449 lines
16 KiB
Python
449 lines
16 KiB
Python
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"""Tests dealing with the NDFrame.allows_duplicates."""
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import operator
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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not_implemented = pytest.mark.xfail(reason="Not implemented.")
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# ----------------------------------------------------------------------------
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# Preservation
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class TestPreserves:
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@pytest.mark.parametrize(
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"cls, data",
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[
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(pd.Series, np.array([])),
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(pd.Series, [1, 2]),
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(pd.DataFrame, {}),
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(pd.DataFrame, {"A": [1, 2]}),
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],
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)
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def test_construction_ok(self, cls, data):
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result = cls(data)
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assert result.flags.allows_duplicate_labels is True
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result = cls(data).set_flags(allows_duplicate_labels=False)
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assert result.flags.allows_duplicate_labels is False
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@pytest.mark.parametrize(
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"func",
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[
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operator.itemgetter(["a"]),
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operator.methodcaller("add", 1),
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operator.methodcaller("rename", str.upper),
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operator.methodcaller("rename", "name"),
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operator.methodcaller("abs"),
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np.abs,
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],
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)
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def test_preserved_series(self, func):
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s = pd.Series([0, 1], index=["a", "b"]).set_flags(allows_duplicate_labels=False)
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assert func(s).flags.allows_duplicate_labels is False
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@pytest.mark.parametrize(
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"other", [pd.Series(0, index=["a", "b", "c"]), pd.Series(0, index=["a", "b"])]
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)
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# TODO: frame
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@not_implemented
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def test_align(self, other):
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s = pd.Series([0, 1], index=["a", "b"]).set_flags(allows_duplicate_labels=False)
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a, b = s.align(other)
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assert a.flags.allows_duplicate_labels is False
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assert b.flags.allows_duplicate_labels is False
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def test_preserved_frame(self):
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df = pd.DataFrame({"A": [1, 2], "B": [3, 4]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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)
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assert df.loc[["a"]].flags.allows_duplicate_labels is False
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assert df.loc[:, ["A", "B"]].flags.allows_duplicate_labels is False
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def test_to_frame(self):
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ser = pd.Series(dtype=float).set_flags(allows_duplicate_labels=False)
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assert ser.to_frame().flags.allows_duplicate_labels is False
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@pytest.mark.parametrize("func", ["add", "sub"])
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@pytest.mark.parametrize("frame", [False, True])
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@pytest.mark.parametrize("other", [1, pd.Series([1, 2], name="A")])
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def test_binops(self, func, other, frame):
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df = pd.Series([1, 2], name="A", index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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)
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if frame:
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df = df.to_frame()
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if isinstance(other, pd.Series) and frame:
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other = other.to_frame()
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func = operator.methodcaller(func, other)
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assert df.flags.allows_duplicate_labels is False
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assert func(df).flags.allows_duplicate_labels is False
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def test_preserve_getitem(self):
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df = pd.DataFrame({"A": [1, 2]}).set_flags(allows_duplicate_labels=False)
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assert df[["A"]].flags.allows_duplicate_labels is False
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assert df["A"].flags.allows_duplicate_labels is False
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assert df.loc[0].flags.allows_duplicate_labels is False
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assert df.loc[[0]].flags.allows_duplicate_labels is False
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assert df.loc[0, ["A"]].flags.allows_duplicate_labels is False
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def test_ndframe_getitem_caching_issue(self, request, using_copy_on_write):
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if not using_copy_on_write:
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request.node.add_marker(pytest.mark.xfail(reason="Unclear behavior."))
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# NDFrame.__getitem__ will cache the first df['A']. May need to
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# invalidate that cache? Update the cached entries?
