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TST(string dtype): Resolve xfails in pytables #60795

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@rhshadrach rhshadrach commented Jan 26, 2025

  • closes #xxxx (Replace xxxx with the GitHub issue number)
  • Tests added and passed if fixing a bug or adding a new feature
  • All code checks passed.
  • Added type annotations to new arguments/methods/functions.
  • Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature.

Looks like using where that results in empty will still give object dtype. xfailing those tests here and plan to tackle in a followup.

@rhshadrach rhshadrach added Testing pandas testing functions or related to the test suite IO HDF5 read_hdf, HDFStore Strings String extension data type and string data labels Jan 26, 2025
@rhshadrach rhshadrach added this to the 2.3 milestone Jan 26, 2025
pandas/io/pytables.py Outdated Show resolved Hide resolved
@rhshadrach rhshadrach marked this pull request as draft January 26, 2025 13:47
Comment on lines +257 to +260
if using_infer_string:
# TODO: Test is incorrect when not using_infer_string.
# Should take the last 4 rows uncondiationally.
expected = expected[16:]
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Would like to make sure this is correct.

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So the string type is just truncating the last 4 rows? Is it an invalid unicode sequence?

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The DataFrame is all NaN in rows 0-15 inclusive (L250 in this PR), and it is being appended to the store with dropna=True.

@rhshadrach rhshadrach marked this pull request as ready for review February 2, 2025 21:19
Comment on lines +257 to +260
if using_infer_string:
# TODO: Test is incorrect when not using_infer_string.
# Should take the last 4 rows uncondiationally.
expected = expected[16:]
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So the string type is just truncating the last 4 rows? Is it an invalid unicode sequence?

@@ -822,10 +826,11 @@ def test_append_raise(setup_path):
df["foo"] = Timestamp("20130101")
store.append("df", df)
df["foo"] = "bar"
shape = "(30,)" if using_infer_string else "(1, 30)"
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Isn't this still a bug? Not sure why we would expect a different shape with the string data types?

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I assumed it was due to array-backed vs 1d ndarray backed data. But I haven't checked too deeply.

"Cannot serialize the column [datetime1]\nbecause its data "
"contents are not [string] but [date] object dtype"
),
re.escape("[date] is not implemented as a table column"),
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I think the original error message here is much clearer - is there no way to catch and raise that for the string types?

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@rhshadrach rhshadrach Feb 4, 2025

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Not sure what you mean, this error is not raised for string types. It's being raised for date types.

When infer_string=False, this function is passed a single object block with a mix of strings and dates. In this case, the data of the block is inferred as mixed, and then checked column-by-column. This is where the top message (which I think is confusing) is raised. When infer_string=True, each string array is fed into this function individually and does not raise. Then the object block is fed in containing only dates. This is inferred as dates, and the corresponding error message is raised.

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