230 lines
7.4 KiB
Python
230 lines
7.4 KiB
Python
import numpy as np
|
|
import pytest
|
|
|
|
import pandas._libs.index as _index
|
|
from pandas.errors import PerformanceWarning
|
|
|
|
import pandas as pd
|
|
from pandas import (
|
|
DataFrame,
|
|
Index,
|
|
MultiIndex,
|
|
Series,
|
|
)
|
|
import pandas._testing as tm
|
|
|
|
|
|
class TestMultiIndexBasic:
|
|
def test_multiindex_perf_warn(self):
|
|
df = DataFrame(
|
|
{
|
|
"jim": [0, 0, 1, 1],
|
|
"joe": ["x", "x", "z", "y"],
|
|
"jolie": np.random.rand(4),
|
|
}
|
|
).set_index(["jim", "joe"])
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
df.loc[(1, "z")]
|
|
|
|
df = df.iloc[[2, 1, 3, 0]]
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
df.loc[(0,)]
|
|
|
|
def test_indexing_over_hashtable_size_cutoff(self):
|
|
n = 10000
|
|
|
|
old_cutoff = _index._SIZE_CUTOFF
|
|
_index._SIZE_CUTOFF = 20000
|
|
|
|
s = Series(np.arange(n), MultiIndex.from_arrays((["a"] * n, np.arange(n))))
|
|
|
|
# hai it works!
|
|
assert s[("a", 5)] == 5
|
|
assert s[("a", 6)] == 6
|
|
assert s[("a", 7)] == 7
|
|
|
|
_index._SIZE_CUTOFF = old_cutoff
|
|
|
|
def test_multi_nan_indexing(self):
|
|
# GH 3588
|
|
df = DataFrame(
|
|
{
|
|
"a": ["R1", "R2", np.nan, "R4"],
|
|
"b": ["C1", "C2", "C3", "C4"],
|
|
"c": [10, 15, np.nan, 20],
|
|
}
|
|
)
|
|
result = df.set_index(["a", "b"], drop=False)
|
|
expected = DataFrame(
|
|
{
|
|
"a": ["R1", "R2", np.nan, "R4"],
|
|
"b": ["C1", "C2", "C3", "C4"],
|
|
"c": [10, 15, np.nan, 20],
|
|
},
|
|
index=[
|
|
Index(["R1", "R2", np.nan, "R4"], name="a"),
|
|
Index(["C1", "C2", "C3", "C4"], name="b"),
|
|
],
|
|
)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_exclusive_nat_column_indexing(self):
|
|
# GH 38025
|
|
# test multi indexing when one column exclusively contains NaT values
|
|
df = DataFrame(
|
|
{
|
|
"a": [pd.NaT, pd.NaT, pd.NaT, pd.NaT],
|
|
"b": ["C1", "C2", "C3", "C4"],
|
|
"c": [10, 15, np.nan, 20],
|
|
}
|
|
)
|
|
df = df.set_index(["a", "b"])
|
|
expected = DataFrame(
|
|
{
|
|
"c": [10, 15, np.nan, 20],
|
|
},
|
|
index=[
|
|
Index([pd.NaT, pd.NaT, pd.NaT, pd.NaT], name="a"),
|
|
Index(["C1", "C2", "C3", "C4"], name="b"),
|
|
],
|
|
)
|
|
tm.assert_frame_equal(df, expected)
|
|
|
|
def test_nested_tuples_duplicates(self):
|
|
# GH#30892
|
|
|
|
dti = pd.to_datetime(["20190101", "20190101", "20190102"])
|
|
idx = Index(["a", "a", "c"])
|
|
mi = MultiIndex.from_arrays([dti, idx], names=["index1", "index2"])
|
|
|
|
df = DataFrame({"c1": [1, 2, 3], "c2": [np.nan, np.nan, np.nan]}, index=mi)
|
|
|
|
expected = DataFrame({"c1": df["c1"], "c2": [1.0, 1.0, np.nan]}, index=mi)
|
|
|
|
df2 = df.copy(deep=True)
|
|
df2.loc[(dti[0], "a"), "c2"] = 1.0
|
|
tm.assert_frame_equal(df2, expected)
|
|
|
|
df3 = df.copy(deep=True)
|
|
df3.loc[[(dti[0], "a")], "c2"] = 1.0
|
|
tm.assert_frame_equal(df3, expected)
|
|
|
|
def test_multiindex_with_datatime_level_preserves_freq(self):
|
|
# https://github.com/pandas-dev/pandas/issues/35563
|
|
idx = Index(range(2), name="A")
|
|
dti = pd.date_range("2020-01-01", periods=7, freq="D", name="B")
|
|
mi = MultiIndex.from_product([idx, dti])
|
|
df = DataFrame(np.random.randn(14, 2), index=mi)
|
|
