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pandas / tests / indexing / multiindex / test_indexing_slow.py
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import warnings

import numpy as np
import pytest

import pandas as pd
from pandas import DataFrame, Series
import pandas._testing as tm

m = 50
n = 1000
cols = ["jim", "joe", "jolie", "joline", "jolia"]

vals = [
    np.random.randint(0, 10, n),
    np.random.choice(list("abcdefghij"), n),
    np.random.choice(pd.date_range("20141009", periods=10).tolist(), n),
    np.random.choice(list("ZYXWVUTSRQ"), n),
    np.random.randn(n),
]
vals = list(map(tuple, zip(*vals)))

# bunch of keys for testing
keys = [
    np.random.randint(0, 11, m),
    np.random.choice(list("abcdefghijk"), m),
    np.random.choice(pd.date_range("20141009", periods=11).tolist(), m),
    np.random.choice(list("ZYXWVUTSRQP"), m),
]
keys = list(map(tuple, zip(*keys)))
keys += list(map(lambda t: t[:-1], vals[:: n // m]))


# covers both unique index and non-unique index
df = DataFrame(vals, columns=cols)
a = pd.concat([df, df])
b = df.drop_duplicates(subset=cols[:-1])


@pytest.mark.filterwarnings("ignore::pandas.errors.PerformanceWarning")
@pytest.mark.parametrize("lexsort_depth", list(range(5)))
@pytest.mark.parametrize("key", keys)
@pytest.mark.parametrize("frame", [a, b])
def test_multiindex_get_loc(lexsort_depth, key, frame):
    # GH7724, GH2646

    with warnings.catch_warnings(record=True):

        # test indexing into a multi-index before & past the lexsort depth

        def validate(mi, df, key):
            mask = np.ones(len(df)).astype("bool")

            # test for all partials of this key
            for i, k in enumerate(key):
                mask &= df.iloc[:, i] == k

                if not mask.any():
                    assert key[: i + 1] not in mi.index
                    continue

                assert key[: i + 1] in mi.index
                right = df[mask].copy()

                if i + 1 != len(key):  # partial key
                    return_value = right.drop(cols[: i + 1], axis=1, inplace=True)
                    assert return_value is None
                    return_value = right.set_index(cols[i + 1 : -1], inplace=True)
                    assert return_value is None
                    tm.assert_frame_equal(mi.loc[key[: i + 1]], right)

                else:  # full key
                    return_value = right.set_index(cols[:-1], inplace=True)
                    assert return_value is None
                    if len(right) == 1:  # single hit
                        right = Series(
                            right["jolia"].values, name=right.index[0], index=["jolia"]
                        )
                        tm.assert_series_equal(mi.loc[key[: i + 1]], right)
                    else:  # multi hit
                        tm.assert_frame_equal(mi.loc[key[: i + 1]], right)

        if lexsort_depth == 0:
            df = frame.copy()
        else:
            df = frame.sort_values(by=cols[:lexsort_depth])

        mi = df.set_index(cols[:-1])
        assert not mi.index.lexsort_depth < lexsort_depth
        validate(mi, df, key)