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import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
Index,
MultiIndex,
Series,
date_range,
)
import pandas._testing as tm
def test_unstack_preserves_object():
mi = MultiIndex.from_product([["bar", "foo"], ["one", "two"]])
ser = Series(np.arange(4.0), index=mi, dtype=object)
res1 = ser.unstack()
assert (res1.dtypes == object).all()
res2 = ser.unstack(level=0)
assert (res2.dtypes == object).all()
def test_unstack():
index = MultiIndex(
levels=[["bar", "foo"], ["one", "three", "two"]],
codes=[[1, 1, 0, 0], [0, 1, 0, 2]],
)
s = Series(np.arange(4.0), index=index)
unstacked = s.unstack()
expected = DataFrame(
[[2.0, np.nan, 3.0], [0.0, 1.0, np.nan]],
index=["bar", "foo"],
columns=["one", "three", "two"],
)
tm.assert_frame_equal(unstacked, expected)
unstacked = s.unstack(level=0)
tm.assert_frame_equal(unstacked, expected.T)
index = MultiIndex(
levels=[["bar"], ["one", "two", "three"], [0, 1]],
codes=[[0, 0, 0, 0, 0, 0], [0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]],
)
s = Series(np.random.default_rng(2).standard_normal(6), index=index)
exp_index = MultiIndex(
levels=[["one", "two", "three"], [0, 1]],
codes=[[0, 1, 2, 0, 1, 2], [0, 1, 0, 1, 0, 1]],
)
expected = DataFrame({"bar": s.values}, index=exp_index).sort_index(level=0)
unstacked = s.unstack(0).sort_index()
tm.assert_frame_equal(unstacked, expected)
# GH5873
idx = MultiIndex.from_arrays([[101, 102], [3.5, np.nan]])
ts = Series([1, 2], index=idx)
left = ts.unstack()
right = DataFrame(
[[np.nan, 1], [2, np.nan]], index=[101, 102], columns=[np.nan, 3.5]
)
tm.assert_frame_equal(left, right)
idx = MultiIndex.from_arrays(
[
["cat", "cat", "cat", "dog", "dog"],
["a", "a", "b", "a", "b"],
[1, 2, 1, 1, np.nan],
]
)
ts = Series([1.0, 1.1, 1.2, 1.3, 1.4], index=idx)
right = DataFrame(
[[1.0, 1.3], [1.1, np.nan], [np.nan, 1.4], [1.2, np.nan]],
columns=["cat", "dog"],
)
tpls = [("a", 1), ("a", 2), ("b", np.nan), ("b", 1)]
right.index = MultiIndex.from_tuples(tpls)
tm.assert_frame_equal(ts.unstack(level=0), right)
def test_unstack_tuplename_in_multiindex():
# GH 19966
idx = MultiIndex.from_product(
[["a", "b", "c"], [1, 2, 3]], names=[("A", "a"), ("B", "b")]
)
ser = Series(1, index=idx)
result = ser.unstack(("A", "a"))
expected = DataFrame(
[[1, 1, 1], [1, 1, 1], [1, 1, 1]],
columns=MultiIndex.from_tuples([("a",), ("b",), ("c",)], names=[("A", "a")]),
index=Index([1, 2, 3], name=("B", "b")),
)
tm.assert_frame_equal(result, expected)
@pytest.mark.parametrize(
"unstack_idx, expected_values, expected_index, expected_columns",
[
(
("A", "a"),
[[1, 1], [1, 1], [1, 1], [1, 1]],
MultiIndex.from_tuples([(1, 3), (1, 4), (2, 3), (2, 4)], names=["B", "C"]),
MultiIndex.from_tuples([("a",), ("b",)], names=[("A", "a")]),
),
(
(("A", "a"), "B"),
[[1, 1, 1, 1], [1, 1, 1, 1]],
Index([3, 4], name="C"),
MultiIndex.from_tuples(
[("a", 1), ("a", 2), ("b", 1), ("b", 2)], names=[("A", "a"), "B"]
),
),
],
)
def test_unstack_mixed_type_name_in_multiindex(
unstack_idx, expected_values, expected_index, expected_columns
):
# GH 19966
idx = MultiIndex.from_product(
[["a", "b"], [1, 2], [3, 4]], names=[("A", "a"), "B", "C"]
)
ser = Series(1, index=idx)
result = ser.unstack(unstack_idx)
expected = DataFrame(
expected_values, columns=expected_columns, index=expected_index
)
tm.assert_frame_equal(result, expected)
def test_unstack_multi_index_categorical_values():
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD"), dtype=object),
index=date_range("2000-01-01", periods=10, freq="B"),
)
mi = df.stack(future_stack=True).index.rename(["major", "minor"])
ser = Series(["foo"] * len(mi), index=mi, name="category", dtype="category")
result = ser.unstack()
dti = ser.index.levels[0]
c = pd.Categorical(["foo"] * len(dti))
expected = DataFrame(
{"A": c.copy(), "B": c.copy(), "C": c.copy(), "D": c.copy()},
columns=Index(list("ABCD"), name="minor"),
index=dti.rename("major"),
)
tm.assert_frame_equal(result, expected)
def test_unstack_mixed_level_names():
# GH#48763
arrays = [["a", "a"], [1, 2], ["red", "blue"]]
idx = MultiIndex.from_arrays(arrays, names=("x", 0, "y"))
ser = Series([1, 2], index=idx)
result = ser.unstack("x")
expected = DataFrame(
[[1], [2]],
columns=Index(["a"], name="x"),
index=MultiIndex.from_tuples([(1, "red"), (2, "blue")], names=[0, "y"]),
)
tm.assert_frame_equal(result, expected)