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# -*- coding: utf-8 -*-
# pylint: disable-msg=E1101,W0612
from distutils.version import LooseVersion
from operator import methodcaller
import numpy as np
import pytest
from pandas.compat import range
import pandas.util._test_decorators as td
import pandas as pd
from pandas import MultiIndex, Series, date_range
import pandas.util.testing as tm
from pandas.util.testing import assert_almost_equal, assert_series_equal
from .test_generic import Generic
try:
import xarray
_XARRAY_INSTALLED = True
except ImportError:
_XARRAY_INSTALLED = False
class TestSeries(Generic):
_typ = Series
_comparator = lambda self, x, y: assert_series_equal(x, y)
def setup_method(self):
self.ts = tm.makeTimeSeries() # Was at top level in test_series
self.ts.name = 'ts'
self.series = tm.makeStringSeries()
self.series.name = 'series'
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)
def test_set_axis_name(self):
s = Series([1, 2, 3], index=['a', 'b', 'c'])
funcs = ['rename_axis', '_set_axis_name']
name = 'foo'
for func in funcs:
result = methodcaller(func, name)(s)
assert s.index.name is None
assert result.index.name == name
def test_set_axis_name_mi(self):
s = Series([11, 21, 31], index=MultiIndex.from_tuples(
[("A", x) for x in ["a", "B", "c"]],
names=['l1', 'l2'])
)
funcs = ['rename_axis', '_set_axis_name']
for func in funcs:
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])
with pytest.raises(ValueError):
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.])
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()
# single item nan to raise
for s in [Series([np.nan]), Series([pd.NaT]), Series([True]),
Series([False])]:
pytest.raises(ValueError, lambda: bool(s))
for s in [Series([np.nan]), Series([pd.NaT])]:
pytest.raises(ValueError, lambda: s.bool())
# multiple bool are still an error
for s in [Series([True, True]), Series([False, False])]:
pytest.raises(ValueError, lambda: bool(s))
pytest.raises(ValueError, lambda: s.bool())
# single non-bool are an error
for s in [Series([1]), Series([0]), Series(['a']), Series([0.0])]:
pytest.raises(ValueError, lambda: bool(s))
pytest.raises(ValueError, lambda: 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
@pytest.mark.skipif(not _XARRAY_INSTALLED or _XARRAY_INSTALLED and
LooseVersion(xarray.__version__) <
LooseVersion('0.10.0'),
reason='xarray >= 0.10.0 required')
@pytest.mark.parametrize(
"index",
['FloatIndex', 'IntIndex',
'StringIndex', 'UnicodeIndex',
'DateIndex', 'PeriodIndex',
'TimedeltaIndex', 'CategoricalIndex'])
def test_to_xarray_index_types(self, index):
from xarray import DataArray
index = getattr(tm, 'make{}'.format(index))
s = Series(range(6), index=index(6))
s.index.name = 'foo'
result = s.to_xarray()
repr(result)
assert len(result) == 6
assert len(result.coords) == 1
assert_almost_equal(list(result.coords.keys()), ['foo'])
assert isinstance(result, DataArray)
# idempotency
assert_series_equal(result.to_series(), s,
check_index_type=False,
check_categorical=True)
@td.skip_if_no('xarray', min_version='0.7.0')
def test_to_xarray(self):
from xarray import DataArray
s = Series([])
s.index.name = 'foo'
result = s.to_xarray()
assert len(result) == 0
assert len(result.coords) == 1
assert_almost_equal(list(result.coords.keys()), ['foo'])
assert isinstance(result, DataArray)
s = Series(range(6))
s.index.name = 'foo'
s.index = pd.MultiIndex.from_product([['a', 'b'], range(3)],
names=['one', 'two'])
result = s.to_xarray()
assert len(result) == 2
assert_almost_equal(list(result.coords.keys()), ['one', 'two'])
assert isinstance(result, DataArray)
assert_series_equal(result.to_series(), s)
def test_valid_deprecated(self):
# GH18800
with tm.assert_produces_warning(FutureWarning):
pd.Series([]).valid()
@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
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