#
# Copyright (C) 2019 Databricks, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import pandas as pd
from pandas.api.types import is_hashable
from databricks import koalas as ks
from databricks.koalas.indexes.base import Index
from databricks.koalas.series import Series
class NumericIndex(Index):
"""
Provide numeric type operations.
This is an abstract class.
"""
pass
class IntegerIndex(NumericIndex):
"""
This is an abstract class for Int64Index.
"""
pass
[docs]class Int64Index(IntegerIndex):
"""
Immutable sequence used for indexing and alignment. The basic object
storing axis labels for all pandas objects. Int64Index is a special case
of `Index` with purely integer labels.
Parameters
----------
data : array-like (1-dimensional)
dtype : NumPy dtype (default: int64)
copy : bool
Make a copy of input ndarray.
name : object
Name to be stored in the index.
See Also
--------
Index : The base Koalas Index type.
Float64Index : A special case of :class:`Index` with purely float labels.
Notes
-----
An Index instance can **only** contain hashable objects.
Examples
--------
>>> ks.Int64Index([1, 2, 3])
Int64Index([1, 2, 3], dtype='int64')
From a Series:
>>> s = ks.Series([1, 2, 3], index=[10, 20, 30])
>>> ks.Int64Index(s)
Int64Index([1, 2, 3], dtype='int64')
From an Index:
>>> idx = ks.Index([1, 2, 3])
>>> ks.Int64Index(idx)
Int64Index([1, 2, 3], dtype='int64')
"""
def __new__(cls, data=None, dtype=None, copy=False, name=None):
if not is_hashable(name):
raise TypeError("Index.name must be a hashable type")
if isinstance(data, (Series, Index)):
if dtype is None:
dtype = "int64"
return Index(data, dtype=dtype, copy=copy, name=name)
return ks.from_pandas(pd.Int64Index(data=data, dtype=dtype, copy=copy, name=name))
[docs]class Float64Index(NumericIndex):
"""
Immutable sequence used for indexing and alignment. The basic object
storing axis labels for all pandas objects. Float64Index is a special case
of `Index` with purely float labels.
Parameters
----------
data : array-like (1-dimensional)
dtype : NumPy dtype (default: float64)
copy : bool
Make a copy of input ndarray.
name : object
Name to be stored in the index.
See Also
--------
Index : The base Koalas Index type.
Int64Index : A special case of :class:`Index` with purely integer labels.
Notes
-----
An Index instance can **only** contain hashable objects.
Examples
--------
>>> ks.Float64Index([1.0, 2.0, 3.0])
Float64Index([1.0, 2.0, 3.0], dtype='float64')
From a Series:
>>> s = ks.Series([1, 2, 3], index=[10, 20, 30])
>>> ks.Float64Index(s)
Float64Index([1.0, 2.0, 3.0], dtype='float64')
From an Index:
>>> idx = ks.Index([1, 2, 3])
>>> ks.Float64Index(idx)
Float64Index([1.0, 2.0, 3.0], dtype='float64')
"""
def __new__(cls, data=None, dtype=None, copy=False, name=None):
if not is_hashable(name):
raise TypeError("Index.name must be a hashable type")
if isinstance(data, (Series, Index)):
if dtype is None:
dtype = "float64"
return Index(data, dtype=dtype, copy=copy, name=name)
return ks.from_pandas(pd.Float64Index(data=data, dtype=dtype, copy=copy, name=name))