@@ -29,20 +29,20 @@ It is now possible to create an index of any numpy int/uint/float dtype using th
29
29
pd.NumericIndex([1 , 2 , 3 ], dtype = " uint32" )
30
30
pd.NumericIndex([1 , 2 , 3 ], dtype = " float32" )
31
31
32
- In order to maintain backwards compatibility, calls to the base :class: `Index ` will in
33
- pandas 1.x. return :class: `Int64Index `, :class: `UInt64Index ` and :class: `Float64Index `, where relevant.
32
+ In order to maintain backwards compatibility, calls to the base :class: `Index ` will currently
33
+ return :class: `Int64Index `, :class: `UInt64Index ` and :class: `Float64Index `, where relevant.
34
34
For example, the code below returns an ``Int64Index `` with dtype ``int64 ``:
35
35
36
36
.. code-block :: ipython
37
37
38
38
In [1]: pd.Index([1, 2, 3], dtype="int8")
39
39
Int64Index([1, 2, 3], dtype='int64')
40
40
41
- but will in Pandas 2.0 return a :class: `NumericIndex ` with dtype ``int8 ``.
41
+ but will in a future version return a :class: `NumericIndex ` with dtype ``int8 ``.
42
42
43
- More generally, for the duration of Pandas 1.x , all operations that until now have
43
+ More generally, currently , all operations that until now have
44
44
returned :class: `Int64Index `, :class: `UInt64Index ` and :class: `Float64Index ` will
45
- continue to so. This means, that in order to use ``NumericIndex `` in Pandas 1.x , you
45
+ continue to so. This means, that in order to use ``NumericIndex `` in the current version , you
46
46
will have to call ``NumericIndex `` explicitly. For example the below series will have an ``Int64Index ``:
47
47
48
48
.. code-block :: ipython
@@ -51,17 +51,17 @@ will have to call ``NumericIndex`` explicitly. For example the below series will
51
51
In [3]: ser.index
52
52
Int64Index([1, 2, 3], dtype='int64')
53
53
54
- Instead, if you want to use a ``NumericIndex `` in Pandas 1.x , you should do:
54
+ Instead, if you want to use a ``NumericIndex ``, you should do:
55
55
56
56
.. ipython :: python
57
57
58
58
idx = pd.NumericIndex([1 , 2 , 3 ], dtype = " int8" )
59
59
ser = pd.Series([1 , 2 , 3 ], index = idx)
60
60
ser.index
61
61
62
- In Pandas 2.0 , :class: `NumericIndex ` will become the default numeric index type and
62
+ In a future version of Pandas , :class: `NumericIndex ` will become the default numeric index type and
63
63
``Int64Index ``, ``UInt64Index `` and ``Float64Index `` are therefore deprecated and will
64
- be removed in pandas 2.0 , see :ref: `here <whatsnew_140.deprecations.int64_uint64_float64index >` for more.
64
+ be removed in the future , see :ref: `here <whatsnew_140.deprecations.int64_uint64_float64index >` for more.
65
65
66
66
See :ref: `here <advanced.numericindex >` for more about :class: `NumericIndex `.
67
67
@@ -234,9 +234,9 @@ Deprecated Int64Index, UInt64Index & Float64Index
234
234
:class: `Int64Index `, :class: `UInt64Index ` and :class: `Float64Index ` have been deprecated
235
235
in favor of the new :class: `NumericIndex ` and will be removed in Pandas 2.0 (:issue: `43028 `).
236
236
237
- For the duration of Pandas 1.x , in order to maintain backward compatibility, calls to
237
+ Currently , in order to maintain backward compatibility, calls to
238
238
:class: `Index ` will continue to return :class: `Int64Index `, :class: `UInt64Index ` and :class: `Float64Index `
239
- when given numeric data, but in Pandas 2.0 , a :class: `NumericIndex ` will be returned.
239
+ when given numeric data, but in the future , a :class: `NumericIndex ` will be returned.
240
240
241
241
*Current behavior *:
242
242
0 commit comments