230 lines
7.4 KiB
Python
230 lines
7.4 KiB
Python
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# -*- coding: utf-8 -*-
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# pylint: disable-msg=E1101,W0612
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from operator import methodcaller
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import pytest
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import numpy as np
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import pandas as pd
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from distutils.version import LooseVersion
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from pandas import Series, date_range, MultiIndex
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from pandas.compat import range
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from pandas.util.testing import (assert_series_equal,
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assert_almost_equal)
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import pandas.util.testing as tm
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import pandas.util._test_decorators as td
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from .test_generic import Generic
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try:
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import xarray
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_XARRAY_INSTALLED = True
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except ImportError:
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_XARRAY_INSTALLED = False
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class TestSeries(Generic):
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_typ = Series
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_comparator = lambda self, x, y: assert_series_equal(x, y)
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def setup_method(self):
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self.ts = tm.makeTimeSeries() # Was at top level in test_series
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self.ts.name = 'ts'
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self.series = tm.makeStringSeries()
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self.series.name = 'series'
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def test_rename_mi(self):
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s = Series([11, 21, 31],
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index=MultiIndex.from_tuples(
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[("A", x) for x in ["a", "B", "c"]]))
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s.rename(str.lower)
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def test_set_axis_name(self):
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s = Series([1, 2, 3], index=['a', 'b', 'c'])
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funcs = ['rename_axis', '_set_axis_name']
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name = 'foo'
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for func in funcs:
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result = methodcaller(func, name)(s)
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assert s.index.name is None
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assert result.index.name == name
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def test_set_axis_name_mi(self):
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s = Series([11, 21, 31], index=MultiIndex.from_tuples(
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[("A", x) for x in ["a", "B", "c"]],
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names=['l1', 'l2'])
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)
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funcs = ['rename_axis', '_set_axis_name']
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for func in funcs:
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result = methodcaller(func, ['L1', 'L2'])(s)
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assert s.index.name is None
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assert s.index.names == ['l1', 'l2']
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assert result.index.name is None
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assert result.index.names, ['L1', 'L2']
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def test_set_axis_name_raises(self):
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s = pd.Series([1])
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with pytest.raises(ValueError):
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s._set_axis_name(name='a', axis=1)
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def test_get_numeric_data_preserve_dtype(self):
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# get the numeric data
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o = Series([1, 2, 3])
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result = o._get_numeric_data()
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self._compare(result, o)
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o = Series([1, '2', 3.])
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result = o._get_numeric_data()
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expected = Series([], dtype=object, index=pd.Index([], dtype=object))
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self._compare(result, expected)
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o = Series([True, False, True])
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result = o._get_numeric_data()
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self._compare(result, o)
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o = Series([True, False, True])
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result = o._get_bool_data()
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self._compare(result, o)
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o = Series(date_range('20130101', periods=3))
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result = o._get_numeric_data()
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expected = Series([], dtype='M8[ns]', index=pd.Index([], dtype=object))
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self._compare(result, expected)
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def test_nonzero_single_element(self):
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# allow single item via bool method
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s = Series([True])
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assert s.bool()
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s = Series([False])
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assert not s.bool()
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# single item nan to raise
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for s in [Series([np.nan]), Series([pd.NaT]), Series([True]),
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Series([False])]:
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pytest.raises(ValueError, lambda: bool(s))
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for s in [Series([np.nan]), Series([pd.NaT])]:
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pytest.raises(ValueError, lambda: s.bool())
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# multiple bool are still an error
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for s in [Series([True, True]), Series([False, False])]:
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pytest.raises(ValueError, lambda: bool(s))
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pytest.raises(ValueError, lambda: s.bool())
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# single non-bool are an error
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for s in [Series([1]), Series([0]), Series(['a']), Series([0.0])]:
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pytest.raises(ValueError, lambda: bool(s))
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pytest.raises(ValueError, lambda: s.bool())
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def test_metadata_propagation_indiv(self):
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# check that the metadata matches up on the resulting ops
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o = Series(range(3), range(3))
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o.name = 'foo'
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o2 = Series(range(3), range(3))
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o2.name = 'bar'
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result = o.T
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self.check_metadata(o, result)
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# resample
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ts = Series(np.random.rand(1000),
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index=date_range('20130101', periods=1000, freq='s'),
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name='foo')
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result = ts.resample('1T').mean()
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self.check_metadata(ts, result)
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result = ts.resample('1T').min()
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self.check_metadata(ts, result)
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result = ts.resample('1T').apply(lambda x: x.sum())
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self.check_metadata(ts, result)
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_metadata = Series._metadata
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_finalize = Series.__finalize__
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Series._metadata = ['name', 'filename']
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o.filename = 'foo'
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o2.filename = 'bar'
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def finalize(self, other, method=None, **kwargs):
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for name in self._metadata:
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if method == 'concat' and name == 'filename':
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value = '+'.join([getattr(
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o, name) for o in other.objs if getattr(o, name, None)
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])
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object.__setattr__(self, name, value)
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else:
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object.__setattr__(self, name, getattr(other, name, None))
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return self
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Series.__finalize__ = finalize
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result = pd.concat([o, o2])
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assert result.filename == 'foo+bar'
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assert result.name is None
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# reset
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Series._metadata = _metadata
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Series.__finalize__ = _finalize
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@pytest.mark.skipif(not _XARRAY_INSTALLED or _XARRAY_INSTALLED and
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LooseVersion(xarray.__version__) <
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LooseVersion('0.10.0'),
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reason='xarray >= 0.10.0 required')
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@pytest.mark.parametrize(
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"index",
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['FloatIndex', 'IntIndex',
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'StringIndex', 'UnicodeIndex',
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'DateIndex', 'PeriodIndex',
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'TimedeltaIndex', 'CategoricalIndex'])
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def test_to_xarray_index_types(self, index):
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from xarray import DataArray
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index = getattr(tm, 'make{}'.format(index))
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s = Series(range(6), index=index(6))
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s.index.name = 'foo'
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result = s.to_xarray()
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repr(result)
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assert len(result) == 6
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assert len(result.coords) == 1
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assert_almost_equal(list(result.coords.keys()), ['foo'])
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assert isinstance(result, DataArray)
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# idempotency
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assert_series_equal(result.to_series(), s,
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check_index_type=False,
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check_categorical=True)
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@td.skip_if_no('xarray', min_version='0.7.0')
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def test_to_xarray(self):
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from xarray import DataArray
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s = Series([])
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s.index.name = 'foo'
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result = s.to_xarray()
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assert len(result) == 0
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assert len(result.coords) == 1
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assert_almost_equal(list(result.coords.keys()), ['foo'])
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assert isinstance(result, DataArray)
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s = Series(range(6))
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s.index.name = 'foo'
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s.index = pd.MultiIndex.from_product([['a', 'b'], range(3)],
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names=['one', 'two'])
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result = s.to_xarray()
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assert len(result) == 2
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assert_almost_equal(list(result.coords.keys()), ['one', 'two'])
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assert isinstance(result, DataArray)
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assert_series_equal(result.to_series(), s)
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def test_valid_deprecated(self):
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# GH18800
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with tm.assert_produces_warning(FutureWarning):
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pd.Series([]).valid()
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