fixup! API: Have MultiIndex constructors return MI

Author: TomAugspurger

pandas/core/frame.py

@@ -68,7 +68,7 @@
                                 standardize_mapping)
 from pandas.core.generic import NDFrame, _shared_docs
 from pandas.core.index import (Index, MultiIndex, _ensure_index,
-                               _index_from_sequences)
+                               _ensure_index_from_sequences)
 from pandas.core.indexing import (maybe_droplevels, convert_to_index_sliceable,
                                   check_bool_indexer)
 from pandas.core.internals import (BlockManager,
@@ -1157,8 +1157,8 @@ def from_records(cls, data, index=None, exclude=None, columns=None,
                 try:
                     to_remove = [arr_columns.get_loc(field) for field in index]
                     index_data = [arrays[i] for i in to_remove]
-                    result_index = _index_from_sequences(index_data,
-                                                         names=index)
+                    result_index = _ensure_index_from_sequences(index_data,
+                                                                names=index)
 
                     exclude.update(index)
                 except Exception:
@@ -3001,7 +3001,7 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
                     to_remove.append(col)
             arrays.append(level)
 
-        index = _index_from_sequences(arrays, names)
+        index = _ensure_index_from_sequences(arrays, names)
 
         if verify_integrity and not index.is_unique:
             duplicates = index.get_duplicates()

pandas/core/indexes/api.py

@@ -1,7 +1,7 @@
 from pandas.core.indexes.base import (Index,
                                       _new_Index,
                                       _ensure_index,
-                                      _index_from_sequences,
+                                      _ensure_index_from_sequences,
                                       _get_na_value,
                                       InvalidIndexError)  # noqa
 from pandas.core.indexes.category import CategoricalIndex  # noqa
@@ -25,7 +25,7 @@
            'InvalidIndexError', 'TimedeltaIndex',
            'PeriodIndex', 'DatetimeIndex',
            '_new_Index', 'NaT',
-           '_ensure_index', '_index_from_sequences', '_get_na_value',
+           '_ensure_index', '_ensure_index_from_sequences', '_get_na_value',
            '_get_combined_index',
            '_get_objs_combined_axis', '_union_indexes',
            '_get_consensus_names',

pandas/core/indexes/base.py

@@ -4012,19 +4012,28 @@ def invalid_op(self, other=None):
 Index._add_comparison_methods()
 
 
-def _index_from_sequences(sequences, names=None):
+def _ensure_index_from_sequences(sequences, names=None):
     """Construct an index from sequences of data.
 
-    A single sequence returns an Index.
-    Many sequences returns a MultiIndex.
+    A single sequence returns an Index. Many sequences returns a
+    MultiIndex.
+
+    Parameters
+    ----------
+    sequences : sequence of sequences
+    names : sequence of str
+
+    Returns
+    -------
+    index : Index or MultiIndex
 
     Examples
     --------
-
-    >>> _index_from_sequences([[1, 2, 3]], names=['name'])
+    >>> _ensure_index_from_sequences([[1, 2, 3]], names=['name'])
     Int64Index([1, 2, 3], dtype='int64', name='name')
 
-    >>> _index_from_sequences([['a', 'a'], ['a', 'b']], names=['L1', 'L2'])
+    >>> _ensure_index_from_sequences([['a', 'a'], ['a', 'b']],
+                                     names=['L1', 'L2'])
     MultiIndex(levels=[['a'], ['a', 'b']],
                labels=[[0, 0], [0, 1]],
                names=['L1', 'L2'])
@@ -4040,6 +4049,31 @@ def _index_from_sequences(sequences, names=None):
 
 
 def _ensure_index(index_like, copy=False):
+    """
+    Ensure that we have an index from some index-like object
+
+    Parameters
+    ----------
+    index : sequence
+        An Index or other sequence
+    copy : bool
+
+    Returns
+    -------
+    index : Index or MultiIndex
+
+    Examples
+    --------
+    >>> _ensure_index(['a', 'b'])
+    Index(['a', 'b'], dtype='object')
+
+    >>> _ensure_index([('a', 'a'),  ('b', 'c')])
+    Index([('a', 'a'), ('b', 'c')], dtype='object')
+
+    >>> _ensure_index([['a', 'a'], ['b', 'c']])
+    MultiIndex(levels=[['a'], ['b', 'c']],
+               labels=[[0, 0], [0, 1]])
+    """
     if isinstance(index_like, Index):
         if copy:
             index_like = index_like.copy()

