3RNN/Lib/site-packages/pandas/tests/io/parser/test_skiprows.py
2024-05-26 19:49:15 +02:00

335 lines
9.2 KiB
Python

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