267 lines
8.8 KiB
Python
267 lines
8.8 KiB
Python
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import numpy as np
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import pytest
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from pandas import (
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DataFrame,
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Float64Index,
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Int64Index,
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MultiIndex,
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date_range,
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to_datetime,
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)
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import pandas._testing as tm
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class TestMultiIndexPartial:
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def test_getitem_partial_int(self):
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# GH 12416
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# with single item
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l1 = [10, 20]
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l2 = ["a", "b"]
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df = DataFrame(index=range(2), columns=MultiIndex.from_product([l1, l2]))
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expected = DataFrame(index=range(2), columns=l2)
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result = df[20]
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tm.assert_frame_equal(result, expected)
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# with list
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expected = DataFrame(
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index=range(2), columns=MultiIndex.from_product([l1[1:], l2])
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)
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result = df[[20]]
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tm.assert_frame_equal(result, expected)
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# missing item:
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with pytest.raises(KeyError, match="1"):
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df[1]
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with pytest.raises(KeyError, match=r"'\[1\] not in index'"):
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df[[1]]
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def test_series_slice_partial(self):
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pass
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def test_xs_partial(
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self,
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multiindex_dataframe_random_data,
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multiindex_year_month_day_dataframe_random_data,
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):
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frame = multiindex_dataframe_random_data
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ymd = multiindex_year_month_day_dataframe_random_data
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result = frame.xs("foo")
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result2 = frame.loc["foo"]
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expected = frame.T["foo"].T
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tm.assert_frame_equal(result, expected)
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tm.assert_frame_equal(result, result2)
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result = ymd.xs((2000, 4))
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expected = ymd.loc[2000, 4]
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tm.assert_frame_equal(result, expected)
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# ex from #1796
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index = MultiIndex(
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levels=[["foo", "bar"], ["one", "two"], [-1, 1]],
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codes=[
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[0, 0, 0, 0, 1, 1, 1, 1],
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[0, 0, 1, 1, 0, 0, 1, 1],
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[0, 1, 0, 1, 0, 1, 0, 1],
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],
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)
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df = DataFrame(np.random.randn(8, 4), index=index, columns=list("abcd"))
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result = df.xs(["foo", "one"])
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expected = df.loc["foo", "one"]
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tm.assert_frame_equal(result, expected)
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def test_getitem_partial(self, multiindex_year_month_day_dataframe_random_data):
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ymd = multiindex_year_month_day_dataframe_random_data
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ymd = ymd.T
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result = ymd[2000, 2]
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expected = ymd.reindex(columns=ymd.columns[ymd.columns.codes[1] == 1])
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expected.columns = expected.columns.droplevel(0).droplevel(0)
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tm.assert_frame_equal(result, expected)
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def test_fancy_slice_partial(
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self,
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multiindex_dataframe_random_data,
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multiindex_year_month_day_dataframe_random_data,
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):
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frame = multiindex_dataframe_random_data
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result = frame.loc["bar":"baz"]
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expected = frame[3:7]
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tm.assert_frame_equal(result, expected)
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ymd = multiindex_year_month_day_dataframe_random_data
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result = ymd.loc[(2000, 2):(2000, 4)]
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lev = ymd.index.codes[1]
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expected = ymd[(lev >= 1) & (lev <= 3)]
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tm.assert_frame_equal(result, expected)
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def test_getitem_partial_column_select(self):
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idx = MultiIndex(
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codes=[[0, 0, 0], [0, 1, 1], [1, 0, 1]],
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levels=[["a", "b"], ["x", "y"], ["p", "q"]],
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)
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df = DataFrame(np.random.rand(3, 2), index=idx)
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result = df.loc[("a", "y"), :]
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expected = df.loc[("a", "y")]
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tm.assert_frame_equal(result, expected)
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result = df.loc[("a", "y"), [1, 0]]
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expected = df.loc[("a", "y")][[1, 0]]
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tm.assert_frame_equal(result, expected)
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with pytest.raises(KeyError, match=r"\('a', 'foo'\)"):
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df.loc[("a", "foo"), :]
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def test_partial_set(self, multiindex_year_month_day_dataframe_random_data):
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# GH #397
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ymd = multiindex_year_month_day_dataframe_random_data
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df = ymd.copy()
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exp = ymd.copy()
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df.loc[2000, 4] = 0
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exp.loc[2000, 4].values[:] = 0
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tm.assert_frame_equal(df, exp)
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df["A"].loc[2000, 4] = 1
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exp["A"].loc[2000, 4].values[:] = 1
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tm.assert_frame_equal(df, exp)
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df.loc[2000] = 5
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exp.loc[2000].values[:] = 5
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tm.assert_frame_equal(df, exp)
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# this works...for now
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df["A"].iloc[14] = 5
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assert df["A"].iloc[14] == 5
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@pytest.mark.parametrize("dtype", [int, float])
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def test_getitem_intkey_leading_level(
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self, multiindex_year_month_day_dataframe_random_data, dtype
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):
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# GH#33355 dont fall-back to positional when leading level is int
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ymd = multiindex_year_month_day_dataframe_random_data
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levels = ymd.index.levels
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ymd.index = ymd.index.set_levels([levels[0].astype(dtype)] + levels[1:])
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ser = ymd["A"]
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mi = ser.index
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assert isinstance(mi, MultiIndex)
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if dtype is int:
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assert isinstance(mi.levels[0], Int64Index)
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else:
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assert isinstance(mi.levels[0], Float64Index)
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assert 14 not in mi.levels[0]
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assert not mi.levels[0]._should_fallback_to_positional()
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assert not mi._should_fallback_to_positional()
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with pytest.raises(KeyError, match="14"):
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ser[14]
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with pytest.raises(KeyError, match="14"):
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with tm.assert_produces_warning(FutureWarning):
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mi.get_value(ser, 14)
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# ---------------------------------------------------------------------
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# AMBIGUOUS CASES!
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def test_partial_loc_missing(self, multiindex_year_month_day_dataframe_random_data):
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pytest.skip("skipping for now")
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ymd = multiindex_year_month_day_dataframe_random_data
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result = ymd.loc[2000, 0]
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expected = ymd.loc[2000]["A"]
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tm.assert_series_equal(result, expected)
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# need to put in some work here
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# FIXME: dont leave commented-out
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# self.ymd.loc[2000, 0] = 0
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# assert (self.ymd.loc[2000]['A'] == 0).all()
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# Pretty sure the second (and maybe even the first) is already wrong.
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with pytest.raises(Exception):
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ymd.loc[(2000, 6)]
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with pytest.raises(Exception):
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ymd.loc[(2000, 6), 0]
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# ---------------------------------------------------------------------
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def test_setitem_multiple_partial(self, multiindex_dataframe_random_data):
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frame = multiindex_dataframe_random_data
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expected = frame.copy()
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result = frame.copy()
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result.loc[["foo", "bar"]] = 0
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expected.loc["foo"] = 0
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expected.loc["bar"] = 0
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tm.assert_frame_equal(result, expected)
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expected = frame.copy()
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result = frame.copy()
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result.loc["foo":"bar"] = 0
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expected.loc["foo"] = 0
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expected.loc["bar"] = 0
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tm.assert_frame_equal(result, expected)
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expected = frame["A"].copy()
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result = frame["A"].copy()
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result.loc[["foo", "bar"]] = 0
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expected.loc["foo"] = 0
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expected.loc["bar"] = 0
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tm.assert_series_equal(result, expected)
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expected = frame["A"].copy()
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result = frame["A"].copy()
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result.loc["foo":"bar"] = 0
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expected.loc["foo"] = 0
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expected.loc["bar"] = 0
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize(
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"indexer, exp_idx, exp_values",
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[
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(slice("2019-2", None), [to_datetime("2019-02-01")], [2, 3]),
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(
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slice(None, "2019-2"),
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date_range("2019", periods=2, freq="MS"),
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[0, 1, 2, 3],
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),
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],
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)
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def test_partial_getitem_loc_datetime(self, indexer, exp_idx, exp_values):
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# GH: 25165
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date_idx = date_range("2019", periods=2, freq="MS")
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df = DataFrame(
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list(range(4)),
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index=MultiIndex.from_product([date_idx, [0, 1]], names=["x", "y"]),
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)
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expected = DataFrame(
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exp_values,
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index=MultiIndex.from_product([exp_idx, [0, 1]], names=["x", "y"]),
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)
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result = df[indexer]
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tm.assert_frame_equal(result, expected)
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result = df.loc[indexer]
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tm.assert_frame_equal(result, expected)
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result = df.loc(axis=0)[indexer]
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tm.assert_frame_equal(result, expected)
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result = df.loc[indexer, :]
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tm.assert_frame_equal(result, expected)
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df2 = df.swaplevel(0, 1).sort_index()
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expected = expected.swaplevel(0, 1).sort_index()
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result = df2.loc[:, indexer, :]
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tm.assert_frame_equal(result, expected)
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def test_loc_getitem_partial_both_axis():
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# gh-12660
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iterables = [["a", "b"], [2, 1]]
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columns = MultiIndex.from_product(iterables, names=["col1", "col2"])
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rows = MultiIndex.from_product(iterables, names=["row1", "row2"])
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df = DataFrame(np.random.randn(4, 4), index=rows, columns=columns)
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expected = df.iloc[:2, 2:].droplevel("row1").droplevel("col1", axis=1)
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result = df.loc["a", "b"]
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tm.assert_frame_equal(result, expected)
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