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Currently if X and y have common columns the error ValueError: Xandy must not share column names is thrown.
ValueError:
and
must not share column names
Would it be possible possible to check for common columns in X and y after the recipe has been applied?
Given that Drop and Select would be there, It would make more sense to enforce no column columns after the pipeline has processed, not before.
Drop
Select
import pandas as pd import ibis import ibis_ml as ml con = ibis.duckdb.connect() df = pd.DataFrame({ 'cat1': ['AA', 'BBB', 'AA', 'BBB', 'CCC'], 'cat2': ['X', 'Y', 'Y', 'X', 'Z'], 'value': [10, 20, 30, 40, 50] }) tbl = con.create_table("tmp", df, overwrite=True) tr_oe = ml.Recipe( ml.OrdinalEncode(ml.string(), min_frequency=2), ml.Drop("value") ).fit(tbl, tbl.value) # ValueError: `X` and `y` must not share column names
The text was updated successfully, but these errors were encountered:
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Currently if X and y have common columns the error
ValueError:
Xand
ymust not share column names
is thrown.Would it be possible possible to check for common columns in X and y after the recipe has been applied?
Given that
Drop
andSelect
would be there, It would make more sense to enforce no column columns after the pipeline has processed, not before.The text was updated successfully, but these errors were encountered: