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335 lines
9.2 KiB
335 lines
9.2 KiB
"""
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Tests that skipped rows are properly handled during
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parsing for all of the parsers defined in parsers.py
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"""
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from datetime import datetime
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from io import StringIO
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import numpy as np
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import pytest
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from pandas.errors import EmptyDataError
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from pandas import (
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DataFrame,
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Index,
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)
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import pandas._testing as tm
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xfail_pyarrow = pytest.mark.usefixtures("pyarrow_xfail")
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pytestmark = pytest.mark.filterwarnings(
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"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
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)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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@pytest.mark.parametrize("skiprows", [list(range(6)), 6])
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def test_skip_rows_bug(all_parsers, skiprows):
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# see gh-505
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parser = all_parsers
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text = """#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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1/1/2000,1.,2.,3.
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1/2/2000,4,5,6
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1/3/2000,7,8,9
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"""
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result = parser.read_csv(
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StringIO(text), skiprows=skiprows, header=None, index_col=0, parse_dates=True
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)
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index = Index(
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[datetime(2000, 1, 1), datetime(2000, 1, 2), datetime(2000, 1, 3)], name=0
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)
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expected = DataFrame(
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np.arange(1.0, 10.0).reshape((3, 3)), columns=[1, 2, 3], index=index
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)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_deep_skip_rows(all_parsers):
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# see gh-4382
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parser = all_parsers
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data = "a,b,c\n" + "\n".join(
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[",".join([str(i), str(i + 1), str(i + 2)]) for i in range(10)]
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)
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condensed_data = "a,b,c\n" + "\n".join(
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[",".join([str(i), str(i + 1), str(i + 2)]) for i in [0, 1, 2, 3, 4, 6, 8, 9]]
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)
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result = parser.read_csv(StringIO(data), skiprows=[6, 8])
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condensed_result = parser.read_csv(StringIO(condensed_data))
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tm.assert_frame_equal(result, condensed_result)
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@xfail_pyarrow # AssertionError: DataFrame are different
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def test_skip_rows_blank(all_parsers):
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# see gh-9832
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parser = all_parsers
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text = """#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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#foo,a,b,c
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1/1/2000,1.,2.,3.
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1/2/2000,4,5,6
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1/3/2000,7,8,9
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"""
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data = parser.read_csv(
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StringIO(text), skiprows=6, header=None, index_col=0, parse_dates=True
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)
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index = Index(
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[datetime(2000, 1, 1), datetime(2000, 1, 2), datetime(2000, 1, 3)], name=0
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)
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expected = DataFrame(
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np.arange(1.0, 10.0).reshape((3, 3)), columns=[1, 2, 3], index=index
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)
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tm.assert_frame_equal(data, expected)
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@pytest.mark.parametrize(
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"data,kwargs,expected",
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[
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(
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"""id,text,num_lines
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1,"line 11
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line 12",2
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2,"line 21
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line 22",2
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3,"line 31",1""",
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{"skiprows": [1]},
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DataFrame(
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[[2, "line 21\nline 22", 2], [3, "line 31", 1]],
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columns=["id", "text", "num_lines"],
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),
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),
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(
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"a,b,c\n~a\n b~,~e\n d~,~f\n f~\n1,2,~12\n 13\n 14~",
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{"quotechar": "~", "skiprows": [2]},
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DataFrame([["a\n b", "e\n d", "f\n f"]], columns=["a", "b", "c"]),
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),
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(
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(
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"Text,url\n~example\n "
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"sentence\n one~,url1\n~"
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"example\n sentence\n two~,url2\n~"
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"example\n sentence\n three~,url3"
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),
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{"quotechar": "~", "skiprows": [1, 3]},
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DataFrame([["example\n sentence\n two", "url2"]], columns=["Text", "url"]),
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),
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],
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)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_row_with_newline(all_parsers, data, kwargs, expected):
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# see gh-12775 and gh-10911
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parser = all_parsers
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result = parser.read_csv(StringIO(data), **kwargs)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_row_with_quote(all_parsers):
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# see gh-12775 and gh-10911
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parser = all_parsers
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data = """id,text,num_lines
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1,"line '11' line 12",2
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2,"line '21' line 22",2
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3,"line '31' line 32",1"""
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exp_data = [[2, "line '21' line 22", 2], [3, "line '31' line 32", 1]]
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expected = DataFrame(exp_data, columns=["id", "text", "num_lines"])
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result = parser.read_csv(StringIO(data), skiprows=[1])
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"data,exp_data",
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[
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(
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"""id,text,num_lines
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1,"line \n'11' line 12",2
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2,"line \n'21' line 22",2
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3,"line \n'31' line 32",1""",
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[[2, "line \n'21' line 22", 2], [3, "line \n'31' line 32", 1]],
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),
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(
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"""id,text,num_lines
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1,"line '11\n' line 12",2
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2,"line '21\n' line 22",2
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3,"line '31\n' line 32",1""",
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[[2, "line '21\n' line 22", 2], [3, "line '31\n' line 32", 1]],
