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BUG: during interchanging from non-pandas tz-aware data #54287

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Merged
merged 9 commits into from
Jul 31, 2023
Merged

BUG: during interchanging from non-pandas tz-aware data #54287

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c89377c
TST: add a test for interchanging from non-pandas tz-aware
natmokval Jul 28, 2023
ddcf978
TST: correct the test for interchanging from non-pandas tz-aware
natmokval Jul 28, 2023
42aeee0
check an error in the test
natmokval Jul 28, 2023
9448242
correct test
natmokval Jul 31, 2023
da6fe09
add extra except in set_nulls
natmokval Jul 31, 2023
15a1fa6
fix bug during interchanging from non-pandas tz-aware
natmokval Jul 31, 2023
dd2c3eb
correct test
natmokval Jul 31, 2023
c575157
correct wording
natmokval Jul 31, 2023
0d5774e
resolve conflict
natmokval Jul 31, 2023
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16 changes: 16 additions & 0 deletions pandas/tests/interchange/test_impl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
import pytest

from pandas._libs.tslibs import iNaT
from pandas.errors import SettingWithCopyError
import pandas.util._test_decorators as td

import pandas as pd
Expand Down Expand Up @@ -295,3 +296,18 @@ def test_datetimetzdtype(tz, unit):
)
df = pd.DataFrame({"ts_tz": tz_data})
tm.assert_frame_equal(df, from_dataframe(df.__dataframe__()))


def test_interchange_from_non_pandas_tz_aware_raise_error():
# GH 54239
pa = pytest.importorskip("pyarrow")
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we may need to set a minimum version here

Suggested change
pa = pytest.importorskip("pyarrow")
pa = pytest.importorskip("pyarrow", "11.0.0")

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thank you, I added the minimum version here

import pyarrow.compute as pc

arr = pa.array([datetime(2020, 1, 1), None, datetime(2020, 1, 2)])
arr = pc.assume_timezone(arr, "Asia/Kathmandu")
table = pa.table({"arr": arr})
exchange_df = table.__dataframe__()

msg = "modifications to a method of a datetimelike object are not supported."
with pytest.raises(SettingWithCopyError, match=msg):
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I don't think this should be raising an error though

In

        try:
            data[null_pos] = None
        except TypeError:
            # TypeError happens if the `data` dtype appears to be non-nullable
            # in numpy notation (bool, int, uint). If this happens,
            # cast the `data` to nullable float dtype.
            data = data.astype(float)
            data[null_pos] = None

, could we add an extra except, which catches SettingWithCopyError, and in that case makes a copy of data (data = data.copy()) and then sets the nulls (data[null_pos] = None)?

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Thank you, I added the extra except, it works very well. I updated my test and added a line to whatsnew/v2.1.0.rst as well.

from_dataframe(exchange_df)