""" Tests that work on both the Python and C engines but do not have a specific classification into the other test modules. """ from datetime import datetime from inspect import signature from io import StringIO import os from pathlib import Path import sys import numpy as np import pytest from pandas.errors import ( EmptyDataError, ParserError, ParserWarning, ) from pandas import ( DataFrame, Index, Timestamp, compat, ) import pandas._testing as tm from pandas.io.parsers import TextFileReader from pandas.io.parsers.c_parser_wrapper import CParserWrapper xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail") skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip") def test_override_set_noconvert_columns(): # see gh-17351 # # Usecols needs to be sorted in _set_noconvert_columns based # on the test_usecols_with_parse_dates test from test_usecols.py class MyTextFileReader(TextFileReader): def __init__(self) -> None: self._currow = 0 self.squeeze = False class MyCParserWrapper(CParserWrapper): def _set_noconvert_columns(self): if self.usecols_dtype == "integer": # self.usecols is a set, which is documented as unordered # but in practice, a CPython set of integers is sorted. # In other implementations this assumption does not hold. # The following code simulates a different order, which # before GH 17351 would cause the wrong columns to be # converted via the parse_dates parameter self.usecols = list(self.usecols) self.usecols.reverse() return CParserWrapper._set_noconvert_columns(self) data = """a,b,c,d,e 0,1,2014-01-01,09:00,4 0,1,2014-01-02,10:00,4""" parse_dates = [[1, 2]] cols = { "a": [0, 0], "c_d": [Timestamp("2014-01-01 09:00:00"), Timestamp("2014-01-02 10:00:00")], } expected = DataFrame(cols, columns=["c_d", "a"]) parser = MyTextFileReader() parser.options = { "usecols": [0, 2, 3], "parse_dates": parse_dates, "delimiter": ",", } parser.engine = "c" parser._engine = MyCParserWrapper(StringIO(data), **parser.options) result = parser.read() tm.assert_frame_equal(result, expected) def test_read_csv_local(all_parsers, csv1): prefix = "file:///" if compat.is_platform_windows() else "file://" parser = all_parsers fname = prefix + str(os.path.abspath(csv1)) result = parser.read_csv(fname, index_col=0, parse_dates=True) expected = DataFrame( [ [0.980269, 3.685731, -0.364216805298, -1.159738], [1.047916, -0.041232, -0.16181208307, 0.212549], [0.498581, 0.731168, -0.537677223318, 1.346270], [1.120202, 1.567621, 0.00364077397681, 0.675253], [-0.487094, 0.571455, -1.6116394093, 0.103469], [0.836649, 0.246462, 0.588542635376, 1.062782], [-0.157161, 1.340307, 1.1957779562, -1.097007], ], columns=["A", "B", "C", "D"], index=Index( [ datetime(2000, 1, 3), datetime(2000, 1, 4), datetime(2000, 1, 5), datetime(2000, 1, 6), datetime(2000, 1, 7), datetime(2000, 1, 10), datetime(2000, 1, 11), ], name="index", ), ) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_1000_sep(all_parsers): parser = all_parsers data = """A|B|C 1|2,334|5 10|13|10. """ expected = DataFrame({"A": [1, 10], "B": [2334, 13], "C": [5, 10.0]}) result = parser.read_csv(StringIO(data), sep="|", thousands=",") tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_unnamed_columns(all_parsers): data = """A,B,C,, 1,2,3,4,5 6,7,8,9,10 11,12,13,14,15 """ parser = all_parsers expected = DataFrame( [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15]], dtype=np.int64, columns=["A", "B", "C", "Unnamed: 3", "Unnamed: 4"], ) result = parser.read_csv(StringIO(data)) tm.assert_frame_equal(result, expected) def test_csv_mixed_type(all_parsers): data = """A,B,C a,1,2 b,3,4 c,4,5 """ parser = all_parsers expected = DataFrame({"A": ["a", "b", "c"], "B": [1, 3, 4], "C": [2, 4, 5]}) result = parser.read_csv(StringIO(data)) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_read_csv_low_memory_no_rows_with_index(all_parsers): # see gh-21141 parser = all_parsers if not parser.low_memory: pytest.skip("This is a low-memory specific test") data = """A,B,C 1,1,1,2 2,2,3,4 3,3,4,5 """ result = parser.read_csv(StringIO(data), low_memory=True, index_col=0, nrows=0) expected = DataFrame(columns=["A", "B", "C"]) tm.assert_frame_equal(result, expected) def test_read_csv_dataframe(all_parsers, csv1): parser = all_parsers result = parser.read_csv(csv1, index_col=0, parse_dates=True) expected = DataFrame( [ [0.980269, 3.685731, -0.364216805298, -1.159738], [1.047916, -0.041232, -0.16181208307, 0.212549], [0.498581, 0.731168, -0.537677223318, 1.346270], [1.120202, 1.567621, 0.00364077397681, 0.675253], [-0.487094, 0.571455, -1.6116394093, 0.103469], [0.836649, 0.246462, 0.588542635376, 1.062782], [-0.157161, 1.340307, 1.1957779562, -1.097007], ], columns=["A", "B", "C", "D"], index=Index( [ datetime(2000, 1, 3), datetime(2000, 1, 4), datetime(2000, 1, 5), datetime(2000, 1, 6), datetime(2000, 1, 7), datetime(2000, 1, 10), datetime(2000, 1, 11), ], name="index", ), ) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize("nrows", [3, 3.0]) def test_read_nrows(all_parsers, nrows): # see gh-10476 data = """index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 qux,12,13,14,15 foo2,12,13,14,15 bar2,12,13,14,15 """ expected = DataFrame( [["foo", 2, 3, 4, 5], ["bar", 7, 8, 9, 10], ["baz", 12, 13, 14, 15]], columns=["index", "A", "B", "C", "D"], ) parser = all_parsers result = parser.read_csv(StringIO(data), nrows=nrows) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize("nrows", [1.2, "foo", -1]) def test_read_nrows_bad(all_parsers, nrows): data = """index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 qux,12,13,14,15 foo2,12,13,14,15 bar2,12,13,14,15 """ msg = r"'nrows' must be an integer >=0" parser = all_parsers with pytest.raises(ValueError, match=msg): parser.read_csv(StringIO(data), nrows=nrows) def test_nrows_skipfooter_errors(all_parsers): msg = "'skipfooter' not supported with 'nrows'" data = "a\n1\n2\n3\n4\n5\n6" parser = all_parsers with pytest.raises(ValueError, match=msg): parser.read_csv(StringIO(data), skipfooter=1, nrows=5) @xfail_pyarrow def test_missing_trailing_delimiters(all_parsers): parser = all_parsers data = """A,B,C,D 1,2,3,4 1,3,3, 1,4,5""" result = parser.read_csv(StringIO(data)) expected = DataFrame( [[1, 2, 3, 4], [1, 3, 3, np.nan], [1, 4, 5, np.nan]], columns=["A", "B", "C", "D"], ) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_skip_initial_space(all_parsers): data = ( '"09-Apr-2012", "01:10:18.300", 2456026.548822908, 12849, ' "1.00361, 1.12551, 330.65659, 0355626618.16711, 73.48821, " "314.11625, 1917.09447, 179.71425, 80.000, 240.000, -350, " "70.06056, 344.98370, 1, 1, -0.689265, -0.692787, " "0.212036, 14.7674, 41.605, -9999.0, -9999.0, " "-9999.0, -9999.0, -9999.0, -9999.0, 000, 012, 128" ) parser = all_parsers result = parser.read_csv( StringIO(data), names=list(range(33)), header=None, na_values=["-9999.0"], skipinitialspace=True, ) expected = DataFrame( [ [ "09-Apr-2012", "01:10:18.300", 2456026.548822908, 12849, 1.00361, 1.12551, 330.65659, 355626618.16711, 73.48821, 314.11625, 1917.09447, 179.71425, 80.0, 240.0, -350, 70.06056, 344.9837, 1, 1, -0.689265, -0.692787, 0.212036, 14.7674, 41.605, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, 0, 12, 128, ] ] ) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_trailing_delimiters(all_parsers): # see gh-2442 data = """A,B,C 1,2,3, 4,5,6, 7,8,9,""" parser = all_parsers result = parser.read_csv(StringIO(data), index_col=False) expected = DataFrame({"A": [1, 4, 7], "B": [2, 5, 8], "C": [3, 6, 9]}) tm.assert_frame_equal(result, expected) def test_escapechar(all_parsers): # https://stackoverflow.com/questions/13824840/feature-request-for- # pandas-read-csv data = '''SEARCH_TERM,ACTUAL_URL "bra tv board","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord" "tv p\xc3\xa5 hjul","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord" "SLAGBORD, \\"Bergslagen\\", IKEA:s 1700-tals series","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"''' # noqa: E501 parser = all_parsers result = parser.read_csv( StringIO(data), escapechar="\\", quotechar='"', encoding="utf-8" ) assert result["SEARCH_TERM"][2] == 'SLAGBORD, "Bergslagen", IKEA:s 1700-tals series' tm.assert_index_equal(result.columns, Index(["SEARCH_TERM", "ACTUAL_URL"])) @xfail_pyarrow def test_ignore_leading_whitespace(all_parsers): # see gh-3374, gh-6607 parser = all_parsers data = " a b c\n 1 2 3\n 4 5 6\n 7 8 9" result = parser.read_csv(StringIO(data), sep=r"\s+") expected = DataFrame({"a": [1, 4, 7], "b": [2, 5, 8], "c": [3, 6, 9]}) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize("usecols", [None, [0, 1], ["a", "b"]]) def test_uneven_lines_with_usecols(all_parsers, usecols): # see gh-12203 parser = all_parsers data = r"""a,b,c 0,1,2 3,4,5,6,7 8,9,10""" if usecols is None: # Make sure that an error is still raised # when the "usecols" parameter is not provided. msg = r"Expected \d+ fields in line \d+, saw \d+" with pytest.raises(ParserError, match=msg): parser.read_csv(StringIO(data)) else: expected = DataFrame({"a": [0, 3, 8], "b": [1, 4, 9]}) result = parser.read_csv(StringIO(data), usecols=usecols) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize( "data,kwargs,expected", [ # First, check to see that the response of parser when faced with no # provided columns raises the correct error, with or without usecols. ("", {}, None), ("", {"usecols": ["X"]}, None), ( ",,", {"names": ["Dummy", "X", "Dummy_2"], "usecols": ["X"]}, DataFrame(columns=["X"], index=[0], dtype=np.float64), ), ( "", {"names": ["Dummy", "X", "Dummy_2"], "usecols": ["X"]}, DataFrame(columns=["X"]), ), ], ) def test_read_empty_with_usecols(all_parsers, data, kwargs, expected): # see gh-12493 parser = all_parsers if expected is None: msg = "No columns to parse from file" with pytest.raises(EmptyDataError, match=msg): parser.read_csv(StringIO(data), **kwargs) else: result = parser.read_csv(StringIO(data), **kwargs) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize( "kwargs,expected", [ # gh-8661, gh-8679: this should ignore six lines, including # lines with trailing whitespace and blank lines. ( { "header": None, "delim_whitespace": True, "skiprows": [0, 1, 2, 3, 5, 6], "skip_blank_lines": True, }, DataFrame([[1.0, 2.0, 4.0], [5.1, np.nan, 10.0]]), ), # gh-8983: test skipping set of rows after a row with trailing spaces. ( { "delim_whitespace": True, "skiprows": [1, 2, 3, 5, 6], "skip_blank_lines": True, }, DataFrame({"A": [1.0, 5.1], "B": [2.0, np.nan], "C": [4.0, 10]}), ), ], ) def test_trailing_spaces(all_parsers, kwargs, expected): data = "A B C \nrandom line with trailing spaces \nskip\n1,2,3\n1,2.,4.\nrandom line with trailing tabs\t\t\t\n \n5.1,NaN,10.0\n" # noqa: E501 parser = all_parsers result = parser.read_csv(StringIO(data.replace(",", " ")), **kwargs) tm.assert_frame_equal(result, expected) def test_raise_on_sep_with_delim_whitespace(all_parsers): # see gh-6607 data = "a b c\n1 2 3" parser = all_parsers with pytest.raises(ValueError, match="you can only specify one"): parser.read_csv(StringIO(data), sep=r"\s", delim_whitespace=True) def test_read_filepath_or_buffer(all_parsers): # see gh-43366 parser = all_parsers with pytest.raises(TypeError, match="Expected file path name or file-like"): parser.read_csv(filepath_or_buffer=b"input") @xfail_pyarrow @pytest.mark.parametrize("delim_whitespace", [True, False]) def test_single_char_leading_whitespace(all_parsers, delim_whitespace): # see gh-9710 parser = all_parsers data = """\ MyColumn a b a b\n""" expected = DataFrame({"MyColumn": list("abab")}) result = parser.read_csv( StringIO(data), skipinitialspace=True, delim_whitespace=delim_whitespace ) tm.assert_frame_equal(result, expected) # Skip for now, actually only one test fails though, but its tricky to xfail @skip_pyarrow @pytest.mark.parametrize( "sep,skip_blank_lines,exp_data", [ (",", True, [[1.0, 2.0, 4.0], [5.0, np.nan, 10.0], [-70.0, 0.4, 1.0]]), (r"\s+", True, [[1.0, 2.0, 4.0], [5.0, np.nan, 10.0], [-70.0, 0.4, 1.0]]), ( ",", False, [ [1.0, 2.0, 4.0], [np.nan, np.nan, np.nan], [np.nan, np.nan, np.nan], [5.0, np.nan, 10.0], [np.nan, np.nan, np.nan], [-70.0, 0.4, 1.0], ], ), ], ) def test_empty_lines(all_parsers, sep, skip_blank_lines, exp_data): parser = all_parsers data = """\ A,B,C 1,2.,4. 5.,NaN,10.0 -70,.4,1 """ if sep == r"\s+": data = data.replace(",", " ") result = parser.read_csv(StringIO(data), sep=sep, skip_blank_lines=skip_blank_lines) expected = DataFrame(exp_data, columns=["A", "B", "C"]) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_whitespace_lines(all_parsers): parser = all_parsers data = """ \t \t\t \t A,B,C \t 1,2.,4. 5.,NaN,10.0 """ expected = DataFrame([[1, 2.0, 4.0], [5.0, np.nan, 10.0]], columns=["A", "B", "C"]) result = parser.read_csv(StringIO(data)) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize( "data,expected", [ ( """ A B C D a 1 2 3 4 b 1 2 3 4 c 1 2 3 4 """, DataFrame( [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]], columns=["A", "B", "C", "D"], index=["a", "b", "c"], ), ), ( " a b c\n1 2 3 \n4 5 6\n 7 8 9", DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]], columns=["a", "b", "c"]), ), ], ) def test_whitespace_regex_separator(all_parsers, data, expected): # see gh-6607 parser = all_parsers result = parser.read_csv(StringIO(data), sep=r"\s+") tm.assert_frame_equal(result, expected) def test_sub_character(all_parsers, csv_dir_path): # see gh-16893 filename = os.path.join(csv_dir_path, "sub_char.csv") expected = DataFrame([[1, 2, 3]], columns=["a", "\x1ab", "c"]) parser = all_parsers result = parser.read_csv(filename) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("filename", ["sé-es-vé.csv", "ru-sй.csv", "中文文件名.csv"]) def test_filename_with_special_chars(all_parsers, filename): # see gh-15086. parser = all_parsers df = DataFrame({"a": [1, 2, 3]}) with tm.ensure_clean(filename) as path: df.to_csv(path, index=False) result = parser.read_csv(path) tm.assert_frame_equal(result, df) def test_read_table_same_signature_as_read_csv(all_parsers): # GH-34976 parser = all_parsers table_sign = signature(parser.read_table) csv_sign = signature(parser.read_csv) assert table_sign.parameters.keys() == csv_sign.parameters.keys() assert table_sign.return_annotation == csv_sign.return_annotation for key, csv_param in csv_sign.parameters.items(): table_param = table_sign.parameters[key] if key == "sep": assert csv_param.default == "," assert table_param.default == "\t" assert table_param.annotation == csv_param.annotation assert table_param.kind == csv_param.kind continue assert table_param == csv_param def test_read_table_equivalency_to_read_csv(all_parsers): # see gh-21948 # As of 0.25.0, read_table is undeprecated parser = all_parsers data = "a\tb\n1\t2\n3\t4" expected = parser.read_csv(StringIO(data), sep="\t") result = parser.read_table(StringIO(data)) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("read_func", ["read_csv", "read_table"]) def test_read_csv_and_table_sys_setprofile(all_parsers, read_func): # GH#41069 parser = all_parsers data = "a b\n0 1" sys.setprofile(lambda *a, **k: None) result = getattr(parser, read_func)(StringIO(data)) sys.setprofile(None) expected = DataFrame({"a b": ["0 1"]}) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_first_row_bom(all_parsers): # see gh-26545 parser = all_parsers data = '''\ufeff"Head1"\t"Head2"\t"Head3"''' result = parser.read_csv(StringIO(data), delimiter="\t") expected = DataFrame(columns=["Head1", "Head2", "Head3"]) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_first_row_bom_unquoted(all_parsers): # see gh-36343 parser = all_parsers data = """\ufeffHead1\tHead2\tHead3""" result = parser.read_csv(StringIO(data), delimiter="\t") expected = DataFrame(columns=["Head1", "Head2", "Head3"]) tm.assert_frame_equal(result, expected) @xfail_pyarrow @pytest.mark.parametrize("nrows", range(1, 6)) def test_blank_lines_between_header_and_data_rows(all_parsers, nrows): # GH 28071 ref = DataFrame( [[np.nan, np.nan], [np.nan, np.nan], [1, 2], [np.nan, np.nan], [3, 4]], columns=list("ab"), ) csv = "\nheader\n\na,b\n\n\n1,2\n\n3,4" parser = all_parsers df = parser.read_csv(StringIO(csv), header=3, nrows=nrows, skip_blank_lines=False) tm.assert_frame_equal(df, ref[:nrows]) @xfail_pyarrow def test_no_header_two_extra_columns(all_parsers): # GH 26218 column_names = ["one", "two", "three"] ref = DataFrame([["foo", "bar", "baz"]], columns=column_names) stream = StringIO("foo,bar,baz,bam,blah") parser = all_parsers df = parser.read_csv_check_warnings( ParserWarning, "Length of header or names does not match length of data. " "This leads to a loss of data with index_col=False.", stream, header=None, names=column_names, index_col=False, ) tm.assert_frame_equal(df, ref) def test_read_csv_names_not_accepting_sets(all_parsers): # GH 34946 data = """\ 1,2,3 4,5,6\n""" parser = all_parsers with pytest.raises(ValueError, match="Names should be an ordered collection."): parser.read_csv(StringIO(data), names=set("QAZ")) @xfail_pyarrow def test_read_table_delim_whitespace_default_sep(all_parsers): # GH: 35958 f = StringIO("a b c\n1 -2 -3\n4 5 6") parser = all_parsers result = parser.read_table(f, delim_whitespace=True) expected = DataFrame({"a": [1, 4], "b": [-2, 5], "c": [-3, 6]}) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("delimiter", [",", "\t"]) def test_read_csv_delim_whitespace_non_default_sep(all_parsers, delimiter): # GH: 35958 f = StringIO("a b c\n1 -2 -3\n4 5 6") parser = all_parsers msg = ( "Specified a delimiter with both sep and " "delim_whitespace=True; you can only specify one." ) with pytest.raises(ValueError, match=msg): parser.read_csv(f, delim_whitespace=True, sep=delimiter) with pytest.raises(ValueError, match=msg): parser.read_csv(f, delim_whitespace=True, delimiter=delimiter) def test_read_csv_delimiter_and_sep_no_default(all_parsers): # GH#39823 f = StringIO("a,b\n1,2") parser = all_parsers msg = "Specified a sep and a delimiter; you can only specify one." with pytest.raises(ValueError, match=msg): parser.read_csv(f, sep=" ", delimiter=".") @pytest.mark.parametrize("kwargs", [{"delimiter": "\n"}, {"sep": "\n"}]) def test_read_csv_line_break_as_separator(kwargs, all_parsers): # GH#43528 parser = all_parsers data = """a,b,c 1,2,3 """ msg = ( r"Specified \\n as separator or delimiter. This forces the python engine " r"which does not accept a line terminator. Hence it is not allowed to use " r"the line terminator as separator." ) with pytest.raises(ValueError, match=msg): parser.read_csv(StringIO(data), **kwargs) @pytest.mark.parametrize("delimiter", [",", "\t"]) def test_read_table_delim_whitespace_non_default_sep(all_parsers, delimiter): # GH: 35958 f = StringIO("a b c\n1 -2 -3\n4 5 6") parser = all_parsers msg = ( "Specified a delimiter with both sep and " "delim_whitespace=True; you can only specify one." ) with pytest.raises(ValueError, match=msg): parser.read_table(f, delim_whitespace=True, sep=delimiter) with pytest.raises(ValueError, match=msg): parser.read_table(f, delim_whitespace=True, delimiter=delimiter) @xfail_pyarrow def test_dict_keys_as_names(all_parsers): # GH: 36928 data = "1,2" keys = {"a": int, "b": int}.keys() parser = all_parsers result = parser.read_csv(StringIO(data), names=keys) expected = DataFrame({"a": [1], "b": [2]}) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_encoding_surrogatepass(all_parsers): # GH39017 parser = all_parsers content = b"\xed\xbd\xbf" decoded = content.decode("utf-8", errors="surrogatepass") expected = DataFrame({decoded: [decoded]}, index=[decoded * 2]) expected.index.name = decoded * 2 with tm.ensure_clean() as path: Path(path).write_bytes( content * 2 + b"," + content + b"\n" + content * 2 + b"," + content ) df = parser.read_csv(path, encoding_errors="surrogatepass", index_col=0) tm.assert_frame_equal(df, expected) with pytest.raises(UnicodeDecodeError, match="'utf-8' codec can't decode byte"): parser.read_csv(path) def test_malformed_second_line(all_parsers): # see GH14782 parser = all_parsers data = "\na\nb\n" result = parser.read_csv(StringIO(data), skip_blank_lines=False, header=1) expected = DataFrame({"a": ["b"]}) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_short_single_line(all_parsers): # GH 47566 parser = all_parsers columns = ["a", "b", "c"] data = "1,2" result = parser.read_csv(StringIO(data), header=None, names=columns) expected = DataFrame({"a": [1], "b": [2], "c": [np.nan]}) tm.assert_frame_equal(result, expected) @xfail_pyarrow def test_short_multi_line(all_parsers): # GH 47566 parser = all_parsers columns = ["a", "b", "c"] data = "1,2\n1,2" result = parser.read_csv(StringIO(data), header=None, names=columns) expected = DataFrame({"a": [1, 1], "b": [2, 2], "c": [np.nan, np.nan]}) tm.assert_frame_equal(result, expected) def test_read_seek(all_parsers): # GH48646 parser = all_parsers prefix = "### DATA\n" content = "nkey,value\ntables,rectangular\n" with tm.ensure_clean() as path: Path(path).write_text(prefix + content, encoding="utf-8") with open(path, encoding="utf-8") as file: file.readline() actual = parser.read_csv(file) expected = parser.read_csv(StringIO(content)) tm.assert_frame_equal(actual, expected)