector dataframe-agnostic (#670) * make pandas dtype selector df-agnostic * bump version * 3.8 compat * Update sklego/preprocessing/pandastransformers.py Co-authored-by: Francesco Bruzzesi <[email protected]> * fixup pyproject.toml * unify (and test!) error message * deprecate * update readme * undo contribution.md change --------- Co-authored-by: Francesco Bruzzesi <[email protected]> * format typeselector and bump version * feat: Make grouped and hierarchical dataframe-agnostic (#667) * feat: make grouped and hierarchical dataframe-agnostic * add pyarrow * narwhals grouped_transformer * grouped transformer eureka * hierarchical narwhalified * so close but so far * return series instead of DataFrame for y * grouped WIP * merge branch and fix grouped * future annotations * format * handling negative indices * solve conflicts * hacking C * fairness: change C values in tests --------- Co-authored-by: Marco Edward Gorelli <[email protected]> Co-authored-by: Magdalena Anopsy <[email protected]> Co-authored-by: Dea María Léon <[email protected]>
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Description
This was quite a fun one! As a precursor, I added
nw.maybe_align_indexandnw.maybe_set_index, so that the automated index alignment can be preserved for pandas users, but Polars can still be supported (so long asdate_serieandX/yare the same length), as discussed hereAnother step towards #658
Type of change
Checklist: