Python pandas.util.testing.makeStringIndex() Examples
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code examples of pandas.util.testing.makeStringIndex().
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Example #1
| Source File: test_base.py From recruit with Apache License 2.0 | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeRangeIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #2
| Source File: test_base.py From vnpy_crypto with MIT License | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeRangeIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #3
| Source File: test_reductions.py From recruit with Apache License 2.0 | 6 votes |
|
def get_objs():
indexes = [
tm.makeBoolIndex(10, name='a'),
tm.makeIntIndex(10, name='a'),
tm.makeFloatIndex(10, name='a'),
tm.makeDateIndex(10, name='a'),
tm.makeDateIndex(10, name='a').tz_localize(tz='US/Eastern'),
tm.makePeriodIndex(10, name='a'),
tm.makeStringIndex(10, name='a'),
tm.makeUnicodeIndex(10, name='a')
]
arr = np.random.randn(10)
series = [Series(arr, index=idx, name='a') for idx in indexes]
objs = indexes + series
return objs
Example #4
| Source File: test_base.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeRangeIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #5
| Source File: test_base.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def setup_method(self, method):
self.bool_index = tm.makeBoolIndex(10, name='a')
self.int_index = tm.makeIntIndex(10, name='a')
self.float_index = tm.makeFloatIndex(10, name='a')
self.dt_index = tm.makeDateIndex(10, name='a')
self.dt_tz_index = tm.makeDateIndex(10, name='a').tz_localize(
tz='US/Eastern')
self.period_index = tm.makePeriodIndex(10, name='a')
self.string_index = tm.makeStringIndex(10, name='a')
self.unicode_index = tm.makeUnicodeIndex(10, name='a')
arr = np.random.randn(10)
self.int_series = Series(arr, index=self.int_index, name='a')
self.float_series = Series(arr, index=self.float_index, name='a')
self.dt_series = Series(arr, index=self.dt_index, name='a')
self.dt_tz_series = self.dt_tz_index.to_series(keep_tz=True)
self.period_series = Series(arr, index=self.period_index, name='a')
self.string_series = Series(arr, index=self.string_index, name='a')
types = ['bool', 'int', 'float', 'dt', 'dt_tz', 'period', 'string',
'unicode']
fmts = ["{0}_{1}".format(t, f)
for t in types for f in ['index', 'series']]
self.objs = [getattr(self, f)
for f in fmts if getattr(self, f, None) is not None]
Example #6
| Source File: test_constructors.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_constructor_dict_cast(self):
# cast float tests
test_data = {
'A': {'1': 1, '2': 2},
'B': {'1': '1', '2': '2', '3': '3'},
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 3
assert frame['B'].dtype == np.float64
assert frame['A'].dtype == np.float64
frame = DataFrame(test_data)
assert len(frame) == 3
assert frame['B'].dtype == np.object_
assert frame['A'].dtype == np.float64
# can't cast to float
test_data = {
'A': dict(zip(range(20), tm.makeStringIndex(20))),
'B': dict(zip(range(15), randn(15)))
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 20
assert frame['A'].dtype == np.object_
assert frame['B'].dtype == np.float64
Example #7
| Source File: test_packers.py From recruit with Apache License 2.0 | 6 votes |
|
def setup_method(self, method):
super(TestIndex, self).setup_method(method)
self.d = {
'string': tm.makeStringIndex(100),
'date': tm.makeDateIndex(100),
'int': tm.makeIntIndex(100),
'rng': tm.makeRangeIndex(100),
'float': tm.makeFloatIndex(100),
'empty': Index([]),
'tuple': Index(zip(['foo', 'bar', 'baz'], [1, 2, 3])),
'period': Index(period_range('2012-1-1', freq='M', periods=3)),
'date2': Index(date_range('2013-01-1', periods=10)),
'bdate': Index(bdate_range('2013-01-02', periods=10)),
'cat': tm.makeCategoricalIndex(100),
'interval': tm.makeIntervalIndex(100),
