BUG: concat/append misc fixes

doc/source/whatsnew/v0.19.0.txt

@@ -1356,6 +1356,13 @@ Bug Fixes
 - Bug in ``DatetimeIndex``, which did not honour the ``copy=True`` (:issue:`13205`)
 - Bug in ``DatetimeIndex.is_normalized`` returns incorrectly for normalized date_range in case of local timezones (:issue:`13459`)
 
+- Bug in ``pd.concat`` and ``.append`` may coerces ``datetime64`` and ``timedelta`` to ``object`` dtype containing python built-in ``datetime`` or ``timedelta`` rather than ``Timestamp`` or ``Timedelta`` (:issue:`13626`)
+- Bug in ``PeriodIndex.append`` may raises ``AttributeError`` when the result is ``object`` dtype (:issue:`13221`)
+- Bug in ``CategoricalIndex.append`` may accept normal ``list`` (:issue:`13626`)
+- Bug in ``pd.concat`` and ``.append`` with the same timezone get reset to UTC (:issue:`7795`)
+- Bug in ``Series`` and ``DataFrame`` ``.append`` raises ``AmbiguousTimeError`` if data contains datetime near DST boundary (:issue:`13626`)
+
+
 - Bug in ``DataFrame.to_csv()`` in which float values were being quoted even though quotations were specified for non-numeric values only (:issue:`12922`, :issue:`13259`)
 - Bug in ``DataFrame.describe()`` raising ``ValueError`` with only boolean columns (:issue:`13898`)
 - Bug in ``MultiIndex`` slicing where extra elements were returned when level is non-unique (:issue:`12896`)

pandas/core/frame.py

@@ -4384,14 +4384,20 @@ def append(self, other, ignore_index=False, verify_integrity=False):
                 raise TypeError('Can only append a Series if ignore_index=True'
                                 ' or if the Series has a name')
 
-            index = None if other.name is None else [other.name]
+            if other.name is None:
+                index = None
+            else:
+                # other must have the same index name as self, otherwise
+                # index name will be reset
+                index = Index([other.name], name=self.index.name)
+
             combined_columns = self.columns.tolist() + self.columns.union(
                 other.index).difference(self.columns).tolist()
             other = other.reindex(combined_columns, copy=False)
             other = DataFrame(other.values.reshape((1, len(other))),
-                              index=index, columns=combined_columns)
+                              index=index,
+                              columns=combined_columns)
             other = other._convert(datetime=True, timedelta=True)
-
             if not self.columns.equals(combined_columns):
                 self = self.reindex(columns=combined_columns)
         elif isinstance(other, list) and not isinstance(other[0], DataFrame):

pandas/core/series.py

@@ -289,16 +289,18 @@ def _set_axis(self, axis, labels, fastpath=False):
 
         is_all_dates = labels.is_all_dates
         if is_all_dates:
-
             if not isinstance(labels,
                               (DatetimeIndex, PeriodIndex, TimedeltaIndex)):
                 try:
                     labels = DatetimeIndex(labels)
                     # need to set here becuase we changed the index
                     if fastpath:
                         self._data.set_axis(axis, labels)
-                except tslib.OutOfBoundsDatetime:
+                except (tslib.OutOfBoundsDatetime, ValueError):
+                    # labels may exceeds datetime bounds,
+                    # or not be a DatetimeIndex
                     pass
+
         self._set_subtyp(is_all_dates)
 
         object.__setattr__(self, '_index', labels)

pandas/indexes/base.py

@@ -1392,15 +1392,19 @@ def __getitem__(self, key):
         else:
             return result
 
-    def _ensure_compat_append(self, other):
+    def append(self, other):
         """
-        prepare the append
+        Append a collection of Index options together
+
+        Parameters
+        ----------
+        other : Index or list/tuple of indices
 
         Returns
         -------
-        list of to_concat, name of result Index
+        appended : Index
         """
-        name = self.name
+
         to_concat = [self]
 
         if isinstance(other, (list, tuple)):
@@ -1409,46 +1413,29 @@ def _ensure_compat_append(self, other):
             to_concat.append(other)
 
         for obj in to_concat:
-            if (isinstance(obj, Index) and obj.name != name and
-                    obj.name is not None):
-                name = None
-                break
+            if not isinstance(obj, Index):
+                raise TypeError('all inputs must be Index')
 
-        to_concat = self._ensure_compat_concat(to_concat)
-        to_concat = [x._values if isinstance(x, Index) else x
-                     for x in to_concat]
-        return to_concat, name
+        names = set([obj.name for obj in to_concat])
+        name = None if len(names) > 1 else self.name
 
-    def append(self, other):
-        """
-        Append a collection of Index options together
+        typs = _concat.get_dtype_kinds(to_concat)
 
-        Parameters
-        ----------
-        other : Index or list/tuple of indices
+        if 'category' in typs:
+            # if any of the to_concat is category
+            from pandas.indexes.category import CategoricalIndex
+            return CategoricalIndex._append_same_dtype(self, to_concat, name)
 
-        Returns
-        -------
-        appended : Index
-        """
-        to_concat, name = self._ensure_compat_append(other)
-        attribs = self._get_attributes_dict()
-        attribs['name'] = name
-        return self._shallow_copy_with_infer(
-            np.concatenate(to_concat), **attribs)
-
-    @staticmethod
-    def _ensure_compat_concat(indexes):
-        from pandas.tseries.api import (DatetimeIndex, PeriodIndex,
-                                        TimedeltaIndex)
-        klasses = DatetimeIndex, PeriodIndex, TimedeltaIndex
-
-        is_ts = [isinstance(idx, klasses) for idx in indexes]
+        if len(typs) == 1:
+            return self._append_same_dtype(to_concat, name=name)
+        return _concat._concat_index_asobject(to_concat, name=name)
 
-        if any(is_ts) and not all(is_ts):
-            return [_maybe_box(idx) for idx in indexes]
-
-        return indexes
+    def _append_same_dtype(self, to_concat, name):
+        """
+        Concatenate to_concat which has the same class
+        """
+        # must be overrided in specific classes
+        return _concat._concat_index_asobject(to_concat, name)
 
     _index_shared_docs['take'] = """
         return a new %(klass)s of the values selected by the indices
@@ -3634,16 +3621,6 @@ def _ensure_has_len(seq):
         return seq
 
 
-def _maybe_box(idx):
-    from pandas.tseries.api import DatetimeIndex, PeriodIndex, TimedeltaIndex
-    klasses = DatetimeIndex, PeriodIndex, TimedeltaIndex
-
-    if isinstance(idx, klasses):
-        return idx.asobject
-
-    return idx
-
-
 def _trim_front(strings):
     """
     Trims zeros and decimal points

pandas/indexes/category.py

@@ -569,26 +569,17 @@ def insert(self, loc, item):
         codes = np.concatenate((codes[:loc], code, codes[loc:]))
         return self._create_from_codes(codes)
 
-    def append(self, other):
+    def _append_same_dtype(self, to_concat, name):
         """
-        Append a collection of CategoricalIndex options together
-
-        Parameters
-        ----------
-        other : Index or list/tuple of indices
-
-        Returns
-        -------
-        appended : Index
-
-        Raises
-        ------
+        Concatenate to_concat which has the same class
         ValueError if other is not in the categories
         """
-        to_concat, name = self._ensure_compat_append(other)
         to_concat = [self._is_dtype_compat(c) for c in to_concat]
         codes = np.concatenate([c.codes for c in to_concat])
-        return self._create_from_codes(codes, name=name)
+        result = self._create_from_codes(codes, name=name)
+        # if name is None, _create_from_codes sets self.name
+        result.name = name
+        return result
 
     @classmethod
     def _add_comparison_methods(cls):

pandas/tests/indexes/test_category.py

@@ -271,12 +271,12 @@ def test_append(self):
             lambda: ci.append(ci.values.reorder_categories(list('abc'))))
 
         # with objects
-        result = ci.append(['c', 'a'])
+        result = ci.append(Index(['c', 'a']))
         expected = CategoricalIndex(list('aabbcaca'), categories=categories)
         tm.assert_index_equal(result, expected, exact=True)
 
         # invalid objects
-        self.assertRaises(TypeError, lambda: ci.append(['a', 'd']))
+        self.assertRaises(TypeError, lambda: ci.append(Index(['a', 'd'])))
 
     def test_insert(self):
 

pandas/tests/indexes/test_multi.py

@@ -6,8 +6,8 @@
 import re
 import warnings
 
-from pandas import (DataFrame, date_range, MultiIndex, Index, CategoricalIndex,
-                    compat)
+from pandas import (DataFrame, date_range, period_range, MultiIndex, Index,
+                    CategoricalIndex, compat)
 from pandas.core.common import PerformanceWarning
 from pandas.indexes.base import InvalidIndexError
 from pandas.compat import range, lrange, u, PY3, long, lzip
@@ -769,6 +769,40 @@ def test_append(self):
         result = self.index.append([])
         self.assertTrue(result.equals(self.index))
 
+    def test_append_mixed_dtypes(self):
+        # GH 13660
+        dti = date_range('2011-01-01', freq='M', periods=3,)
+        dti_tz = date_range('2011-01-01', freq='M', periods=3, tz='US/Eastern')
+        pi = period_range('2011-01', freq='M', periods=3)
+
+        mi = MultiIndex.from_arrays([[1, 2, 3],
+                                     [1.1, np.nan, 3.3],
+                                     ['a', 'b', 'c'],
+                                     dti, dti_tz, pi])
+        self.assertEqual(mi.nlevels, 6)
+
+        res = mi.append(mi)
+        exp = MultiIndex.from_arrays([[1, 2, 3, 1, 2, 3],
+                                     [1.1, np.nan, 3.3, 1.1, np.nan, 3.3],
+                                     ['a', 'b', 'c', 'a', 'b', 'c'],
+                                     dti.append(dti),
+                                     dti_tz.append(dti_tz),
+                                     pi.append(pi)])
+        tm.assert_index_equal(res, exp)
+
+        other = MultiIndex.from_arrays([['x', 'y', 'z'], ['x', 'y', 'z'],
+                                        ['x', 'y', 'z'], ['x', 'y', 'z'],
+                                        ['x', 'y', 'z'], ['x', 'y', 'z']])
+
+        res = mi.append(other)
+        exp = MultiIndex.from_arrays([[1, 2, 3, 'x', 'y', 'z'],
+                                     [1.1, np.nan, 3.3, 'x', 'y', 'z'],
+                                     ['a', 'b', 'c', 'x', 'y', 'z'],
+                                     dti.append(pd.Index(['x', 'y', 'z'])),
+                                     dti_tz.append(pd.Index(['x', 'y', 'z'])),
+                                     pi.append(pd.Index(['x', 'y', 'z']))])
+        tm.assert_index_equal(res, exp)
+
     def test_get_level_values(self):
         result = self.index.get_level_values(0)
         expected = Index(['foo', 'foo', 'bar', 'baz', 'qux', 'qux'],

pandas/tests/types/test_concat.py

@@ -0,0 +1,86 @@
+# -*- coding: utf-8 -*-
+
+import nose
+import pandas as pd
+import pandas.types.concat as _concat
+import pandas.util.testing as tm
+
+
+class TestConcatCompat(tm.TestCase):
+
+    _multiprocess_can_split_ = True
+
+    def check_concat(self, to_concat, exp):
+        for klass in [pd.Index, pd.Series]:
+            to_concat_klass = [klass(c) for c in to_concat]
+            res = _concat.get_dtype_kinds(to_concat_klass)
+            self.assertEqual(res, set(exp))
+
+    def test_get_dtype_kinds(self):
+        to_concat = [['a'], [1, 2]]
+        self.check_concat(to_concat, ['i', 'object'])
+
+        to_concat = [[3, 4], [1, 2]]
+        self.check_concat(to_concat, ['i'])
+
+        to_concat = [[3, 4], [1, 2.1]]
+        self.check_concat(to_concat, ['i', 'f'])
+
+    def test_get_dtype_kinds_datetimelike(self):
+        to_concat = [pd.DatetimeIndex(['2011-01-01']),
+                     pd.DatetimeIndex(['2011-01-02'])]
+        self.check_concat(to_concat, ['datetime'])
+
+        to_concat = [pd.TimedeltaIndex(['1 days']),
+                     pd.TimedeltaIndex(['2 days'])]
+        self.check_concat(to_concat, ['timedelta'])
+
+    def test_get_dtype_kinds_datetimelike_object(self):
+        to_concat = [pd.DatetimeIndex(['2011-01-01']),
+                     pd.DatetimeIndex(['2011-01-02'], tz='US/Eastern')]
+        self.check_concat(to_concat,
+                          ['datetime', 'datetime64[ns, US/Eastern]'])
+
+        to_concat = [pd.DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'),
+                     pd.DatetimeIndex(['2011-01-02'], tz='US/Eastern')]
+        self.check_concat(to_concat,
+                          ['datetime64[ns, Asia/Tokyo]',
+                           'datetime64[ns, US/Eastern]'])
+
+        # timedelta has single type
+        to_concat = [pd.TimedeltaIndex(['1 days']),
+                     pd.TimedeltaIndex(['2 hours'])]
+        self.check_concat(to_concat, ['timedelta'])
+
+        to_concat = [pd.DatetimeIndex(['2011-01-01'], tz='Asia/Tokyo'),
+                     pd.TimedeltaIndex(['1 days'])]
+        self.check_concat(to_concat,
+                          ['datetime64[ns, Asia/Tokyo]', 'timedelta'])
+
+    def test_get_dtype_kinds_period(self):
+        # because we don't have Period dtype (yet),
+        # Series results in object dtype
+        to_concat = [pd.PeriodIndex(['2011-01'], freq='M'),
+                     pd.PeriodIndex(['2011-01'], freq='M')]
+        res = _concat.get_dtype_kinds(to_concat)
+        self.assertEqual(res, set(['period[M]']))
+
+        to_concat = [pd.Series([pd.Period('2011-01', freq='M')]),
+                     pd.Series([pd.Period('2011-02', freq='M')])]
+        res = _concat.get_dtype_kinds(to_concat)
+        self.assertEqual(res, set(['object']))
+
+        to_concat = [pd.PeriodIndex(['2011-01'], freq='M'),
+                     pd.PeriodIndex(['2011-01'], freq='D')]
+        res = _concat.get_dtype_kinds(to_concat)
+        self.assertEqual(res, set(['period[M]', 'period[D]']))
+
+        to_concat = [pd.Series([pd.Period('2011-01', freq='M')]),
+                     pd.Series([pd.Period('2011-02', freq='D')])]
+        res = _concat.get_dtype_kinds(to_concat)
+        self.assertEqual(res, set(['object']))
+
+
+if __name__ == '__main__':
+    nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],
+                   exit=False)

pandas/tools/pivot.py

@@ -523,6 +523,9 @@ def _normalize(table, normalize, margins):
         column_margin = table.loc[:, 'All'].drop('All')
         index_margin = table.loc['All', :].drop('All')
         table = table.drop('All', axis=1).drop('All')
+        # to keep index and columns names
+        table_index_names = table.index.names
+        table_columns_names = table.columns.names
 
         # Normalize core
         table = _normalize(table, normalize=normalize, margins=False)
@@ -550,6 +553,9 @@ def _normalize(table, normalize, margins):
         else:
             raise ValueError("Not a valid normalize argument")
 
+        table.index.names = table_index_names
+        table.columns.names = table_columns_names
+
     else:
         raise ValueError("Not a valid margins argument")