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| """
| Tests that duplicate columns are handled appropriately when parsed by the
| CSV engine. In general, the expected result is that they are either thoroughly
| de-duplicated (if mangling requested) or ignored otherwise.
| """
| from io import StringIO
|
| import pytest
|
| from pandas import DataFrame
| import pandas._testing as tm
|
| skip_pyarrow = pytest.mark.usefixtures("pyarrow_skip")
|
|
| @skip_pyarrow
| def test_basic(all_parsers):
| parser = all_parsers
|
| data = "a,a,b,b,b\n1,2,3,4,5"
| result = parser.read_csv(StringIO(data), sep=",")
|
| expected = DataFrame([[1, 2, 3, 4, 5]], columns=["a", "a.1", "b", "b.1", "b.2"])
| tm.assert_frame_equal(result, expected)
|
|
| @skip_pyarrow
| def test_basic_names(all_parsers):
| # See gh-7160
| parser = all_parsers
|
| data = "a,b,a\n0,1,2\n3,4,5"
| expected = DataFrame([[0, 1, 2], [3, 4, 5]], columns=["a", "b", "a.1"])
|
| result = parser.read_csv(StringIO(data))
| tm.assert_frame_equal(result, expected)
|
|
| def test_basic_names_raise(all_parsers):
| # See gh-7160
| parser = all_parsers
|
| data = "0,1,2\n3,4,5"
| with pytest.raises(ValueError, match="Duplicate names"):
| parser.read_csv(StringIO(data), names=["a", "b", "a"])
|
|
| @skip_pyarrow
| @pytest.mark.parametrize(
| "data,expected",
| [
| ("a,a,a.1\n1,2,3", DataFrame([[1, 2, 3]], columns=["a", "a.2", "a.1"])),
| (
| "a,a,a.1,a.1.1,a.1.1.1,a.1.1.1.1\n1,2,3,4,5,6",
| DataFrame(
| [[1, 2, 3, 4, 5, 6]],
| columns=["a", "a.2", "a.1", "a.1.1", "a.1.1.1", "a.1.1.1.1"],
| ),
| ),
| (
| "a,a,a.3,a.1,a.2,a,a\n1,2,3,4,5,6,7",
| DataFrame(
| [[1, 2, 3, 4, 5, 6, 7]],
| columns=["a", "a.4", "a.3", "a.1", "a.2", "a.5", "a.6"],
| ),
| ),
| ],
| )
| def test_thorough_mangle_columns(all_parsers, data, expected):
| # see gh-17060
| parser = all_parsers
|
| result = parser.read_csv(StringIO(data))
| tm.assert_frame_equal(result, expected)
|
|
| @skip_pyarrow
| @pytest.mark.parametrize(
| "data,names,expected",
| [
| (
| "a,b,b\n1,2,3",
| ["a.1", "a.1", "a.1.1"],
| DataFrame(
| [["a", "b", "b"], ["1", "2", "3"]], columns=["a.1", "a.1.1", "a.1.1.1"]
| ),
| ),
| (
| "a,b,c,d,e,f\n1,2,3,4,5,6",
| ["a", "a", "a.1", "a.1.1", "a.1.1.1", "a.1.1.1.1"],
| DataFrame(
| [["a", "b", "c", "d", "e", "f"], ["1", "2", "3", "4", "5", "6"]],
| columns=["a", "a.1", "a.1.1", "a.1.1.1", "a.1.1.1.1", "a.1.1.1.1.1"],
| ),
| ),
| (
| "a,b,c,d,e,f,g\n1,2,3,4,5,6,7",
| ["a", "a", "a.3", "a.1", "a.2", "a", "a"],
| DataFrame(
| [
| ["a", "b", "c", "d", "e", "f", "g"],
| ["1", "2", "3", "4", "5", "6", "7"],
| ],
| columns=["a", "a.1", "a.3", "a.1.1", "a.2", "a.2.1", "a.3.1"],
| ),
| ),
| ],
| )
| def test_thorough_mangle_names(all_parsers, data, names, expected):
| # see gh-17095
| parser = all_parsers
|
| with pytest.raises(ValueError, match="Duplicate names"):
| parser.read_csv(StringIO(data), names=names)
|
|
| @skip_pyarrow
| def test_mangled_unnamed_placeholders(all_parsers):
| # xref gh-13017
| orig_key = "0"
| parser = all_parsers
|
| orig_value = [1, 2, 3]
| df = DataFrame({orig_key: orig_value})
|
| # This test recursively updates `df`.
| for i in range(3):
| expected = DataFrame()
|
| for j in range(i + 1):
| col_name = "Unnamed: 0" + f".{1*j}" * min(j, 1)
| expected.insert(loc=0, column=col_name, value=[0, 1, 2])
|
| expected[orig_key] = orig_value
| df = parser.read_csv(StringIO(df.to_csv()))
|
| tm.assert_frame_equal(df, expected)
|
|
| @skip_pyarrow
| def test_mangle_dupe_cols_already_exists(all_parsers):
| # GH#14704
| parser = all_parsers
|
| data = "a,a,a.1,a,a.3,a.1,a.1.1\n1,2,3,4,5,6,7"
| result = parser.read_csv(StringIO(data))
| expected = DataFrame(
| [[1, 2, 3, 4, 5, 6, 7]],
| columns=["a", "a.2", "a.1", "a.4", "a.3", "a.1.2", "a.1.1"],
| )
| tm.assert_frame_equal(result, expected)
|
|
| @skip_pyarrow
| def test_mangle_dupe_cols_already_exists_unnamed_col(all_parsers):
| # GH#14704
| parser = all_parsers
|
| data = ",Unnamed: 0,,Unnamed: 2\n1,2,3,4"
| result = parser.read_csv(StringIO(data))
| expected = DataFrame(
| [[1, 2, 3, 4]],
| columns=["Unnamed: 0.1", "Unnamed: 0", "Unnamed: 2.1", "Unnamed: 2"],
| )
| tm.assert_frame_equal(result, expected)
|
|