'timedelta': tm.makeTimedeltaIndex(100, 'H')
}
self.mi = {
'reg': MultiIndex.from_tuples([('bar', 'one'), ('baz', 'two'),
('foo', 'two'),
('qux', 'one'), ('qux', 'two')],
names=['first', 'second']),
}
Example #8
| Source File: test_base.py From coffeegrindsize with MIT License | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeRangeIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #9
| Source File: test_base.py From vnpy_crypto with MIT License | 6 votes |
|
def setup_method(self, method):
self.bool_index = tm.makeBoolIndex(10, name='a')
self.int_index = tm.makeIntIndex(10, name='a')
self.float_index = tm.makeFloatIndex(10, name='a')
self.dt_index = tm.makeDateIndex(10, name='a')
self.dt_tz_index = tm.makeDateIndex(10, name='a').tz_localize(
tz='US/Eastern')
self.period_index = tm.makePeriodIndex(10, name='a')
self.string_index = tm.makeStringIndex(10, name='a')
self.unicode_index = tm.makeUnicodeIndex(10, name='a')
arr = np.random.randn(10)
self.int_series = Series(arr, index=self.int_index, name='a')
self.float_series = Series(arr, index=self.float_index, name='a')
self.dt_series = Series(arr, index=self.dt_index, name='a')
self.dt_tz_series = self.dt_tz_index.to_series(keep_tz=True)
self.period_series = Series(arr, index=self.period_index, name='a')
self.string_series = Series(arr, index=self.string_index, name='a')
types = ['bool', 'int', 'float', 'dt', 'dt_tz', 'period', 'string',
'unicode']
fmts = ["{0}_{1}".format(t, f)
for t in types for f in ['index', 'series']]
self.objs = [getattr(self, f)
for f in fmts if getattr(self, f, None) is not None]
Example #10
| Source File: test_packers.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def setup_method(self, method):
super(TestIndex, self).setup_method(method)
self.d = {
'string': tm.makeStringIndex(100),
'date': tm.makeDateIndex(100),
'int': tm.makeIntIndex(100),
'rng': tm.makeRangeIndex(100),
'float': tm.makeFloatIndex(100),
'empty': Index([]),
'tuple': Index(zip(['foo', 'bar', 'baz'], [1, 2, 3])),
'period': Index(period_range('2012-1-1', freq='M', periods=3)),
'date2': Index(date_range('2013-01-1', periods=10)),
'bdate': Index(bdate_range('2013-01-02', periods=10)),
'cat': tm.makeCategoricalIndex(100)
}
self.mi = {
'reg': MultiIndex.from_tuples([('bar', 'one'), ('baz', 'two'),
('foo', 'two'),
('qux', 'one'), ('qux', 'two')],
names=['first', 'second']),
}
Example #11
| Source File: test_to_html.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_to_html_filename(self):
biggie = DataFrame({'A': np.random.randn(200),
'B': tm.makeStringIndex(200)},
index=lrange(200))
biggie.loc[:20, 'A'] = np.nan
biggie.loc[:20, 'B'] = np.nan
with tm.ensure_clean('test.html') as path:
biggie.to_html(path)
with open(path, 'r') as f:
s = biggie.to_html()
s2 = f.read()
assert s == s2
frame = DataFrame(index=np.arange(200))
with tm.ensure_clean('test.html') as path:
frame.to_html(path)
with open(path, 'r') as f:
assert frame.to_html() == f.read()
Example #12
| Source File: test_constructors.py From vnpy_crypto with MIT License | 6 votes |
|
def test_constructor_dict_cast(self):
# cast float tests
test_data = {
'A': {'1': 1, '2': 2},
'B': {'1': '1', '2': '2', '3': '3'},
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 3
assert frame['B'].dtype == np.float64
assert frame['A'].dtype == np.float64
frame = DataFrame(test_data)
assert len(frame) == 3
assert frame['B'].dtype == np.object_
assert frame['A'].dtype == np.float64
# can't cast to float
test_data = {
'A': dict(zip(range(20), tm.makeStringIndex(20))),
'B': dict(zip(range(15), randn(15)))
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 20
assert frame['A'].dtype == np.object_
assert frame['B'].dtype == np.float64
Example #13
| Source File: test_to_html.py From vnpy_crypto with MIT License | 6 votes |
|
def test_to_html_filename(self):
biggie = DataFrame({'A': np.random.randn(200),
