# # 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))