result = df.loc[0].index
|
|
tm.assert_index_equal(result, dti)
|
|
assert result.freq == dti.freq
|
|
|
|
def test_multiindex_complex(self):
|
|
# GH#42145
|
|
complex_data = [1 + 2j, 4 - 3j, 10 - 1j]
|
|
non_complex_data = [3, 4, 5]
|
|
result = DataFrame(
|
|
{
|
|
"x": complex_data,
|
|
"y": non_complex_data,
|
|
"z": non_complex_data,
|
|
}
|
|
)
|
|
result.set_index(["x", "y"], inplace=True)
|
|
expected = DataFrame(
|
|
{"z": non_complex_data},
|
|
index=MultiIndex.from_arrays(
|
|
[complex_data, non_complex_data],
|
|
names=("x", "y"),
|
|
),
|
|
)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_rename_multiindex_with_duplicates(self):
|
|
# GH 38015
|
|
mi = MultiIndex.from_tuples([("A", "cat"), ("B", "cat"), ("B", "cat")])
|
|
df = DataFrame(index=mi)
|
|
df = df.rename(index={"A": "Apple"}, level=0)
|
|
|
|
mi2 = MultiIndex.from_tuples([("Apple", "cat"), ("B", "cat"), ("B", "cat")])
|
|
expected = DataFrame(index=mi2)
|
|
tm.assert_frame_equal(df, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"data_result, data_expected",
|
|
[
|
|
(
|
|
[
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[(np.nan, np.nan), (82.0, np.nan)],
|
|
[1, 2],
|
|
[1, 2],
|
|
],
|
|
[
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[1, 2],
|
|
[1, 1],
|
|
],
|
|
),
|
|
(
|
|
[
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[(np.nan, np.nan), (81.0, np.nan)],
|
|
[1, 2],
|
|
[1, 2],
|
|
],
|
|
[
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[(81.0, np.nan), (np.nan, np.nan)],
|
|
[1, 2],
|
|
[2, 1],
|
|
],
|
|
),
|
|
],
|
|
)
|
|
def test_subtracting_two_series_with_unordered_index_and_all_nan_index(
|
|
self, data_result, data_expected
|
|
):
|
|
# GH 38439
|
|
a_index_result = MultiIndex.from_tuples(data_result[0])
|
|
b_index_result = MultiIndex.from_tuples(data_result[1])
|
|
a_series_result = Series(data_result[2], index=a_index_result)
|
|
b_series_result = Series(data_result[3], index=b_index_result)
|
|
result = a_series_result.align(b_series_result)
|
|
|
|
a_index_expected = MultiIndex.from_tuples(data_expected[0])
|
|
b_index_expected = MultiIndex.from_tuples(data_expected[1])
|
|
a_series_expected = Series(data_expected[2], index=a_index_expected)
|
|
b_series_expected = Series(data_expected[3], index=b_index_expected)
|
|
a_series_expected.index = a_series_expected.index.set_levels(
|
|
[
|
|
a_series_expected.index.levels[0].astype("float"),
|
|
a_series_expected.index.levels[1].astype("float"),
|
|
]
|
|
)
|
|
b_series_expected.index = b_series_expected.index.set_levels(
|
|
[
|
|
b_series_expected.index.levels[0].astype("float"),
|
|
b_series_expected.index.levels[1].astype("float"),
|
|
]
|
|
)
|
|
|
|
tm.assert_series_equal(result[0], a_series_expected)
|
|
tm.assert_series_equal(result[1], b_series_expected)
|
|
|
|
def test_nunique_smoke(self):
|
|
# GH 34019
|
|
n = DataFrame([[1, 2], [1, 2]]).set_index([0, 1]).index.nunique()
|
|
assert n == 1
|
|
|
|
def test_multiindex_repeated_keys(self):
|
|
# GH19414
|
|
tm.assert_series_equal(
|
|
Series([1, 2], MultiIndex.from_arrays([["a", "b"]])).loc[
|
|
["a", "a", "b", "b"]
|
|
],
|
|
Series([1, 1, 2, 2], MultiIndex.from_arrays([["a", "a", "b", "b"]])),
|
|
)
|