162 lines
5.3 KiB
Python
162 lines
5.3 KiB
Python
|
import numpy as np
|
||
|
import pytest
|
||
|
|
||
|
import pandas as pd
|
||
|
from pandas import (
|
||
|
Index,
|
||
|
MultiIndex,
|
||
|
)
|
||
|
import pandas._testing as tm
|
||
|
|
||
|
|
||
|
def test_reindex(idx):
|
||
|
result, indexer = idx.reindex(list(idx[:4]))
|
||
|
assert isinstance(result, MultiIndex)
|
||
|
assert result.names == ["first", "second"]
|
||
|
assert [level.name for level in result.levels] == ["first", "second"]
|
||
|
|
||
|
result, indexer = idx.reindex(list(idx))
|
||
|
assert isinstance(result, MultiIndex)
|
||
|
assert indexer is None
|
||
|
assert result.names == ["first", "second"]
|
||
|
assert [level.name for level in result.levels] == ["first", "second"]
|
||
|
|
||
|
|
||
|
def test_reindex_level(idx):
|
||
|
index = Index(["one"])
|
||
|
|
||
|
target, indexer = idx.reindex(index, level="second")
|
||
|
target2, indexer2 = index.reindex(idx, level="second")
|
||
|
|
||
|
exp_index = idx.join(index, level="second", how="right")
|
||
|
exp_index2 = idx.join(index, level="second", how="left")
|
||
|
|
||
|
assert target.equals(exp_index)
|
||
|
exp_indexer = np.array([0, 2, 4])
|
||
|
tm.assert_numpy_array_equal(indexer, exp_indexer, check_dtype=False)
|
||
|
|
||
|
assert target2.equals(exp_index2)
|
||
|
exp_indexer2 = np.array([0, -1, 0, -1, 0, -1])
|
||
|
tm.assert_numpy_array_equal(indexer2, exp_indexer2, check_dtype=False)
|
||
|
|
||
|
with pytest.raises(TypeError, match="Fill method not supported"):
|
||
|
idx.reindex(idx, method="pad", level="second")
|
||
|
|
||
|
|
||
|
def test_reindex_preserves_names_when_target_is_list_or_ndarray(idx):
|
||
|
# GH6552
|
||
|
idx = idx.copy()
|
||
|
target = idx.copy()
|
||
|
idx.names = target.names = [None, None]
|
||
|
|
||
|
other_dtype = MultiIndex.from_product([[1, 2], [3, 4]])
|
||
|
|
||
|
# list & ndarray cases
|
||
|
assert idx.reindex([])[0].names == [None, None]
|
||
|
assert idx.reindex(np.array([]))[0].names == [None, None]
|
||
|
assert idx.reindex(target.tolist())[0].names == [None, None]
|
||
|
assert idx.reindex(target.values)[0].names == [None, None]
|
||
|
assert idx.reindex(other_dtype.tolist())[0].names == [None, None]
|
||
|
assert idx.reindex(other_dtype.values)[0].names == [None, None]
|
||
|
|
||
|
idx.names = ["foo", "bar"]
|
||
|
assert idx.reindex([])[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex(np.array([]))[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex(target.tolist())[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex(target.values)[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex(other_dtype.tolist())[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex(other_dtype.values)[0].names == ["foo", "bar"]
|
||
|
|
||
|
|
||
|
def test_reindex_lvl_preserves_names_when_target_is_list_or_array():
|
||
|
# GH7774
|
||
|
idx = MultiIndex.from_product([[0, 1], ["a", "b"]], names=["foo", "bar"])
|
||
|
assert idx.reindex([], level=0)[0].names == ["foo", "bar"]
|
||
|
assert idx.reindex([], level=1)[0].names == ["foo", "bar"]
|
||
|
|
||
|
|
||
|
def test_reindex_lvl_preserves_type_if_target_is_empty_list_or_array():
|
||
|
# GH7774
|
||
|
idx = MultiIndex.from_product([[0, 1], ["a", "b"]])
|
||
|
assert idx.reindex([], level=0)[0].levels[0].dtype.type == np.int64
|
||
|
assert idx.reindex([], level=1)[0].levels[1].dtype.type == np.object_
|
||
|
|
||
|
# case with EA levels
|
||
|
cat = pd.Categorical(["foo", "bar"])
|
||
|
dti = pd.date_range("2016-01-01", periods=2, tz="US/Pacific")
|
||
|
mi = MultiIndex.from_product([cat, dti])
|
||
|
assert mi.reindex([], level=0)[0].levels[0].dtype == cat.dtype
|
||
|
assert mi.reindex([], level=1)[0].levels[1].dtype == dti.dtype
|
||
|
|
||
|
|
||
|
def test_reindex_base(idx):
|
||
|
idx = idx
|
||
|
expected = np.arange(idx.size, dtype=np.intp)
|
||
|
|
||
|
actual = idx.get_indexer(idx)
|
||
|
tm.assert_numpy_array_equal(expected, actual)
|
||
|
|
||
|
with pytest.raises(ValueError, match="Invalid fill method"):
|
||
|
idx.get_indexer(idx, method="invalid")
|
||
|
|
||
|
|
||
|
def test_reindex_non_unique():
|
||
|
idx = MultiIndex.from_tuples([(0, 0), (1, 1), (1, 1), (2, 2)])
|
||
|
a = pd.Series(np.arange(4), index=idx)
|
||
|
new_idx = MultiIndex.from_tuples([(0, 0), (1, 1), (2, 2)])
|
||
|
|
||
|
msg = "cannot handle a non-unique multi-index!"
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
with tm.assert_produces_warning(FutureWarning, match="non-unique"):
|
||
|
a.reindex(new_idx)
|
||
|
|
||
|
|
||
|
@pytest.mark.parametrize("values", [[["a"], ["x"]], [[], []]])
|
||
|
def test_reindex_empty_with_level(values):
|
||
|
# GH41170
|
||
|
idx = MultiIndex.from_arrays(values)
|
||
|
result, result_indexer = idx.reindex(np.array(["b"]), level=0)
|
||
|
expected = MultiIndex(levels=[["b"], values[1]], codes=[[], []])
|
||
|
expected_indexer = np.array([], dtype=result_indexer.dtype)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
tm.assert_numpy_array_equal(result_indexer, expected_indexer)
|
||
|
|
||
|
|
||
|
def test_reindex_not_all_tuples():
|
||
|
keys = [("i", "i"), ("i", "j"), ("j", "i"), "j"]
|
||
|
mi = MultiIndex.from_tuples(keys[:-1])
|
||
|
idx = Index(keys)
|
||
|
res, indexer = mi.reindex(idx)
|
||
|
|
||
|
tm.assert_index_equal(res, idx)
|
||
|
expected = np.array([0, 1, 2, -1], dtype=np.intp)
|
||
|
tm.assert_numpy_array_equal(indexer, expected)
|
||
|
|
||
|
|
||
|
def test_reindex_limit_arg_with_multiindex():
|
||
|
# GH21247
|
||
|
|
||
|
idx = MultiIndex.from_tuples([(3, "A"), (4, "A"), (4, "B")])
|
||
|
|
||
|
df = pd.Series([0.02, 0.01, 0.012], index=idx)
|
||
|
|
||
|
new_idx = MultiIndex.from_tuples(
|
||
|
[
|
||
|
(3, "A"),
|
||
|
(3, "B"),
|
||
|
(4, "A"),
|
||
|
(4, "B"),
|
||
|
(4, "C"),
|
||
|
(5, "B"),
|
||
|
(5, "C"),
|
||
|
(6, "B"),
|
||
|
(6, "C"),
|
||
|
]
|
||
|
)
|
||
|
|
||
|
with pytest.raises(
|
||
|
ValueError,
|
||
|
match="limit argument only valid if doing pad, backfill or nearest reindexing",
|
||
|
):
|
||
|
df.reindex(new_idx, fill_value=0, limit=1)
|