Inzynierka/Lib/site-packages/pandas/tests/series/methods/test_reset_index.py
2023-06-02 12:51:02 +02:00

197 lines
6.6 KiB
Python

from datetime import datetime
import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
Index,
MultiIndex,
RangeIndex,
Series,
date_range,
)
import pandas._testing as tm
class TestResetIndex:
def test_reset_index_dti_round_trip(self):
dti = date_range(start="1/1/2001", end="6/1/2001", freq="D")._with_freq(None)
d1 = DataFrame({"v": np.random.rand(len(dti))}, index=dti)
d2 = d1.reset_index()
assert d2.dtypes[0] == np.dtype("M8[ns]")
d3 = d2.set_index("index")
tm.assert_frame_equal(d1, d3, check_names=False)
# GH#2329
stamp = datetime(2012, 11, 22)
df = DataFrame([[stamp, 12.1]], columns=["Date", "Value"])
df = df.set_index("Date")
assert df.index[0] == stamp
assert df.reset_index()["Date"][0] == stamp
def test_reset_index(self):
df = tm.makeDataFrame()[:5]
ser = df.stack()
ser.index.names = ["hash", "category"]
ser.name = "value"
df = ser.reset_index()
assert "value" in df
df = ser.reset_index(name="value2")
assert "value2" in df
# check inplace
s = ser.reset_index(drop=True)
s2 = ser
return_value = s2.reset_index(drop=True, inplace=True)
assert return_value is None
tm.assert_series_equal(s, s2)
# level
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.randn(6), index=index)
rs = s.reset_index(level=1)
assert len(rs.columns) == 2
rs = s.reset_index(level=[0, 2], drop=True)
tm.assert_index_equal(rs.index, Index(index.get_level_values(1)))
assert isinstance(rs, Series)
def test_reset_index_name(self):
s = Series([1, 2, 3], index=Index(range(3), name="x"))
assert s.reset_index().index.name is None
assert s.reset_index(drop=True).index.name is None
def test_reset_index_level(self):
df = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"])
for levels in ["A", "B"], [0, 1]:
# With MultiIndex
s = df.set_index(["A", "B"])["C"]
result = s.reset_index(level=levels[0])
tm.assert_frame_equal(result, df.set_index("B"))
result = s.reset_index(level=levels[:1])
tm.assert_frame_equal(result, df.set_index("B"))
result = s.reset_index(level=levels)
tm.assert_frame_equal(result, df)
result = df.set_index(["A", "B"]).reset_index(level=levels, drop=True)
tm.assert_frame_equal(result, df[["C"]])
with pytest.raises(KeyError, match="Level E "):
s.reset_index(level=["A", "E"])
# With single-level Index
s = df.set_index("A")["B"]
result = s.reset_index(level=levels[0])
tm.assert_frame_equal(result, df[["A", "B"]])
result = s.reset_index(level=levels[:1])
tm.assert_frame_equal(result, df[["A", "B"]])
result = s.reset_index(level=levels[0], drop=True)
tm.assert_series_equal(result, df["B"])
with pytest.raises(IndexError, match="Too many levels"):
s.reset_index(level=[0, 1, 2])
# Check that .reset_index([],drop=True) doesn't fail
result = Series(range(4)).reset_index([], drop=True)
expected = Series(range(4))
tm.assert_series_equal(result, expected)
def test_reset_index_range(self):
# GH 12071
s = Series(range(2), name="A", dtype="int64")
series_result = s.reset_index()
assert isinstance(series_result.index, RangeIndex)
series_expected = DataFrame(
[[0, 0], [1, 1]], columns=["index", "A"], index=RangeIndex(stop=2)
)
tm.assert_frame_equal(series_result, series_expected)
def test_reset_index_drop_errors(self):
# GH 20925
# KeyError raised for series index when passed level name is missing
s = Series(range(4))
with pytest.raises(KeyError, match="does not match index name"):
s.reset_index("wrong", drop=True)
with pytest.raises(KeyError, match="does not match index name"):
s.reset_index("wrong")
# KeyError raised for series when level to be dropped is missing
s = Series(range(4), index=MultiIndex.from_product([[1, 2]] * 2))
with pytest.raises(KeyError, match="not found"):
s.reset_index("wrong", drop=True)
def test_reset_index_with_drop(self, series_with_multilevel_index):
ser = series_with_multilevel_index
deleveled = ser.reset_index()
assert isinstance(deleveled, DataFrame)
assert len(deleveled.columns) == len(ser.index.levels) + 1
assert deleveled.index.name == ser.index.name
deleveled = ser.reset_index(drop=True)
assert isinstance(deleveled, Series)
assert deleveled.index.name == ser.index.name
def test_reset_index_inplace_and_drop_ignore_name(self):
# GH#44575
ser = Series(range(2), name="old")
ser.reset_index(name="new", drop=True, inplace=True)
expected = Series(range(2), name="old")
tm.assert_series_equal(ser, expected)
@pytest.mark.parametrize(
"array, dtype",
[
(["a", "b"], object),
(
pd.period_range("12-1-2000", periods=2, freq="Q-DEC"),
pd.PeriodDtype(freq="Q-DEC"),
),
],
)
def test_reset_index_dtypes_on_empty_series_with_multiindex(array, dtype):
# GH 19602 - Preserve dtype on empty Series with MultiIndex
idx = MultiIndex.from_product([[0, 1], [0.5, 1.0], array])
result = Series(dtype=object, index=idx)[:0].reset_index().dtypes
expected = Series(
{"level_0": np.int64, "level_1": np.float64, "level_2": dtype, 0: object}
)
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize(
"names, expected_names",
[
(["A", "A"], ["A", "A"]),
(["level_1", None], ["level_1", "level_1"]),
],
)
@pytest.mark.parametrize("allow_duplicates", [False, True])
def test_column_name_duplicates(names, expected_names, allow_duplicates):
# GH#44755 reset_index with duplicate column labels
s = Series([1], index=MultiIndex.from_arrays([[1], [1]], names=names))
if allow_duplicates:
result = s.reset_index(allow_duplicates=True)
expected = DataFrame([[1, 1, 1]], columns=expected_names + [0])
tm.assert_frame_equal(result, expected)
else:
with pytest.raises(ValueError, match="cannot insert"):
s.reset_index()