craftbeerpi4-pione/venv3/lib/python3.7/site-packages/pandas/tests/generic/test_series.py
2021-03-03 23:49:41 +01:00

181 lines
5.8 KiB
Python

from operator import methodcaller
import numpy as np
import pytest
import pandas as pd
from pandas import MultiIndex, Series, date_range
import pandas._testing as tm
from .test_generic import Generic
class TestSeries(Generic):
_typ = Series
_comparator = lambda self, x, y: tm.assert_series_equal(x, y)
def test_rename_mi(self):
s = Series(
[11, 21, 31],
index=MultiIndex.from_tuples([("A", x) for x in ["a", "B", "c"]]),
)
s.rename(str.lower)
@pytest.mark.parametrize("func", ["rename_axis", "_set_axis_name"])
def test_set_axis_name_mi(self, func):
s = Series(
[11, 21, 31],
index=MultiIndex.from_tuples(
[("A", x) for x in ["a", "B", "c"]], names=["l1", "l2"]
),
)
result = methodcaller(func, ["L1", "L2"])(s)
assert s.index.name is None
assert s.index.names == ["l1", "l2"]
assert result.index.name is None
assert result.index.names, ["L1", "L2"]
def test_set_axis_name_raises(self):
s = pd.Series([1])
msg = "No axis named 1 for object type Series"
with pytest.raises(ValueError, match=msg):
s._set_axis_name(name="a", axis=1)
def test_get_numeric_data_preserve_dtype(self):
# get the numeric data
o = Series([1, 2, 3])
result = o._get_numeric_data()
self._compare(result, o)
o = Series([1, "2", 3.0])
result = o._get_numeric_data()
expected = Series([], dtype=object, index=pd.Index([], dtype=object))
self._compare(result, expected)
o = Series([True, False, True])
result = o._get_numeric_data()
self._compare(result, o)
o = Series([True, False, True])
result = o._get_bool_data()
self._compare(result, o)
o = Series(date_range("20130101", periods=3))
result = o._get_numeric_data()
expected = Series([], dtype="M8[ns]", index=pd.Index([], dtype=object))
self._compare(result, expected)
def test_nonzero_single_element(self):
# allow single item via bool method
s = Series([True])
assert s.bool()
s = Series([False])
assert not s.bool()
msg = "The truth value of a Series is ambiguous"
# single item nan to raise
for s in [Series([np.nan]), Series([pd.NaT]), Series([True]), Series([False])]:
with pytest.raises(ValueError, match=msg):
bool(s)
msg = "bool cannot act on a non-boolean single element Series"
for s in [Series([np.nan]), Series([pd.NaT])]:
with pytest.raises(ValueError, match=msg):
s.bool()
# multiple bool are still an error
msg = "The truth value of a Series is ambiguous"
for s in [Series([True, True]), Series([False, False])]:
with pytest.raises(ValueError, match=msg):
bool(s)
with pytest.raises(ValueError, match=msg):
s.bool()
# single non-bool are an error
for s in [Series([1]), Series([0]), Series(["a"]), Series([0.0])]:
msg = "The truth value of a Series is ambiguous"
with pytest.raises(ValueError, match=msg):
bool(s)
msg = "bool cannot act on a non-boolean single element Series"
with pytest.raises(ValueError, match=msg):
s.bool()
def test_metadata_propagation_indiv(self):
# check that the metadata matches up on the resulting ops
o = Series(range(3), range(3))
o.name = "foo"
o2 = Series(range(3), range(3))
o2.name = "bar"
result = o.T
self.check_metadata(o, result)
# resample
ts = Series(
np.random.rand(1000),
index=date_range("20130101", periods=1000, freq="s"),
name="foo",
)
result = ts.resample("1T").mean()
self.check_metadata(ts, result)
result = ts.resample("1T").min()
self.check_metadata(ts, result)
result = ts.resample("1T").apply(lambda x: x.sum())
self.check_metadata(ts, result)
_metadata = Series._metadata
_finalize = Series.__finalize__
Series._metadata = ["name", "filename"]
o.filename = "foo"
o2.filename = "bar"
def finalize(self, other, method=None, **kwargs):
for name in self._metadata:
if method == "concat" and name == "filename":
value = "+".join(
[getattr(o, name) for o in other.objs if getattr(o, name, None)]
)
object.__setattr__(self, name, value)
else:
object.__setattr__(self, name, getattr(other, name, None))
return self
Series.__finalize__ = finalize
result = pd.concat([o, o2])
assert result.filename == "foo+bar"
assert result.name is None
# reset
Series._metadata = _metadata
Series.__finalize__ = _finalize # FIXME: use monkeypatch
class TestSeries2:
# Separating off because it doesnt rely on parent class
@pytest.mark.parametrize(
"s",
[
Series([np.arange(5)]),
pd.date_range("1/1/2011", periods=24, freq="H"),
pd.Series(range(5), index=pd.date_range("2017", periods=5)),
],
)
@pytest.mark.parametrize("shift_size", [0, 1, 2])
def test_shift_always_copy(self, s, shift_size):
# GH22397
assert s.shift(shift_size) is not s
@pytest.mark.parametrize("move_by_freq", [pd.Timedelta("1D"), pd.Timedelta("1M")])
def test_datetime_shift_always_copy(self, move_by_freq):
# GH22397
s = pd.Series(range(5), index=pd.date_range("2017", periods=5))
assert s.shift(freq=move_by_freq) is not s