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df = pd.DataFrame({"A": [0]}).set_flags(allows_duplicate_labels=False)
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assert df["A"].flags.allows_duplicate_labels is False
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df.flags.allows_duplicate_labels = True
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assert df["A"].flags.allows_duplicate_labels is True
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@pytest.mark.parametrize(
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"objs, kwargs",
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[
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# Series
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(
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[
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pd.Series(1, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.Series(2, index=["c", "d"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{},
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),
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(
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[
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pd.Series(1, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.Series(2, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{"ignore_index": True},
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),
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(
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[
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pd.Series(1, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.Series(2, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{"axis": 1},
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),
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# Frame
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(
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[
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pd.DataFrame({"A": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.DataFrame({"A": [1, 2]}, index=["c", "d"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{},
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),
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(
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[
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pd.DataFrame({"A": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.DataFrame({"A": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{"ignore_index": True},
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),
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(
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[
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pd.DataFrame({"A": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.DataFrame({"B": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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],
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{"axis": 1},
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),
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# Series / Frame
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(
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[
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pd.DataFrame({"A": [1, 2]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.Series(
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[1, 2],
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index=["a", "b"],
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name="B",
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).set_flags(
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allows_duplicate_labels=False,
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),
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],
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{"axis": 1},
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),
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],
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)
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def test_concat(self, objs, kwargs):
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result = pd.concat(objs, **kwargs)
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assert result.flags.allows_duplicate_labels is False
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@pytest.mark.parametrize(
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"left, right, kwargs, expected",
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[
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# false false false
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pytest.param(
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pd.DataFrame({"A": [0, 1]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.DataFrame({"B": [0, 1]}, index=["a", "d"]).set_flags(
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allows_duplicate_labels=False
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),
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{"left_index": True, "right_index": True},
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False,
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marks=not_implemented,
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),
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# false true false
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pytest.param(
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pd.DataFrame({"A": [0, 1]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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),
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pd.DataFrame({"B": [0, 1]}, index=["a", "d"]),
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{"left_index": True, "right_index": True},
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False,
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marks=not_implemented,
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),
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# true true true
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(
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pd.DataFrame({"A": [0, 1]}, index=["a", "b"]),
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pd.DataFrame({"B": [0, 1]}, index=["a", "d"]),
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{"left_index": True, "right_index": True},
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True,
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),
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],
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)
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def test_merge(self, left, right, kwargs, expected):
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result = pd.merge(left, right, **kwargs)
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assert result.flags.allows_duplicate_labels is expected
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@not_implemented
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def test_groupby(self):
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# XXX: This is under tested
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# TODO:
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# - apply
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# - transform
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# - Should passing a grouper that disallows duplicates propagate?
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df = pd.DataFrame({"A": [1, 2, 3]}).set_flags(allows_duplicate_labels=False)
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result = df.groupby([0, 0, 1]).agg("count")
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assert result.flags.allows_duplicate_labels is False
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@pytest.mark.parametrize("frame", [True, False])
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@not_implemented
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def test_window(self, frame):
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df = pd.Series(
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1,
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index=pd.date_range("2000", periods=12),
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name="A",
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allows_duplicate_labels=False,
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)
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if frame:
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df = df.to_frame()
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assert df.rolling(3).mean().flags.allows_duplicate_labels is False
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assert df.ewm(3).mean().flags.allows_duplicate_labels is False
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assert df.expanding(3).mean().flags.allows_duplicate_labels is False
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# ----------------------------------------------------------------------------
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# Raises
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class TestRaises:
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@pytest.mark.parametrize(
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"cls, axes",
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[
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(pd.Series, {"index": ["a", "a"], "dtype": float}),
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(pd.DataFrame, {"index": ["a", "a"]}),
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(pd.DataFrame, {"index": ["a", "a"], "columns": ["b", "b"]}),
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(pd.DataFrame, {"columns": ["b", "b"]}),
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],
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)
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def test_set_flags_with_duplicates(self, cls, axes):
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result = cls(**axes)
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assert result.flags.allows_duplicate_labels is True
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msg = "Index has duplicates."
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with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
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cls(**axes).set_flags(allows_duplicate_labels=False)
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@pytest.mark.parametrize(
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"data",
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[
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pd.Series(index=[0, 0], dtype=float),
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pd.DataFrame(index=[0, 0]),
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pd.DataFrame(columns=[0, 0]),
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],
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)
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def test_setting_allows_duplicate_labels_raises(self, data):
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msg = "Index has duplicates."
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with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
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data.flags.allows_duplicate_labels = False
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assert data.flags.allows_duplicate_labels is True
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def test_series_raises(self):
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a = pd.Series(0, index=["a", "b"])
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b = pd.Series([0, 1], index=["a", "b"]).set_flags(allows_duplicate_labels=False)
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msg = "Index has duplicates."
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with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
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pd.concat([a, b])
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@pytest.mark.parametrize(
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"getter, target",
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[
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(operator.itemgetter(["A", "A"]), None),
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# loc
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(operator.itemgetter(["a", "a"]), "loc"),
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pytest.param(operator.itemgetter(("a", ["A", "A"])), "loc"),
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(operator.itemgetter((["a", "a"], "A")), "loc"),
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# iloc
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(operator.itemgetter([0, 0]), "iloc"),
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pytest.param(operator.itemgetter((0, [0, 0])), "iloc"),
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pytest.param(operator.itemgetter(([0, 0], 0)), "iloc"),
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],
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)
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def test_getitem_raises(self, getter, target):
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df = pd.DataFrame({"A": [1, 2], "B": [3, 4]}, index=["a", "b"]).set_flags(
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allows_duplicate_labels=False
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)
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if target:
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# df, df.loc, or df.iloc
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target = getattr(df, target)
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else:
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target = df
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msg = "Index has duplicates."
