""" Tests that work on both the Python and C engines but do not have a specific classification into the other test modules. """ from io import StringIO import numpy as np import pytest from pandas import ( DataFrame, option_context, ) import pandas._testing as tm xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail") @xfail_pyarrow @pytest.mark.parametrize("na_filter", [True, False]) def test_inf_parsing(all_parsers, na_filter): parser = all_parsers data = """\ ,A a,inf b,-inf c,+Inf d,-Inf e,INF f,-INF g,+INf h,-INf i,inF j,-inF""" expected = DataFrame( {"A": [float("inf"), float("-inf")] * 5}, index=["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"], ) result = parser.read_csv(StringIO(data), index_col=0, na_filter=na_filter) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize("na_filter", [True, False]) def test_infinity_parsing(all_parsers, na_filter): parser = all_parsers data = """\ ,A a,Infinity b,-Infinity c,+Infinity """ expected = DataFrame( {"A": [float("infinity"), float("-infinity"), float("+infinity")]}, index=["a", "b", "c"], ) result = parser.read_csv(StringIO(data), index_col=0, na_filter=na_filter) tm.assert_frame_equal(result, expected) 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" msg = "use_inf_as_na option is deprecated" with tm.assert_produces_warning(FutureWarning, match=msg): 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)