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"""
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)