remove tests and docs for legacy hdf5-pandas support (pandas<0.11)

Author: tp

doc/source/io.rst

@@ -4419,44 +4419,6 @@ Now you can import the ``DataFrame`` into R:
    starting point if you have stored multiple ``DataFrame`` objects to a
    single HDF5 file.
 
-Backwards Compatibility
-'''''''''''''''''''''''
-
-0.10.1 of ``HDFStore`` can read tables created in a prior version of pandas,
-however query terms using the
-prior (undocumented) methodology are unsupported. ``HDFStore`` will
-issue a warning if you try to use a legacy-format file. You must
-read in the entire file and write it out using the new format, using the
-method ``copy`` to take advantage of the updates. The group attribute
-``pandas_version`` contains the version information. ``copy`` takes a
-number of options, please see the docstring.
-
-
-.. ipython:: python
-   :suppress:
-
-   import os
-   legacy_file_path = os.path.abspath('source/_static/legacy_0.10.h5')
-
-.. ipython:: python
-   :okwarning:
-
-   # a legacy store
-   legacy_store = pd.HDFStore(legacy_file_path,'r')
-   legacy_store
-
-   # copy (and return the new handle)
-   new_store = legacy_store.copy('store_new.h5')
-   new_store
-   new_store.close()
-
-.. ipython:: python
-   :suppress:
-
-   legacy_store.close()
-   import os
-   os.remove('store_new.h5')
-
 
 Performance
 '''''''''''

doc/source/whatsnew/v0.21.0.txt

@@ -317,6 +317,8 @@ Removal of prior version deprecations/changes
 - ``Categorical`` has dropped the ``.order()`` and ``.sort()`` methods in favor of ``.sort_values()`` (:issue:`12882`)
 - :func:`eval` and :func:`DataFrame.eval` have changed the default of ``inplace`` from ``None`` to ``False`` (:issue:`11149`)
 - The function ``get_offset_name`` has been dropped in favor of the ``.freqstr`` attribute for an offset (:issue:`11834`)
+- pandas no longer tests for compatibility with hdf5-files created with pandas < 0.11 (:issue:`17398`).
+
 
 
 .. _whatsnew_0210.performance:

pandas/tests/io/data/legacy_hdf/legacy_0.10.h5

@@ -4599,15 +4599,6 @@ def test_legacy_table_read(self):
                 expected = df2[df2.index > df2.index[2]]
                 assert_frame_equal(expected, result)
 
-    def test_legacy_0_10_read(self):
-        # legacy from 0.10
-        with catch_warnings(record=True):
-            path = tm.get_data_path('legacy_hdf/legacy_0.10.h5')
-            with ensure_clean_store(path, mode='r') as store:
-                str(store)
-                for k in store.keys():
-                    store.select(k)
-
     def test_legacy_0_11_read(self):
         # legacy from 0.11
         path = os.path.join('legacy_hdf', 'legacy_table_0.11.h5')
@@ -4627,54 +4618,6 @@ def test_copy(self):
 
         with catch_warnings(record=True):
 
-            def do_copy(f=None, new_f=None, keys=None,
-                        propindexes=True, **kwargs):
-                try:
-                    if f is None:
-                        f = tm.get_data_path(os.path.join('legacy_hdf',
-                                                          'legacy_0.10.h5'))
-
-                    store = HDFStore(f, 'r')
-
-                    if new_f is None:
-                        import tempfile
-                        fd, new_f = tempfile.mkstemp()
-
-                    tstore = store.copy(
-                        new_f, keys=keys, propindexes=propindexes, **kwargs)
-
-                    # check keys
-                    if keys is None:
-                        keys = store.keys()
-                    assert set(keys) == set(tstore.keys())
-
-                    # check indicies & nrows
-                    for k in tstore.keys():
-                        if tstore.get_storer(k).is_table:
-                            new_t = tstore.get_storer(k)
-                            orig_t = store.get_storer(k)
-
-                            assert orig_t.nrows == new_t.nrows
-
-                            # check propindixes
-                            if propindexes:
-                                for a in orig_t.axes:
-                                    if a.is_indexed:
-                                        assert new_t[a.name].is_indexed
-
-                finally:
-                    safe_close(store)
-                    safe_close(tstore)
-                    try:
-                        os.close(fd)
-                    except:
-                        pass
-                    safe_remove(new_f)
-
-            do_copy()
-            do_copy(keys=['/a', '/b', '/df1_mixed'])
-            do_copy(propindexes=False)
-
             # new table
             df = tm.makeDataFrame()