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BUG: fix the value error when using read_csv with "," as decimal point and pd.Float64Dtype() #52696

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BUG: fix the value error when using read_csv with "," as decimal point and pd.Float64Dtype() #52696

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17349f4
fix_for_pdfloat64_decimal
hxy450 Apr 16, 2023
9276b03
Merge remote-tracking branch 'upstream/main' into dconversion
hxy450 Apr 16, 2023
e06290a
fix_for_pdfloat64_decimal1
hxy450 Apr 16, 2023
681440d
fix_for_pdfloat64_decimal2
hxy450 Apr 17, 2023
3af131b
fix_for_pdfloat64_decimal3
hxy450 Apr 17, 2023
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.1.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -308,6 +308,7 @@ Conversion
^^^^^^^^^^
- Bug in :meth:`ArrowDtype.numpy_dtype` returning nanosecond units for non-nanosecond ``pyarrow.timestamp`` and ``pyarrow.duration`` types (:issue:`51800`)
- Bug in :meth:`DataFrame.info` raising ``ValueError`` when ``use_numba`` is set (:issue:`51922`)
- Bug in :meth:`TextReader._convert_with_dtype` raising ``ValueError`` when ``,`` is used as decimal pointer (:issue:`52086`)
-

Strings
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3 changes: 3 additions & 0 deletions pandas/_libs/parsers.pyx
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Expand Up @@ -1201,6 +1201,9 @@ cdef class TextReader:
result, dtype=dtype, true_values=true_values,
false_values=false_values)
else:
if chr(self.parser.decimal) != ".":
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This costs to much performance, I think that we have to fix this somewhere else

for i in range(len(result)):
result[i] = result[i].replace(chr(self.parser.decimal), ".")
result = array_type._from_sequence_of_strings(result, dtype=dtype)
except NotImplementedError:
raise NotImplementedError(
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33 changes: 33 additions & 0 deletions pandas/tests/libs/test_lib.py
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@@ -1,3 +1,5 @@
import io

import numpy as np
import pytest

Expand All @@ -7,6 +9,7 @@
writers as libwriters,
)

import pandas as pd
from pandas import Index
import pandas._testing as tm

Expand Down Expand Up @@ -270,3 +273,33 @@ def test_no_default_pickle():
# GH#40397
obj = tm.round_trip_pickle(lib.no_default)
assert obj is lib.no_default


def test_pdfloat64_decimal_separator():
df1 = pd.read_csv(
io.StringIO('id\n"1,5"\n"1,6"\n'),
dtype={"id": pd.Float64Dtype()},
sep=";",
decimal=",",
)
df2 = pd.read_csv(
io.StringIO('id\n"1.5"\n"1.6"\n'),
dtype={"id": pd.Float64Dtype()},
sep=",",
decimal=".",
)
assert df1.equals(df2)

df1 = pd.read_csv(
io.StringIO('id\n"1,5"\n'),
dtype={"id": pd.Float64Dtype()},
sep=";",
decimal=",",
)
df2 = pd.read_csv(
io.StringIO('id\n"1.5"\n'),
dtype={"id": pd.Float64Dtype()},
sep=",",
decimal=".",
)
assert df1.equals(df2)