Fix conversion from Categorical to pa.dictionary in read_parquet
#10285
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jrbourbeau
reviewed
May 15, 2023
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Thanks @phofl -- one suggestion, but otherwise this looks good to go
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| expected = pd.DataFrame( | ||
| { | ||
| "a": pd.Series( | ||
| ["x", "y"], dtype=pd.ArrowDtype(pa.dictionary(pa.int32(), pa.string())) | ||
| ), | ||
| "b": pd.Series([1, 2], dtype="int64[pyarrow]"), | ||
| } | ||
| ) |
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Instead of hardcoding this result, testing that dask and pandas return the same result is probably a slightly better approach
expected = pd.read_parquet(outdir, engine="pyarrow", dtype_backend="pyarrow")
jrbourbeau
approved these changes
May 15, 2023
| df.to_parquet(outdir, engine="pyarrow") | ||
| ddf = dd.read_parquet(outdir, engine="pyarrow", dtype_backend="pyarrow") | ||
| pdf = pd.read_parquet(outdir, engine="pyarrow", dtype_backend="pyarrow") | ||
| # Set sort_results=False because of pandas bug |
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Is there an upstream issue for this?
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My pr was already merged, will update tomorrow when nightlies are available
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|
Ah, actually it looks like my suggestion of using TypeError: read_table() got an unexpected keyword argument 'dtype_backend'I still think using |
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pre-commit run --all-filesCame across this when working on the blog post.