'B': tm.makeStringIndex(200)},
index=lrange(200))
biggie.loc[:20, 'A'] = np.nan
biggie.loc[:20, 'B'] = np.nan
with tm.ensure_clean('test.html') as path:
biggie.to_html(path)
with open(path, 'r') as f:
s = biggie.to_html()
s2 = f.read()
assert s == s2
frame = DataFrame(index=np.arange(200))
with tm.ensure_clean('test.html') as path:
frame.to_html(path)
with open(path, 'r') as f:
assert frame.to_html() == f.read()
Example #14
| Source File: test_packers.py From vnpy_crypto with MIT License | 6 votes |
|
def setup_method(self, method):
super(TestIndex, self).setup_method(method)
self.d = {
'string': tm.makeStringIndex(100),
'date': tm.makeDateIndex(100),
'int': tm.makeIntIndex(100),
'rng': tm.makeRangeIndex(100),
'float': tm.makeFloatIndex(100),
'empty': Index([]),
'tuple': Index(zip(['foo', 'bar', 'baz'], [1, 2, 3])),
'period': Index(period_range('2012-1-1', freq='M', periods=3)),
'date2': Index(date_range('2013-01-1', periods=10)),
'bdate': Index(bdate_range('2013-01-02', periods=10)),
'cat': tm.makeCategoricalIndex(100),
'interval': tm.makeIntervalIndex(100),
'timedelta': tm.makeTimedeltaIndex(100, 'H')
}
self.mi = {
'reg': MultiIndex.from_tuples([('bar', 'one'), ('baz', 'two'),
('foo', 'two'),
('qux', 'one'), ('qux', 'two')],
names=['first', 'second']),
}
Example #15
| Source File: test_base.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def setup_method(self, method):
self.bool_index = tm.makeBoolIndex(10, name='a')
self.int_index = tm.makeIntIndex(10, name='a')
self.float_index = tm.makeFloatIndex(10, name='a')
self.dt_index = tm.makeDateIndex(10, name='a')
self.dt_tz_index = tm.makeDateIndex(10, name='a').tz_localize(
tz='US/Eastern')
self.period_index = tm.makePeriodIndex(10, name='a')
self.string_index = tm.makeStringIndex(10, name='a')
self.unicode_index = tm.makeUnicodeIndex(10, name='a')
arr = np.random.randn(10)
self.int_series = Series(arr, index=self.int_index, name='a')
self.float_series = Series(arr, index=self.float_index, name='a')
self.dt_series = Series(arr, index=self.dt_index, name='a')
self.dt_tz_series = self.dt_tz_index.to_series(keep_tz=True)
self.period_series = Series(arr, index=self.period_index, name='a')
self.string_series = Series(arr, index=self.string_index, name='a')
types = ['bool', 'int', 'float', 'dt', 'dt_tz', 'period', 'string',
'unicode']
fmts = ["{0}_{1}".format(t, f)
for t in types for f in ['index', 'series']]
self.objs = [getattr(self, f)
for f in fmts if getattr(self, f, None) is not None]
Example #16
| Source File: test_packers.py From Computable with MIT License | 6 votes |
|
def setUp(self):
super(TestIndex, self).setUp()
self.d = {
'string': tm.makeStringIndex(100),
'date': tm.makeDateIndex(100),
'int': tm.makeIntIndex(100),
'float': tm.makeFloatIndex(100),
'empty': Index([]),
'tuple': Index(zip(['foo', 'bar', 'baz'], [1, 2, 3])),
'period': Index(period_range('2012-1-1', freq='M', periods=3)),
'date2': Index(date_range('2013-01-1', periods=10)),
'bdate': Index(bdate_range('2013-01-02', periods=10)),
}
self.mi = {
'reg': MultiIndex.from_tuples([('bar', 'one'), ('baz', 'two'), ('foo', 'two'),
('qux', 'one'), ('qux', 'two')], names=['first', 'second']),
}
Example #17
| Source File: test_base.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeRangeIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #18
| Source File: test_base.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def setup_method(self, method):
self.indices = dict(unicodeIndex=tm.makeUnicodeIndex(100),
strIndex=tm.makeStringIndex(100),
dateIndex=tm.makeDateIndex(100),
periodIndex=tm.makePeriodIndex(100),
tdIndex=tm.makeTimedeltaIndex(100),
intIndex=tm.makeIntIndex(100),
uintIndex=tm.makeUIntIndex(100),
rangeIndex=tm.makeIntIndex(100),
floatIndex=tm.makeFloatIndex(100),
boolIndex=Index([True, False]),
catIndex=tm.makeCategoricalIndex(100),
empty=Index([]),
tuples=MultiIndex.from_tuples(lzip(