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),
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(
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"""id,text,num_lines
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1,"line '11\n' \r\tline 12",2
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2,"line '21\n' \r\tline 22",2
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3,"line '31\n' \r\tline 32",1""",
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[[2, "line '21\n' \r\tline 22", 2], [3, "line '31\n' \r\tline 32", 1]],
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),
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],
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)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_row_with_newline_and_quote(all_parsers, data, exp_data):
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# see gh-12775 and gh-10911
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parser = all_parsers
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result = parser.read_csv(StringIO(data), skiprows=[1])
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expected = DataFrame(exp_data, columns=["id", "text", "num_lines"])
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: The 'delim_whitespace' option is not supported
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@pytest.mark.parametrize(
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"lineterminator", ["\n", "\r\n", "\r"] # "LF" # "CRLF" # "CR"
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)
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def test_skiprows_lineterminator(all_parsers, lineterminator, request):
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# see gh-9079
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parser = all_parsers
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data = "\n".join(
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[
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"SMOSMANIA ThetaProbe-ML2X ",
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"2007/01/01 01:00 0.2140 U M ",
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"2007/01/01 02:00 0.2141 M O ",
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"2007/01/01 04:00 0.2142 D M ",
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]
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)
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expected = DataFrame(
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[
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["2007/01/01", "01:00", 0.2140, "U", "M"],
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["2007/01/01", "02:00", 0.2141, "M", "O"],
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["2007/01/01", "04:00", 0.2142, "D", "M"],
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],
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columns=["date", "time", "var", "flag", "oflag"],
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)
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if parser.engine == "python" and lineterminator == "\r":
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mark = pytest.mark.xfail(reason="'CR' not respect with the Python parser yet")
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request.applymarker(mark)
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data = data.replace("\n", lineterminator)
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depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
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with tm.assert_produces_warning(
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FutureWarning, match=depr_msg, check_stacklevel=False
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):
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result = parser.read_csv(
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StringIO(data),
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skiprows=1,
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delim_whitespace=True,
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names=["date", "time", "var", "flag", "oflag"],
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)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # AssertionError: DataFrame are different
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def test_skiprows_infield_quote(all_parsers):
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# see gh-14459
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parser = all_parsers
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data = 'a"\nb"\na\n1'
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expected = DataFrame({"a": [1]})
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result = parser.read_csv(StringIO(data), skiprows=2)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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@pytest.mark.parametrize(
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"kwargs,expected",
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[
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({}, DataFrame({"1": [3, 5]})),
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({"header": 0, "names": ["foo"]}, DataFrame({"foo": [3, 5]})),
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],
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)
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def test_skip_rows_callable(all_parsers, kwargs, expected):
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parser = all_parsers
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data = "a\n1\n2\n3\n4\n5"
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result = parser.read_csv(StringIO(data), skiprows=lambda x: x % 2 == 0, **kwargs)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_rows_callable_not_in(all_parsers):
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parser = all_parsers
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data = "0,a\n1,b\n2,c\n3,d\n4,e"
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expected = DataFrame([[1, "b"], [3, "d"]])
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result = parser.read_csv(
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StringIO(data), header=None, skiprows=lambda x: x not in [1, 3]
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)
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_rows_skip_all(all_parsers):
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parser = all_parsers
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data = "a\n1\n2\n3\n4\n5"
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msg = "No columns to parse from file"
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with pytest.raises(EmptyDataError, match=msg):
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parser.read_csv(StringIO(data), skiprows=lambda x: True)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_rows_bad_callable(all_parsers):
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msg = "by zero"
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parser = all_parsers
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data = "a\n1\n2\n3\n4\n5"
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with pytest.raises(ZeroDivisionError, match=msg):
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parser.read_csv(StringIO(data), skiprows=lambda x: 1 / 0)
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@xfail_pyarrow # ValueError: skiprows argument must be an integer
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def test_skip_rows_and_n_rows(all_parsers):
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# GH#44021
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data = """a,b
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1,a
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2,b
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3,c
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4,d
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5,e
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6,f
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7,g
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8,h
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"""
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parser = all_parsers
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result = parser.read_csv(StringIO(data), nrows=5, skiprows=[2, 4, 6])
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expected = DataFrame({"a": [1, 3, 5, 7, 8], "b": ["a", "c", "e", "g", "h"]})
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tm.assert_frame_equal(result, expected)
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@xfail_pyarrow
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def test_skip_rows_with_chunks(all_parsers):
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# GH 55677
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data = """col_a
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10
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20
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30
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40
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50
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60
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70
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80
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90
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100
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"""
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parser = all_parsers
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reader = parser.read_csv(
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StringIO(data), engine=parser, skiprows=lambda x: x in [1, 4, 5], chunksize=4
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)
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df1 = next(reader)
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df2 = next(reader)
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tm.assert_frame_equal(df1, DataFrame({"col_a": [20, 30, 60, 70]}))
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tm.assert_frame_equal(df2, DataFrame({"col_a": [80, 90, 100]}, index=[4, 5, 6]))
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