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with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
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getter(target)
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@pytest.mark.parametrize(
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"objs, kwargs",
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[
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(
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[
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pd.Series(1, index=[0, 1], name="a").set_flags(
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allows_duplicate_labels=False
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),
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pd.Series(2, index=[0, 1], name="a").set_flags(
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allows_duplicate_labels=False
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),
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],
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{"axis": 1},
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)
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],
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)
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def test_concat_raises(self, objs, kwargs):
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msg = "Index has duplicates."
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with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
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pd.concat(objs, **kwargs)
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@not_implemented
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def test_merge_raises(self):
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a = pd.DataFrame({"A": [0, 1, 2]}, index=["a", "b", "c"]).set_flags(
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allows_duplicate_labels=False
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)
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b = pd.DataFrame({"B": [0, 1, 2]}, index=["a", "b", "b"])
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msg = "Index has duplicates."
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|
|
with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
|
||
|
|
pd.merge(a, b, left_index=True, right_index=True)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"idx",
|
||
|
|
[
|
||
|
|
pd.Index([1, 1]),
|
||
|
|
pd.Index(["a", "a"]),
|
||
|
|
pd.Index([1.1, 1.1]),
|
||
|
|
pd.PeriodIndex([pd.Period("2000", "D")] * 2),
|
||
|
|
pd.DatetimeIndex([pd.Timestamp("2000")] * 2),
|
||
|
|
pd.TimedeltaIndex([pd.Timedelta("1D")] * 2),
|
||
|
|
pd.CategoricalIndex(["a", "a"]),
|
||
|
|
pd.IntervalIndex([pd.Interval(0, 1)] * 2),
|
||
|
|
pd.MultiIndex.from_tuples([("a", 1), ("a", 1)]),
|
||
|
|
],
|
||
|
|
ids=lambda x: type(x).__name__,
|
||
|
|
)
|
||
|
|
def test_raises_basic(idx):
|
||
|
|
msg = "Index has duplicates."
|
||
|
|
with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
|
||
|
|
pd.Series(1, index=idx).set_flags(allows_duplicate_labels=False)
|
||
|
|
|
||
|
|
with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
|
||
|
|
pd.DataFrame({"A": [1, 1]}, index=idx).set_flags(allows_duplicate_labels=False)
|
||
|
|
|
||
|
|
with pytest.raises(pd.errors.DuplicateLabelError, match=msg):
|
||
|
|
pd.DataFrame([[1, 2]], columns=idx).set_flags(allows_duplicate_labels=False)
|
||
|
|
|
||
|
|
|
||
|
|
def test_format_duplicate_labels_message():
|
||
|
|
idx = pd.Index(["a", "b", "a", "b", "c"])
|
||
|
|
result = idx._format_duplicate_message()
|
||
|
|
expected = pd.DataFrame(
|
||
|
|
{"positions": [[0, 2], [1, 3]]}, index=pd.Index(["a", "b"], name="label")
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_format_duplicate_labels_message_multi():
|
||
|
|
idx = pd.MultiIndex.from_product([["A"], ["a", "b", "a", "b", "c"]])
|
||
|
|
result = idx._format_duplicate_message()
|
||
|
|
expected = pd.DataFrame(
|
||
|
|
{"positions": [[0, 2], [1, 3]]},
|
||
|
|
index=pd.MultiIndex.from_product([["A"], ["a", "b"]]),
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_dataframe_insert_raises():
|
||
|
|
df = pd.DataFrame({"A": [1, 2]}).set_flags(allows_duplicate_labels=False)
|
||
|
|
msg = "Cannot specify"
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.insert(0, "A", [3, 4], allow_duplicates=True)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, frame_only",
|
||
|
|
[
|
||
|
|
(operator.methodcaller("set_index", "A", inplace=True), True),
|
||
|
|
(operator.methodcaller("reset_index", inplace=True), True),
|
||
|
|
(operator.methodcaller("rename", lambda x: x, inplace=True), False),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_inplace_raises(method, frame_only):
|
||
|
|
df = pd.DataFrame({"A": [0, 0], "B": [1, 2]}).set_flags(
|
||
|
|
allows_duplicate_labels=False
|
||
|
|
)
|
||
|
|
s = df["A"]
|
||
|
|
s.flags.allows_duplicate_labels = False
|
||
|
|
msg = "Cannot specify"
|
||
|
|
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
method(df)
|
||
|
|
if not frame_only:
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
method(s)
|
||
|
|
|
||
|
|
|
||
|
|
def test_pickle():
|
||
|
|
a = pd.Series([1, 2]).set_flags(allows_duplicate_labels=False)
|
||
|
|
b = tm.round_trip_pickle(a)
|
||
|
|
tm.assert_series_equal(a, b)
|
||
|
|
|
||
|
|
a = pd.DataFrame({"A": []}).set_flags(allows_duplicate_labels=False)
|
||
|
|
b = tm.round_trip_pickle(a)
|
||
|
|
tm.assert_frame_equal(a, b)
|