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Merged
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Aug 24, 2023
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Incorrect reading of CSV containing large integers Issue#52505 #54679

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mend
kvn4 Aug 21, 2023
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kvn4 Aug 23, 2023
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kvn4 Aug 23, 2023
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kvn4 Aug 24, 2023
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v2.2.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -139,7 +139,7 @@ Timezones

Numeric
^^^^^^^
-
- Bug in :func:`_read`, pyarrow engine not defaulting to float64 causing precision errors when specifying a dtype; fixed by explicitly setting dtype if dtype not none and isinstance of dict (:issue:`52505`)
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Can you phrase this in terms of a public API?

-

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7 changes: 6 additions & 1 deletion pandas/io/parsers/arrow_parser_wrapper.py
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Expand Up @@ -223,5 +223,10 @@ def read(self) -> DataFrame:
elif using_pyarrow_string_dtype():
frame = table.to_pandas(types_mapper=arrow_string_types_mapper())
else:
frame = table.to_pandas()
if self.kwds.get("dtype") is not None and isinstance(
type(self.kwds.get("dtype")), dict
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Suggested change
if self.kwds.get("dtype") is not None and isinstance(
type(self.kwds.get("dtype")), dict
if isinstance(self.kwds.get("dtype"), dict):

):
frame = table.to_pandas(types_mapper=self.kwds["dtype"].get)
else:
frame = table.to_pandas()
return self._finalize_pandas_output(frame)
21 changes: 21 additions & 0 deletions pandas/tests/io/parser/dtypes/test_dtypes_basic.py
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Expand Up @@ -558,3 +558,24 @@ def test_string_inference(all_parsers):
columns=pd.Index(["a", "b"], dtype=dtype),
)
tm.assert_frame_equal(result, expected)


def test_accurate_parsing_of_large_integers(all_parsers):
# GH#52505
data = """SYMBOL,SYSTEM,TYPE,MOMENT,ID,ACTION,PRICE,VOLUME,ID_DEAL,PRICE_DEAL
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Can you reduce the unnecessary data for testing?

AAPL,F,S,20230301181139587,1925036343869802844,0,96690.00000,2,,75.00000
MSFT,F,S,20230301181139587,2023552585717888193,0,75.10000,14,,
TSLA,F,S,20230301181139587,2023552585717889863,1,75.00000,14,,
AAPL,F,S,20230301181139587,2023552585717889863,2,75.00000,1,2023552585717263358,75.00000
TSLA,F,B,20230301181139587,2023552585717882895,2,75.00000,1,2023552585717263358,75.00000
NVDA,F,S,20230301181139587,2023552585717889863,2,75.00000,1,2023552585717263359,75.00000
MRNA,F,B,20230301181139587,2023552585717888161,2,75.00000,1,2023552585717263359,75.00000
AMC,F,S,20230301181139587,2023552585717889863,2,75.00000,10,2023552585717263360,75.00000
AMZN,F,B,20230301181139587,2023552585717889759,2,75.00000,10,2023552585717263360,75.00000
MSFT,F,S,20230301181139587,2023552585717889863,2,75.00000,2,2023552585717263361,75.00000
NVDA,F,B,20230301181139587,2023552585717889827,2,75.00000,2,2023552585717263361,75.00000"""
orders = pd.read_csv(StringIO(data), dtype={"ID_DEAL": pd.Int64Dtype()})
print(len(orders.query("ID_DEAL==2023552585717263360", engine="python")))
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Suggested change
print(len(orders.query("ID_DEAL==2023552585717263360", engine="python")))

tm.assert_equal(
len(orders.query("ID_DEAL==2023552585717263360", engine="python")), 2
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Can you not use query here?

Also a plain assert should be fine

)