pandas/core/reshape/reshape.py

@@ -312,6 +312,7 @@ def _unstack_multiple(data, clocs):
                                          xnull=False)
 
     if rlocs == []:
+        # Everything is in clocs, so the dummy df has a regular index
         dummy_index = Index(obs_ids, name='__placeholder__')
     else:
         dummy_index = MultiIndex(levels=rlevels + [obs_ids],
@@ -450,6 +451,8 @@ def _slow_pivot(index, columns, values):
 def unstack(obj, level, fill_value=None):
     if isinstance(level, (tuple, list)):
         if len(level) == 1:
+            # unstack_multiple only handles MultiIndexes,
+            # and isn't needed for a single level
             level = level[0]
         else:
             return _unstack_multiple(obj, level)

pandas/core/strings.py

@@ -1454,6 +1454,8 @@ def cons_row(x):
                 result = list(result)
                 out = MultiIndex.from_tuples(result, names=name)
                 if out.nlevels == 1:
+                    # We had all tuples of length-one, which are
+                    # better represented as a regular Index.
                     out = out.get_level_values(0)
                 return out
             else:

pandas/io/parsers.py

@@ -24,7 +24,7 @@
 from pandas.core.dtypes.missing import isna
 from pandas.core.dtypes.cast import astype_nansafe
 from pandas.core.index import (Index, MultiIndex, RangeIndex,
-                               _index_from_sequences)
+                               _ensure_index_from_sequences)
 from pandas.core.series import Series
 from pandas.core.frame import DataFrame
 from pandas.core.categorical import Categorical
@@ -1446,15 +1446,7 @@ def _agg_index(self, index, try_parse_dates=True):
             arrays.append(arr)
 
         names = self.index_names
-        index = _index_from_sequences(arrays, names)
-        if len(arrays) > 1:
-            index = MultiIndex.from_arrays(arrays, names=self.index_names)
-        else:
-            if self.index_names is None:
-                name = None
-            else:
-                name = self.index_names[0]
-            index = Index(arrays[0], name=name)
+        index = _ensure_index_from_sequences(arrays, names)
 
         return index
 
@@ -1818,7 +1810,7 @@ def read(self, nrows=None):
                                                  try_parse_dates=True)
                 arrays.append(values)
 
-            index = _index_from_sequences(arrays)
+            index = _ensure_index_from_sequences(arrays)
 
             if self.usecols is not None:
                 names = self._filter_usecols(names)
@@ -3149,7 +3141,7 @@ def _get_empty_meta(columns, index_col, index_names, dtype=None):
         index = Index([])
     else:
         data = [Series([], dtype=dtype[name]) for name in index_names]
-        index = _index_from_sequences(data, names=index_names)
+        index = _ensure_index_from_sequences(data, names=index_names)
         index_col.sort()
         for i, n in enumerate(index_col):
             columns.pop(n - i)

pandas/tests/indexes/test_base.py

@@ -17,7 +17,7 @@
                     DataFrame, Float64Index, Int64Index,
                     CategoricalIndex, DatetimeIndex, TimedeltaIndex,
                     PeriodIndex, isna)
-from pandas.core.index import _get_combined_index, _index_from_sequences
+from pandas.core.index import _get_combined_index, _ensure_index_from_sequences
 from pandas.util.testing import assert_almost_equal
 from pandas.compat.numpy import np_datetime64_compat
 
@@ -2125,6 +2125,6 @@ class TestIndexUtils(object):
          MultiIndex([['a'], ['c', 'd']], [[0, 0], [0, 1]],
                     names=['L1', 'L2'])),
     ])
-    def test_index_from_sequences(self, data, names, expected):
-        result = _index_from_sequences(data, names)
+    def test_ensure_index_from_sequences(self, data, names, expected):
+        result = _ensure_index_from_sequences(data, names)
         tm.assert_index_equal(result, expected)

pandas/util/testing.py

@@ -1909,6 +1909,7 @@ def keyfunc(x):
 
     # convert tuples to index
     if nentries == 1:
+        # we have a single level of tuples, i.e. a regular Index
         index = Index(tuples[0], name=names[0])
     elif nlevels == 1:
         name = None if names is None else names[0]