['foo', 'bar', 'baz'], [1, 2, 3])),
repeats=Index([0, 0, 1, 1, 2, 2]))
self.setup_indices()
Example #19
| Source File: test_packers.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def setup_method(self, method):
super(TestIndex, self).setup_method(method)
self.d = {
'string': tm.makeStringIndex(100),
'date': tm.makeDateIndex(100),
'int': tm.makeIntIndex(100),
'rng': tm.makeRangeIndex(100),
'float': tm.makeFloatIndex(100),
'empty': Index([]),
'tuple': Index(zip(['foo', 'bar', 'baz'], [1, 2, 3])),
'period': Index(period_range('2012-1-1', freq='M', periods=3)),
'date2': Index(date_range('2013-01-1', periods=10)),
'bdate': Index(bdate_range('2013-01-02', periods=10)),
'cat': tm.makeCategoricalIndex(100),
'interval': tm.makeIntervalIndex(100),
'timedelta': tm.makeTimedeltaIndex(100, 'H')
}
self.mi = {
'reg': MultiIndex.from_tuples([('bar', 'one'), ('baz', 'two'),
('foo', 'two'),
('qux', 'one'), ('qux', 'two')],
names=['first', 'second']),
}
Example #20
| Source File: test_constructors.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_constructor_dict_cast(self):
# cast float tests
test_data = {
'A': {'1': 1, '2': 2},
'B': {'1': '1', '2': '2', '3': '3'},
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 3
assert frame['B'].dtype == np.float64
assert frame['A'].dtype == np.float64
frame = DataFrame(test_data)
assert len(frame) == 3
assert frame['B'].dtype == np.object_
assert frame['A'].dtype == np.float64
# can't cast to float
test_data = {
'A': dict(zip(range(20), tm.makeStringIndex(20))),
'B': dict(zip(range(15), randn(15)))
}
frame = DataFrame(test_data, dtype=float)
assert len(frame) == 20
assert frame['A'].dtype == np.object_
assert frame['B'].dtype == np.float64
Example #21
| Source File: test_reductions.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def get_objs():
indexes = [
tm.makeBoolIndex(10, name='a'),
tm.makeIntIndex(10, name='a'),
tm.makeFloatIndex(10, name='a'),
tm.makeDateIndex(10, name='a'),
tm.makeDateIndex(10, name='a').tz_localize(tz='US/Eastern'),
tm.makePeriodIndex(10, name='a'),
tm.makeStringIndex(10, name='a'),
tm.makeUnicodeIndex(10, name='a')
]
arr = np.random.randn(10)
series = [Series(arr, index=idx, name='a') for idx in indexes]
objs = indexes + series
return objs
Example #22
| Source File: test_to_html.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_to_html_filename(self):
biggie = DataFrame({'A': np.random.randn(200),
'B': tm.makeStringIndex(200)},
index=lrange(200))
biggie.loc[:20, 'A'] = np.nan
biggie.loc[:20, 'B'] = np.nan
with tm.ensure_clean('test.html') as path:
biggie.to_html(path)
with open(path, 'r') as f:
s = biggie.to_html()
s2 = f.read()
assert s == s2
frame = DataFrame(index=np.arange(200))
with tm.ensure_clean('test.html') as path:
frame.to_html(path)
with open(path, 'r') as f:
assert frame.to_html() == f.read()
Example #23
| Source File: test_floats.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_scalar_error(self):
# GH 4892
# float_indexers should raise exceptions
# on appropriate Index types & accessors
# this duplicates the code below
# but is spefically testing for the error
# message
for index in [tm.makeStringIndex, tm.makeUnicodeIndex,
tm.makeCategoricalIndex,
tm.makeDateIndex, tm.makeTimedeltaIndex,
tm.makePeriodIndex, tm.makeIntIndex,
tm.makeRangeIndex]:
i = index(5)
s = Series(np.arange(len(i)), index=i)
def f():
s.iloc[3.0]
tm.assert_raises_regex(TypeError,
'cannot do positional indexing',
f)
def f():
s.iloc[3.0] = 0
pytest.raises(TypeError, f)
Example #24
| Source File: test_object.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_sub_fail(self):
index = tm.makeStringIndex(100)
with pytest.raises(TypeError):
index - 'a'
with pytest.raises(TypeError):
index - index
with pytest.raises(TypeError):
index - index.tolist()
with pytest.raises(TypeError):
index.tolist() - index
Example #25
