fixup

Author: kernc

pandas/core/frame.py

@@ -740,9 +740,9 @@ def iterrows(self):
         iteritems : Iterate over (column name, Series) pairs.
 
         """
-        iloc = self.iloc
+        row_at = self.iloc.__getitem__
         for i, k in enumerate(self.index):
-            yield k, iloc[i]
+            yield k, row_at(i)
 
     def itertuples(self, index=True, name="Pandas"):
         """
@@ -2004,9 +2004,7 @@ def set_value(self, index, col, value, takeable=False):
 
         Returns
         -------
-        frame : DataFrame
-            If label pair is contained, will be reference to calling DataFrame,
-            otherwise a new object
+        self : DataFrame
         """
         warnings.warn("set_value is deprecated and will be removed "
                       "in a future release. Please use "

pandas/core/indexing.py

@@ -526,10 +526,10 @@ def setter(item, v):
                     # set the item, possibly having a dtype change
                     s._consolidate_inplace()
                     s = s.copy()
-                    if is_sparse(s):
-                        s.set_value(pi, v, takeable=is_list_like(pi))
-                    else:
-                        s._data = s._data.setitem(indexer=pi, value=v)
+                    # if is_sparse(s):
+                    #     s.set_value(pi, v, takeable=is_list_like(pi))
+                    # else:
+                    s._data = s._data.setitem(indexer=pi, value=v)  # TODO THIS USE THIS
                     s._maybe_update_cacher(clear=True)
 
                 # reset the sliced object if unique

pandas/core/internals.py

@@ -879,6 +879,9 @@ def _is_empty_indexer(indexer):
         if _is_empty_indexer(indexer):
             pass
 
+        elif is_sparse(values):
+            values = values.set_values(indexer, value)
+
         # setting a single element for each dim and with a rhs that could
         # be say a list
         # GH 6043
@@ -1760,9 +1763,12 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
         # use block's copy logic.
         # .values may be an Index which does shallow copy by default
         new_values = self.values if inplace else self.copy().values
-        new_values = new_values.to_dense()
         new_values, _, new, _ = self._try_coerce_args(new_values, new)
 
+        # Cannot modify a SparseArray
+        if is_sparse(new_values):
+            new_values = new_values.to_dense()
+
         if isinstance(new, np.ndarray) and len(new) == len(mask):
             new = new[mask]
 
@@ -2805,8 +2811,12 @@ def _astype(self, dtype, copy=False, errors='raise', values=None,
         return self.make_block_same_class(values=values,
                                           placement=self.mgr_locs)
 
+    def _can_hold_element(self, element):
+        return np.issubdtype(np.asanyarray(element).dtype,
+                             self.sp_values.dtype)
+
     def _try_coerce_result(self, result):
-        if not is_sparse(result):
+        if np.ndim(result) > 0 and not is_sparse(result):
             result = SparseArray(result, kind=self.kind,
                                  fill_value=self.fill_value, dtype=self.dtype)
         return result

pandas/core/sparse/array.py

@@ -387,6 +387,39 @@ def get_values(self, fill=None):
         """ return a dense representation """
         return self.to_dense(fill=fill)
 
+    def set_values(self, indexer, value):
+        """
+        Return new SparseArray with indexed values set to `value`.
+
+        Returns
+        -------
+        SparseArray
+            A new sparse array with indexer positions filled with value.
+        """
+        # If indexer is not a single int position, easiest to handle via dense
+        if not is_scalar(indexer):
+            values = self.to_dense()
+            values[indexer] = value
+            return SparseArray(values, kind=self.kind,
+                               fill_value=self.fill_value)
+
+        # If label already in sparse index, just switch the value on a copy
+        idx = self.sp_index.lookup(indexer)
+        if idx != -1:
+            obj = self.copy()
+            obj.sp_values[idx] = value
+            return obj
+
+        indices = self.sp_index.to_int_index().indices
+        pos = np.searchsorted(indices, indexer)
+
+        indices = np.insert(indices, pos, indexer)
+        sp_values = np.insert(self.sp_values, pos, value)
+
+        return SparseArray(
+            sp_values, fill_value=self.fill_value,
+            sparse_index=_make_index(self.sp_index.length, indices, self.kind))
+
     def to_dense(self, fill=None):
         """
         Convert SparseArray to a NumPy array.

pandas/core/sparse/frame.py

@@ -465,6 +465,29 @@ def _get_value(self, index, col, takeable=False):
         return series._get_value(index, takeable=takeable)
     _get_value.__doc__ = get_value.__doc__
 
+    def set_value(self, index, col, value, takeable=False):
+        """
+        Put single value at passed column and index
+
+        Parameters
+        ----------
+        index : row label
+        col : column label
+        value : scalar value
+        takeable : interpret the index/col as indexers, default False
+
+        Notes
+        -----
+        This method *always* returns a new object for backwards compatibility.
+
+        Returns
+        -------
+        frame : DataFrame
+        """
+        self = self.copy(deep=False)
+        return super(SparseDataFrame, self).set_value(index, col, value,
+                                                      takeable=takeable)
+
     def _slice(self, slobj, axis=0, kind=None):
         if axis == 0:
             new_index = self.index[slobj]

pandas/core/sparse/series.py

@@ -10,7 +10,8 @@
 
 from pandas.core.dtypes.missing import isna, notna
 from pandas.core.dtypes.common import is_scalar, is_sparse
-from pandas.core.common import _values_from_object, _maybe_match_name
+from pandas.core.common import _values_from_object, _maybe_match_name, \
+    PerformanceWarning
 
 from pandas.compat.numpy import function as nv
 from pandas.core.index import Index, _ensure_index, InvalidIndexError
@@ -22,7 +23,6 @@
 import pandas.core.common as com
 import pandas.core.ops as ops
 import pandas._libs.index as _index
-from pandas.errors import PerformanceWarning
 from pandas.util._decorators import Appender
 
 from pandas.core.sparse.array import (
@@ -604,6 +604,7 @@ def _set_value(self, label, value, takeable=False):
                              fill_value=self.fill_value)
         self._data = SingleBlockManager(values, index)
         self._index = index
+        return self
     _set_value.__doc__ = set_value.__doc__
 
     def _set_values(self, key, value):