fix: handle null-only text column in TextTransformer.transform (#801)#834
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…#801) In Perform mode, _base_predict is called with a single sample to measure prediction time. If that sample has a null text column, filtering out nulls produces an empty array, causing TfidfVectorizer to crash with 'Found array with 0 sample(s)'. Fix: initialize output columns to 0.0 first, then only call the vectorizer when there are non-null rows to transform.
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Fixes #801
In Perform mode, _base_predict is called with a single sample (X.iloc[:1]) to measure prediction time. If that sample's text column is null, filtering out nulls produces an empty array — causing TfidfVectorizer.transform() to crash with "Found array with 0 sample(s)". Explain mode is unaffected because _max_single_prediction_time is None there, so _base_predict is never called.
Fix (supervised/preprocessing/text_transformer.py): initialize output columns to 0.0 first, then only call the vectorizer when there are non-null rows. Null-only inputs get zero-filled columns, which is the correct default.