Merge branch 'issue529'

trackpy/framewise_data.py

@@ -248,13 +248,14 @@ def __init__(self, filename, key='FrameData', mode='a', t_column='frame',
         self._t_column = t_column
         self.store = pd.HDFStore(self.filename, mode, **kwargs)
 
-        with pd.get_store(self.filename) as store:
-            try:
-                store[self.key]
-            except KeyError:
-                pass
-            else:
-                self._validate_node(use_tabular_copy)
+        store = pd.HDFStore(self.filename)
+        try:
+            store[self.key]
+        except KeyError:
+            pass
+        else:
+            self._validate_node(use_tabular_copy)
+        store.close()
 
     @property
     def t_column(self):

trackpy/utils.py

@@ -313,7 +313,17 @@ def _pandas_sort_pre_017(df, by, *args, **kwargs):
     return df.sort(*args, columns=by, **kwargs)
 
 def _pandas_sort_post_017(df, by, *args, **kwargs):
-    """Use sort_values() to sort a DataFrame"""
+    """
+    Use sort_values() to sort a DataFrame
+    This raises a ValueError if the given value is both
+    a column and an index label, i.e.:
+    ValueError: 'frame' is both an index level and a column
+    label, which is ambiguous.
+    Because we usually sort by columns, we can rename
+    the index to supress the ValueError.
+    """
+    if df.index.name is not None and df.index.name in by:
+        df.index.name += '_index'
     return df.sort_values(*args, by=by, **kwargs)
 
 if is_pandas_since_017: