fixed list-like handling

dios/dios.py

@@ -320,15 +320,11 @@ class DictOfSeries:
             assert isinstance(data, self.__class__), f"getitem returned data of type {type(data)}"
 
             # special cases
-            # (I)   Dios (ok)
-            # (II)  list-like (fail)
-            # (III) nested lists-like (ok)
-            # NOTE: pd.Series considered list-like and also fail
-            # if they dont hold list-likes obj
             if _is_dios_like(value):
                 self._setitem_dios(data, value)
+            # NOTE: pd.Series also considered list-like
             elif _is_list_like(value):
-                self._setitem_nested_listlike(data, value)
+                self._setitem_listlike(data, value)
 
             # default case
             else:
@@ -337,15 +333,12 @@ class DictOfSeries:
                     s[:] = value
                     self._data.at[k][s.index] = s
 
-    def _setitem_nested_listlike(self, data, value):
-        # nested series, eg. `pd.Series([[1,2], [4,4]], dtype='O')`
+    def _setitem_listlike(self, data, value):
+
         value = value.values if isinstance(value, pd.Series) else value
-        if not _is_nested_list_like(value):
-            raise ValueError(f"1D array-like value could not be broadcast to "
-                             f"indexing result of shape (.., {len(data.columns)})")
 
         if len(value) != len(data.columns):
-            raise ValueError(f"array-like value of shape (.., {len(value)}) could "
+            raise ValueError(f"array-like value of length {len(value)} could "
                              f"not be broadcast to indexing result of shape "
                              f"(.., {len(data.columns)})")
 

dios/indexer.py

@@ -6,6 +6,7 @@ from .dios import (
     _is_bool_dios_like,
     _is_iterator)
 
+import numpy as np
 import pandas as pd
 import pandas.core.common as ccom
 import pandas.core.dtypes.common as dcom
@@ -50,16 +51,16 @@ class _Indexer:
         data = getattr(self._data, xloc)[colkey]
 
         def lenerr(vallen, datlen):
-            return ValueError(f"shape mismatch: values array of shape (.., {vallen}) could "
+            return ValueError(f"shape mismatch: value array of shape (.., {vallen}) could "
                               f"not be broadcast to indexing result of shape (.., {datlen})")
 
-        def set_(data, value, iter=False):
+        def set_(data, value, iter=False, align=False):
+            assert not (iter and align), "only one can be True"
             c = "?"
             try:
                 for i, c in enumerate(data.index):
                     dat = data.at[c]
                     dat_xloc = getattr(dat, xloc)
-                    val = value[i] if iter else value
 
                     # a hashable rowkey (.xloc[3, c] = value) :
                     #   loc:  rowkey not present in self -> prevent that .loc create a new item
@@ -78,21 +79,23 @@ class _Indexer:
                     elif len(dat_xloc[rowkey]) == 0:
                         continue
 
+                    # unpack the value if necessary
+                    if iter:
+                        val = value[i]
+                    elif align:
+                        val = value[c] if c in value else np.nan
+                    else:
+                        val = value
+
                     dat_xloc[rowkey] = val
 
             except Exception as e:
                 raise type(e)(f"failed for column {c}: " + str(e)) from e
 
         if _is_dios_like(value):
-            if len(value) == 1:
-                value = value.squeeze()
-            elif len(value) != len(data):
-                raise lenerr(len(value), len(data))
-            else:
-                value = [value[c] for c in value.columns]
-                # fall trough to nested list
+            set_(data, value, align=True)
 
-        if _is_nested_list_like(value):
+        elif _is_list_like(value):
             if len(value) != len(data):
                 raise lenerr(len(value), len(data))
             set_(data, value, iter=True)
@@ -314,7 +317,7 @@ class _aLocIndexer(_Indexer):
                 dat.loc[rk] = value
 
         # no align, no merci
-        elif _is_nested_list_like(value):
+        elif _is_list_like(value):
             if len(colkeys) != len(value):
                 raise ValueError(f"shape mismatch: values array of shape "
                                  f"(.., {len(value)}) could not "