| Source File: test_object.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_add(self):
index = tm.makeStringIndex(100)
expected = pd.Index(index.values * 2)
tm.assert_index_equal(index + index, expected)
tm.assert_index_equal(index + index.tolist(), expected)
tm.assert_index_equal(index.tolist() + index, expected)
# test add and radd
index = pd.Index(list('abc'))
expected = pd.Index(['a1', 'b1', 'c1'])
tm.assert_index_equal(index + '1', expected)
expected = pd.Index(['1a', '1b', '1c'])
tm.assert_index_equal('1' + index, expected)
Example #26
| Source File: test_combine_concat.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_combine_first(self):
values = tm.makeIntIndex(20).values.astype(float)
series = Series(values, index=tm.makeIntIndex(20))
series_copy = series * 2
series_copy[::2] = np.NaN
# nothing used from the input
combined = series.combine_first(series_copy)
tm.assert_series_equal(combined, series)
# Holes filled from input
combined = series_copy.combine_first(series)
assert np.isfinite(combined).all()
tm.assert_series_equal(combined[::2], series[::2])
tm.assert_series_equal(combined[1::2], series_copy[1::2])
# mixed types
index = tm.makeStringIndex(20)
floats = Series(tm.randn(20), index=index)
strings = Series(tm.makeStringIndex(10), index=index[::2])
combined = strings.combine_first(floats)
tm.assert_series_equal(strings, combined.loc[index[::2]])
tm.assert_series_equal(floats[1::2].astype(object),
combined.loc[index[1::2]])
# corner case
s = Series([1., 2, 3], index=[0, 1, 2])
result = s.combine_first(Series([], index=[]))
assert_series_equal(s, result)
Example #27
| Source File: test_repr_info.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_repr_mixed_big(self):
# big mixed
biggie = DataFrame({'A': np.random.randn(200),
'B': tm.makeStringIndex(200)},
index=lrange(200))
biggie.loc[:20, 'A'] = nan
biggie.loc[:20, 'B'] = nan
foo = repr(biggie) # noqa
Example #28
| Source File: test_frequencies.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_invalid_index_types(self):
# test all index types
for i in [tm.makeIntIndex(10), tm.makeFloatIndex(10),
tm.makePeriodIndex(10)]:
pytest.raises(TypeError, lambda: frequencies.infer_freq(i))
# GH 10822
# odd error message on conversions to datetime for unicode
if not is_platform_windows():
for i in [tm.makeStringIndex(10), tm.makeUnicodeIndex(10)]:
pytest.raises(ValueError, lambda: frequencies.infer_freq(i))
Example #29
| Source File: test_grouping.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_grouper_index_types(self):
# related GH5375
# groupby misbehaving when using a Floatlike index
df = DataFrame(np.arange(10).reshape(5, 2), columns=list('AB'))
for index in [tm.makeFloatIndex, tm.makeStringIndex,
tm.makeUnicodeIndex, tm.makeIntIndex, tm.makeDateIndex,
tm.makePeriodIndex]:
df.index = index(len(df))
df.groupby(list('abcde')).apply(lambda x: x)
df.index = list(reversed(df.index.tolist()))
df.groupby(list('abcde')).apply(lambda x: x)
Example #30
| Source File: test_format.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_to_string_truncate_indices(self):
for index in [tm.makeStringIndex, tm.makeUnicodeIndex, tm.makeIntIndex,
tm.makeDateIndex, tm.makePeriodIndex]:
for column in [tm.makeStringIndex]:
for h in [10, 20]:
for w in [10, 20]:
with option_context("display.expand_frame_repr",
False):
df = DataFrame(index=index(h), columns=column(w))
with option_context("display.max_rows", 15):
if h == 20:
assert has_vertically_truncated_repr(df)
else:
assert not has_vertically_truncated_repr(
df)
with option_context("display.max_columns", 15):
if w == 20:
assert has_horizontally_truncated_repr(df)
else:
assert not (
has_horizontally_truncated_repr(df))
with option_context("display.max_rows", 15,
"display.max_columns", 15):
if h == 20 and w == 20:
assert has_doubly_truncated_repr(df)
else:
assert not has_doubly_truncated_repr(
df)
