[MRG] harmonizing the Joiner parameters - #757
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start applying changes decided in skrub-data#751
jeromedockes
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glemaitre
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LGTM. I would expect only a couple of changes in the documentation mainly.
| aux_table : :obj:`~pandas.DataFrame` | ||
| The auxiliary table, which will be fuzzy-joined to the main table when | ||
| calling ``transform``. | ||
| main_key : str or list of str or None |
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| main_key : str or list of str or None | |
| main_key : str, list of str or None |
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Not that in scikit-learn we will have the following convention
main_key: str or list of str, default=NoneAnd somehow, we want to have details regarding None when the meaning is not straightforward: scikit-learn/scikit-learn#17295
We might want to have something similar (I still need to figure out what the class are doign :))
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Here I am not sure what default=None means. As a pandas user, I would expect to match the index of the tables (let see if this is this behaviour ;))
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Apparently, this is not. It is only to know a sentinel to know if we have a matching key (using key) or different keys (so using main_key and aux_key)
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As a Pandas user, this is what I'm expecting ;)
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html
Note that they don't document the None
| for col in self._aux_key: | ||
| if col not in self.aux_table.columns: | ||
| raise ValueError( | ||
| f"Column key {col!r} not found in columns of " | ||
| f"auxiliary table: {self.aux_table.columns.tolist()}. " | ||
| ) |
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This would not make sense to have it in check_key? Or is it really specific to this class?
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Actually the check_key expect aux_key, main_key so I would expect to make such check as well.
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actually I'm not sure this check is super useful, if we don't do it we get a more accurate KeyError when trying to use the key
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So maybe we should think of removing it then.
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It's nice to raise an error early on (during fit instead of during predict), IMHO. I'm +1 on keeping it or putting it into check_key as @glemaitre suggests since both checks will be performed in practice.
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I put it in a different function as check_key is rather for figuring out what key to use from main_key, aux_key and key, and because this check happens in fit and transform whereas check_key is only in fit
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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LGTM. I am undecided regarding removing or not the check.
jeromedockes
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Vincent-Maladiere
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A few additional comments!
| aux_table : :obj:`~pandas.DataFrame` | ||
| The auxiliary table, which will be fuzzy-joined to the main table when | ||
| calling ``transform``. | ||
| main_key : str or list of str or None |
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As a Pandas user, this is what I'm expecting ;)
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html
Note that they don't document the None
| for col in self._aux_key: | ||
| if col not in self.aux_table.columns: | ||
| raise ValueError( | ||
| f"Column key {col!r} not found in columns of " | ||
| f"auxiliary table: {self.aux_table.columns.tolist()}. " | ||
| ) |
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It's nice to raise an error early on (during fit instead of during predict), IMHO. I'm +1 on keeping it or putting it into check_key as @glemaitre suggests since both checks will be performed in practice.
Co-authored-by: Vincent M <maladiere.vincent@yahoo.fr>
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LGTM! Let's move forward with #802
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start applying changes decided in #751