diff --git a/doc/source/whatsnew/v1.1.1.rst b/doc/source/whatsnew/v1.1.1.rst index 443589308ad4c..f8f655ce7b866 100644 --- a/doc/source/whatsnew/v1.1.1.rst +++ b/doc/source/whatsnew/v1.1.1.rst @@ -15,7 +15,7 @@ including other versions of pandas. Fixed regressions ~~~~~~~~~~~~~~~~~ -- +- Fixed regression where :func:`read_csv` would raise a ``ValueError`` when ``pandas.options.mode.use_inf_as_na`` was set to ``True`` (:issue:`35493`). - - diff --git a/pandas/_libs/missing.pyx b/pandas/_libs/missing.pyx index 760fab3781fd4..771e8053ac9be 100644 --- a/pandas/_libs/missing.pyx +++ b/pandas/_libs/missing.pyx @@ -155,7 +155,10 @@ def isnaobj_old(arr: ndarray) -> ndarray: result = np.zeros(n, dtype=np.uint8) for i in range(n): val = arr[i] - result[i] = checknull(val) or val == INF or val == NEGINF + result[i] = ( + checknull(val) + or util.is_float_object(val) and (val == INF or val == NEGINF) + ) return result.view(np.bool_) diff --git a/pandas/tests/io/parser/test_common.py b/pandas/tests/io/parser/test_common.py index 12e73bae40eac..5154a9ba6fdf0 100644 --- a/pandas/tests/io/parser/test_common.py +++ b/pandas/tests/io/parser/test_common.py @@ -18,7 +18,7 @@ from pandas.errors import DtypeWarning, EmptyDataError, ParserError import pandas.util._test_decorators as td -from pandas import DataFrame, Index, MultiIndex, Series, compat, concat +from pandas import DataFrame, Index, MultiIndex, Series, compat, concat, option_context import pandas._testing as tm from pandas.io.parsers import CParserWrapper, TextFileReader, TextParser @@ -2179,3 +2179,13 @@ def test_read_csv_names_not_accepting_sets(all_parsers): parser = all_parsers with pytest.raises(ValueError, match="Names should be an ordered collection."): parser.read_csv(StringIO(data), names=set("QAZ")) + + +def test_read_csv_with_use_inf_as_na(all_parsers): + # https://github.com/pandas-dev/pandas/issues/35493 + parser = all_parsers + data = "1.0\nNaN\n3.0" + with option_context("use_inf_as_na", True): + result = parser.read_csv(StringIO(data), header=None) + expected = DataFrame([1.0, np.nan, 3.0]) + tm.assert_frame_equal(result, expected)