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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IndexSlice,
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MultiIndex,
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date_range,
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)
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import pandas._testing as tm
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@pytest.fixture
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def df():
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# c1
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# 2016-01-01 00:00:00 a 0
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# b 1
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# c 2
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# 2016-01-01 12:00:00 a 3
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# b 4
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# c 5
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# 2016-01-02 00:00:00 a 6
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# b 7
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# c 8
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# 2016-01-02 12:00:00 a 9
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# b 10
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# c 11
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# 2016-01-03 00:00:00 a 12
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# b 13
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# c 14
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dr = date_range("2016-01-01", "2016-01-03", freq="12H")
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abc = ["a", "b", "c"]
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mi = MultiIndex.from_product([dr, abc])
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frame = DataFrame({"c1": range(0, 15)}, index=mi)
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return frame
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def test_partial_string_matching_single_index(df):
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# partial string matching on a single index
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for df_swap in [df.swaplevel(), df.swaplevel(0), df.swaplevel(0, 1)]:
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df_swap = df_swap.sort_index()
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just_a = df_swap.loc["a"]
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result = just_a.loc["2016-01-01"]
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expected = df.loc[IndexSlice[:, "a"], :].iloc[0:2]
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expected.index = expected.index.droplevel(1)
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tm.assert_frame_equal(result, expected)
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def test_get_loc_partial_timestamp_multiindex(df):
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mi = df.index
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key = ("2016-01-01", "a")
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loc = mi.get_loc(key)
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expected = np.zeros(len(mi), dtype=bool)
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expected[[0, 3]] = True
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tm.assert_numpy_array_equal(loc, expected)
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key2 = ("2016-01-02", "a")
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loc2 = mi.get_loc(key2)
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expected2 = np.zeros(len(mi), dtype=bool)
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expected2[[6, 9]] = True
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tm.assert_numpy_array_equal(loc2, expected2)
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key3 = ("2016-01", "a")
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loc3 = mi.get_loc(key3)
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expected3 = np.zeros(len(mi), dtype=bool)
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expected3[mi.get_level_values(1).get_loc("a")] = True
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tm.assert_numpy_array_equal(loc3, expected3)
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key4 = ("2016", "a")
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loc4 = mi.get_loc(key4)
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expected4 = expected3
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tm.assert_numpy_array_equal(loc4, expected4)
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# non-monotonic
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taker = np.arange(len(mi), dtype=np.intp)
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taker[::2] = taker[::-2]
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mi2 = mi.take(taker)
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loc5 = mi2.get_loc(key)
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expected5 = np.zeros(len(mi2), dtype=bool)
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expected5[[3, 14]] = True
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tm.assert_numpy_array_equal(loc5, expected5)
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def test_partial_string_timestamp_multiindex(df):
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# GH10331
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df_swap = df.swaplevel(0, 1).sort_index()
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SLC = IndexSlice
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# indexing with IndexSlice
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result = df.loc[SLC["2016-01-01":"2016-02-01", :], :]
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expected = df
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tm.assert_frame_equal(result, expected)
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# match on secondary index
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result = df_swap.loc[SLC[:, "2016-01-01":"2016-01-01"], :]
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expected = df_swap.iloc[[0, 1, 5, 6, 10, 11]]
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tm.assert_frame_equal(result, expected)
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# partial string match on year only
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result = df.loc["2016"]
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expected = df
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tm.assert_frame_equal(result, expected)
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# partial string match on date
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result = df.loc["2016-01-01"]
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expected = df.iloc[0:6]
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tm.assert_frame_equal(result, expected)
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# partial string match on date and hour, from middle
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result = df.loc["2016-01-02 12"]
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# hourly resolution, same as index.levels[0], so we are _not_ slicing on
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# that level, so that level gets dropped
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expected = df.iloc[9:12].droplevel(0)
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tm.assert_frame_equal(result, expected)
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# partial string match on secondary index
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result = df_swap.loc[SLC[:, "2016-01-02"], :]
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expected = df_swap.iloc[[2, 3, 7, 8, 12, 13]]
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tm.assert_frame_equal(result, expected)
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# tuple selector with partial string match on date
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# "2016-01-01" has daily resolution, so _is_ a slice on the first level.
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result = df.loc[("2016-01-01", "a"), :]
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expected = df.iloc[[0, 3]]
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expected = df.iloc[[0, 3]].droplevel(1)
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tm.assert_frame_equal(result, expected)
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# Slicing date on first level should break (of course) bc the DTI is the
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# second level on df_swap
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with pytest.raises(KeyError, match="'2016-01-01'"):
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df_swap.loc["2016-01-01"]
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def test_partial_string_timestamp_multiindex_str_key_raises(df):
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# Even though this syntax works on a single index, this is somewhat
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# ambiguous and we don't want to extend this behavior forward to work
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# in multi-indexes. This would amount to selecting a scalar from a
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# column.
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with pytest.raises(KeyError, match="'2016-01-01'"):
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df["2016-01-01"]
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def test_partial_string_timestamp_multiindex_daily_resolution(df):
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# GH12685 (partial string with daily resolution or below)
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result = df.loc[IndexSlice["2013-03":"2013-03", :], :]
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expected = df.iloc[118:180]
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tm.assert_frame_equal(result, expected)
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