本文整理匯總了Python中pandas.Float64Index方法的典型用法代碼示例。如果您正苦於以下問題：Python pandas.Float64Index方法的具體用法？Python pandas.Float64Index怎麽用？Python pandas.Float64Index使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas的用法示例。
在下文中一共展示了pandas.Float64Index方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_explicit_conversions
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_explicit_conversions(self):
# GH 8608
# add/sub are overridden explicitly for Float/Int Index
idx = RangeIndex(5)
# float conversions
arr = np.arange(5, dtype='int64') * 3.2
expected = Float64Index(arr)
fidx = idx * 3.2
tm.assert_index_equal(fidx, expected)
fidx = 3.2 * idx
tm.assert_index_equal(fidx, expected)
# interops with numpy arrays
expected = Float64Index(arr)
a = np.zeros(5, dtype='float64')
result = fidx - a
tm.assert_index_equal(result, expected)
expected = Float64Index(-arr)
a = np.zeros(5, dtype='float64')
result = a - fidx
tm.assert_index_equal(result, expected) 示例2: test_explicit_conversions
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_explicit_conversions(self):
# GH 8608
# add/sub are overridden explicitly for Float/Int Index
idx = self._holder(np.arange(5, dtype='int64'))
# float conversions
arr = np.arange(5, dtype='int64') * 3.2
expected = Float64Index(arr)
fidx = idx * 3.2
tm.assert_index_equal(fidx, expected)
fidx = 3.2 * idx
tm.assert_index_equal(fidx, expected)
# interops with numpy arrays
expected = Float64Index(arr)
a = np.zeros(5, dtype='float64')
result = fidx - a
tm.assert_index_equal(result, expected)
expected = Float64Index(-arr)
a = np.zeros(5, dtype='float64')
result = a - fidx
tm.assert_index_equal(result, expected) 示例3: test_get_nan_multiple
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_get_nan_multiple():
# GH 8569
# ensure that fixing "test_get_nan" above hasn't broken get
# with multiple elements
s = pd.Float64Index(range(10)).to_series()
idx = [2, 30]
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
assert_series_equal(s.get(idx),
Series([2, np.nan], index=idx))
idx = [2, np.nan]
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
assert_series_equal(s.get(idx),
Series([2, np.nan], index=idx))
# GH 17295 - all missing keys
idx = [20, 30]
assert(s.get(idx) is None)
idx = [np.nan, np.nan]
assert(s.get(idx) is None) 示例4: test_insert
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_insert(self):
idx = RangeIndex(5, name='Foo')
result = idx[1:4]
# test 0th element
tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]))
# GH 18295 (test missing)
expected = Float64Index([0, np.nan, 1, 2, 3, 4])
for na in (np.nan, pd.NaT, None):
result = RangeIndex(5).insert(1, na)
tm.assert_index_equal(result, expected) 示例5: test_append
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_append(self):
# GH16212
RI = RangeIndex
I64 = Int64Index
F64 = Float64Index
OI = Index
cases = [([RI(1, 12, 5)], RI(1, 12, 5)),
([RI(0, 6, 4)], RI(0, 6, 4)),
([RI(1, 3), RI(3, 7)], RI(1, 7)),
([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
([RI(-4, -8), RI(3, -4)], RI(0, 0)),
([RI(-4, -8), RI(3, 5)], RI(3, 5)),
([RI(-4, -2), RI(3, 5)], I64([-4, -3, 3, 4])),
([RI(-2,), RI(3, 5)], RI(3, 5)),
([RI(2,), RI(2)], I64([0, 1, 0, 1])),
([RI(2,), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
([RI(2,), RI(3, 5), RI(5, 8, 4)], I64([0, 1, 3, 4, 5])),
([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
([RI(3,), I64([-1, 3, 15])], I64([0, 1, 2, -1, 3, 15])),
([RI(3,), F64([-1, 3.1, 15.])], F64([0, 1, 2, -1, 3.1, 15.])),
([RI(3,), OI(['a', None, 14])], OI([0, 1, 2, 'a', None, 14])),
([RI(3, 1), OI(['a', None, 14])], OI(['a', None, 14]))
]
for indices, expected in cases:
result = indices[0].append(indices[1:])
tm.assert_index_equal(result, expected, exact=True)
if len(indices) == 2:
# Append single item rather than list
result2 = indices[0].append(indices[1])
tm.assert_index_equal(result2, expected, exact=True) 示例6: test_constructor_int_dtype_nan
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_constructor_int_dtype_nan(self):
# see gh-15187
data = [np.nan]
expected = Float64Index(data)
result = Index(data, dtype='float')
tm.assert_index_equal(result, expected) 示例7: test_isin_nan_common_float64
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_isin_nan_common_float64(self, nulls_fixture):
if nulls_fixture is pd.NaT:
pytest.skip("pd.NaT not compatible with Float64Index")
# Float64Index overrides isin, so must be checked separately
tm.assert_numpy_array_equal(Float64Index([1.0, nulls_fixture]).isin(
[np.nan]), np.array([False, True]))
# we cannot compare NaT with NaN
tm.assert_numpy_array_equal(Float64Index([1.0, nulls_fixture]).isin(
[pd.NaT]), np.array([False, False])) 示例8: test_reindex_no_type_preserve_target_empty_mi
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_reindex_no_type_preserve_target_empty_mi(self):
index = pd.Index(list('abc'))
result = index.reindex(pd.MultiIndex(
[pd.Int64Index([]), pd.Float64Index([])], [[], []]))[0]
assert result.levels[0].dtype.type == np.int64
assert result.levels[1].dtype.type == np.float64 示例9: test_where
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_where(self, klass):
i = self.create_index()
cond = [True] * len(i)
expected = i
result = i.where(klass(cond))
cond = [False] + [True] * (len(i) - 1)
expected = Float64Index([i._na_value] + i[1:].tolist())
result = i.where(klass(cond))
tm.assert_index_equal(result, expected) 示例10: setup_method
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def setup_method(self, method):
self.indices = dict(mixed=Float64Index([1.5, 2, 3, 4, 5]),
float=Float64Index(np.arange(5) * 2.5),
mixed_dec=Float64Index([5, 4, 3, 2, 1.5]),
float_dec=Float64Index(np.arange(4, -1, -1) * 2.5))
self.setup_indices() 示例11: create_index
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def create_index(self):
return Float64Index(np.arange(5, dtype='float64')) 示例12: check_is_index
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def check_is_index(self, i):
assert isinstance(i, Index)
assert not isinstance(i, Float64Index) 示例13: check_coerce
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def check_coerce(self, a, b, is_float_index=True):
assert a.equals(b)
tm.assert_index_equal(a, b, exact=False)
if is_float_index:
assert isinstance(b, Float64Index)
else:
self.check_is_index(b) 示例14: test_constructor
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_constructor(self):
# explicit construction
index = Float64Index([1, 2, 3, 4, 5])
assert isinstance(index, Float64Index)
expected = np.array([1, 2, 3, 4, 5], dtype='float64')
tm.assert_numpy_array_equal(index.values, expected)
index = Float64Index(np.array([1, 2, 3, 4, 5]))
assert isinstance(index, Float64Index)
index = Float64Index([1., 2, 3, 4, 5])
assert isinstance(index, Float64Index)
index = Float64Index(np.array([1., 2, 3, 4, 5]))
assert isinstance(index, Float64Index)
assert index.dtype == float
index = Float64Index(np.array([1., 2, 3, 4, 5]), dtype=np.float32)
assert isinstance(index, Float64Index)
assert index.dtype == np.float64
index = Float64Index(np.array([1, 2, 3, 4, 5]), dtype=np.float32)
assert isinstance(index, Float64Index)
assert index.dtype == np.float64
# nan handling
result = Float64Index([np.nan, np.nan])
assert pd.isna(result.values).all()
result = Float64Index(np.array([np.nan]))
assert pd.isna(result.values).all()
result = Index(np.array([np.nan]))
assert pd.isna(result.values).all() 示例15: test_type_coercion_valid
# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import Float64Index [as 別名]
def test_type_coercion_valid(self, float_dtype):
# There is no Float32Index, so we always
# generate Float64Index.
i = Index([1, 2, 3.5], dtype=float_dtype)
tm.assert_index_equal(i, Index([1, 2, 3.5]))