Remove unnecessary path

Author: sinhrks

pandas/core/internals.py

@@ -1192,7 +1192,7 @@ def handle_error(detail):
 
         # technically a broadcast error in numpy can 'work' by returning a
         # boolean False
-        if not isinstance(result, (np.ndarray, PeriodIndex)):
+        if not isinstance(result, np.ndarray):
             # differentiate between an invalid ndarray-ndarray comparison
             # and an invalid type comparison
             if isinstance(values, np.ndarray) and is_list_like(other):
@@ -1860,7 +1860,7 @@ def convert(self, *args, **kwargs):
             raise NotImplementedError
         by_item = True if 'by_item' not in kwargs else kwargs['by_item']
 
-        new_inputs = ['coerce', 'datetime', 'numeric', 'timedelta', 'period']
+        new_inputs = ['coerce', 'datetime', 'numeric', 'timedelta']
         new_style = False
         for kw in new_inputs:
             new_style |= kw in kwargs
@@ -2552,7 +2552,6 @@ def __init__(self, values, placement, ndim=2, **kwargs):
         dtype = kwargs.pop('dtype', None)
         if not isinstance(values, self._holder):
             # dtype contains freq info
-            print(values, dtype)
             values = self._holder(values, dtype=dtype)
 
         super(PeriodBlock, self).__init__(values, placement=placement,
@@ -2583,19 +2582,6 @@ def to_dense(self):
         # called from Series.get_values()
         return self.values.asobject
 
-    # def _try_fill(self, value):
-    #     """ if we are a NaT, return the actual fill value """
-    #     if value is tslib.NaT or np.array(isnull(value)).all():
-    #         value = tslib.iNaT
-    #     elif isinstance(value, Period):
-    #         # Period Nat can be handled here
-    #         value = value.ordinal
-    #     elif is_integer(value):
-    #         # regarded as ordinal
-    #         pass
-    #
-    #    return value
-
     def _try_coerce_args(self, values, other):
         """
         Coerce values and other to dtype 'i8'. NaN and NaT convert to

pandas/indexes/base.py

@@ -182,7 +182,7 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
                 from pandas.tseries.tdi import TimedeltaIndex
                 result = TimedeltaIndex(data, copy=copy, name=name, **kwargs)
                 if dtype is not None and _o_dtype == dtype:
-                    return result.asobject
+                    return Index(result.to_pytimedelta(), dtype=_o_dtype)
                 else:
                     return result
             elif is_period_dtype(data):
@@ -2273,7 +2273,6 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
             tolerance = self._convert_tolerance(tolerance)
 
         pself, ptarget = self._possibly_promote(target)
-
         if pself is not self or ptarget is not target:
             return pself.get_indexer(ptarget, method=method, limit=limit,
                                      tolerance=tolerance)
@@ -2299,6 +2298,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
             if limit is not None:
                 raise ValueError('limit argument only valid if doing pad, '
                                  'backfill or nearest reindexing')
+
             indexer = self._engine.get_indexer(target._values)
 
         return _ensure_platform_int(indexer)

pandas/io/pytables.py

@@ -2037,7 +2037,6 @@ def get_atom_period(self, block):
         return _tables().Int64Col(shape=block.shape[0])
 
     def set_atom_period(self, block, info, values=None):
-        print('set_atom_period')
         if values is None:
             values = block.values
         values = values.asi8.reshape(block.shape)