本文整理汇总了Python中pandas.util.testing.makeCategoricalIndex方法的典型用法代码示例。如果您正苦于以下问题：Python testing.makeCategoricalIndex方法的具体用法？Python testing.makeCategoricalIndex怎么用？Python testing.makeCategoricalIndex使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pandas.util.testing的用法示例。
在下文中一共展示了testing.makeCategoricalIndex方法的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: setup_method
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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() 示例2: test_construction_with_categorical_index
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
def test_construction_with_categorical_index(self):
ci = tm.makeCategoricalIndex(10)
ci.name = 'B'
# with Categorical
df = DataFrame({'A': np.random.randn(10),
'B': ci.values})
idf = df.set_index('B')
tm.assert_index_equal(idf.index, ci)
# from a CategoricalIndex
df = DataFrame({'A': np.random.randn(10),
'B': ci})
idf = df.set_index('B')
tm.assert_index_equal(idf.index, ci)
# round-trip
idf = idf.reset_index().set_index('B')
tm.assert_index_equal(idf.index, ci) 示例3: setup_method
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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']),
} 示例4: setup_method
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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() 示例5: setup_method
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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']),
} 示例6: setup_method
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
def setup_method(self, method):
self.indices = dict(catIndex=tm.makeCategoricalIndex(100))
self.setup_indices() 示例7: test_scalar_error
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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)
msg = 'Cannot index by location index'
with pytest.raises(TypeError, match=msg):
s.iloc[3.0]
def f():
s.iloc[3.0] = 0
pytest.raises(TypeError, f) 示例8: test_scalar_error
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
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) 示例9: test_construction_with_categorical_index
# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import makeCategoricalIndex [as 别名]
def test_construction_with_categorical_index(self):
ci = tm.makeCategoricalIndex(10)
# with Categorical
df = DataFrame({'A': np.random.randn(10),
'B': ci.values})
idf = df.set_index('B')
str(idf)
tm.assert_index_equal(idf.index, ci, check_names=False)
assert idf.index.name == 'B'
# from a CategoricalIndex
df = DataFrame({'A': np.random.randn(10),
'B': ci})
idf = df.set_index('B')
str(idf)
tm.assert_index_equal(idf.index, ci, check_names=False)
assert idf.index.name == 'B'
idf = df.set_index('B').reset_index().set_index('B')
str(idf)
tm.assert_index_equal(idf.index, ci, check_names=False)
assert idf.index.name == 'B'
new_df = idf.reset_index()
new_df.index = df.B
tm.assert_index_equal(new_df.index, ci, check_names=False)
assert idf.index.name == 'B'