allow for pandas 3 strings

Author: rok

docs/source/python/data.rst

@@ -648,7 +648,7 @@ Here we have:
 .. code-block:: python
 
    >>> print(dict_array.type)
-   dictionary<values=string, indices=int64, ordered=0>
+   dictionary<values=...string, indices=int64, ordered=0>
    >>> dict_array.indices
    <pyarrow.lib.Int64Array object at ...>
    [
@@ -684,7 +684,7 @@ When using :class:`~.DictionaryArray` with pandas, the analogue is
    6    NaN
    7    baz
    dtype: category
-   Categories (3, object): ['foo', 'bar', 'baz']
+   Categories (3, ...): ['foo', 'bar', 'baz']
 
 .. _data.record_batch:
 
@@ -714,7 +714,7 @@ A record batch can be created from this list of arrays using
    4
    >>> batch.schema
    f0: int64
-   f1: string
+   f1: ...string
    f2: bool
    >>>
    >>> batch[1]
@@ -761,7 +761,7 @@ one or more copies of the batch using ``Table.from_batches``:
    >>> table
    pyarrow.Table
    f0: int64
-   f1: string
+   f1: ...string
    f2: bool
    ----
    f0: [[1,2,3,4],[1,2,3,4],...,[1,2,3,4],[1,2,3,4]]

docs/source/python/ipc.rst

@@ -94,7 +94,7 @@ convenience function ``pyarrow.ipc.open_stream``:
    ...     batches = [b for b in reader]
    >>> schema
    f0: int64
-   f1: string
+   f1: ...string
    f2: bool
    >>> len(batches)
    5

docs/source/python/pandas.rst

@@ -182,7 +182,7 @@ number of possible values.
    >>> table = pa.Table.from_pandas(df)
    >>> table
    pyarrow.Table
-   cat: dictionary<values=string, indices=int8, ordered=0>
+   cat: dictionary<values=...string, indices=int8, ordered=0>
    ----
    cat: [  -- dictionary:
    ["a","b","c"]  -- indices:

docs/source/python/parquet.rst

@@ -238,9 +238,9 @@ concatenate them into a single table. You can read individual row groups with
    >>> parquet_file.read_row_group(0)
    pyarrow.Table
    one: double
-   two: string
+   two: ...string
    three: bool
-   __index_level_0__: string
+   __index_level_0__: ...string
    ----
    one: [[-1,null,2.5]]
    two: [["foo","bar","baz"]]
@@ -350,9 +350,9 @@ and improved performance for columns with many repeated string values.
    >>> pq.read_table('example.parquet', read_dictionary=['two'])
    pyarrow.Table
    one: double
-   two: dictionary<values=string, indices=int32, ordered=0>
+   two: dictionary<values=...string, indices=int32, ordered=0>
    three: bool
-   __index_level_0__: string
+   __index_level_0__: ...string
    ----
    one: [[-1,null,2.5]]
    two: [  -- dictionary: