REF: implement and use _as_1d_array

Author: toobaz

pandas/core/common.py

@@ -372,6 +372,26 @@ def intersection(*seqs):
     return type(seqs[0])(list(result))
 
 
+def _as_1d_array(values, dtype='object'):
+    """
+    Transform any list-like object in a 1-dimensional numpy array.
+
+    Parameters
+    ----------
+    values : any iterable which has a len()
+    dtype : dtype, default 'object'
+
+    Returns
+    -------
+    1-dimensional numpy array
+    """
+    # Making a 1D array that safely contains list-likes is a bit tricky
+    # in numpy, leading to the following
+    result = np.empty(len(values), dtype=dtype)
+    result[:] = values
+    return result
+
+
 def _asarray_tuplesafe(values, dtype=None):
     from pandas.core.index import Index
 
@@ -381,25 +401,17 @@ def _asarray_tuplesafe(values, dtype=None):
         return values.values
 
     if isinstance(values, list) and dtype in [np.object_, object]:
-        return lib.list_to_object_array(values)
+        return _as_1d_array(values)
 
     result = np.asarray(values, dtype=dtype)
 
     if issubclass(result.dtype.type, compat.string_types):
         result = np.asarray(values, dtype=object)
 
     if result.ndim == 2:
-        if isinstance(values, list):
-            return lib.list_to_object_array(values)
-        else:
-            # Making a 1D array that safely contains tuples is a bit tricky
-            # in numpy, leading to the following
-            try:
-                result = np.empty(len(values), dtype=object)
-                result[:] = values
-            except ValueError:
-                # we have a list-of-list
-                result[:] = [tuple(x) for x in values]
+        if hasattr(values, '__array__'):
+            values = [tuple(x) for x in values]
+        result = _as_1d_array(values)
 
     return result
 

pandas/core/series.py

@@ -41,6 +41,7 @@
 from pandas.core.common import (is_bool_indexer,
                                 _default_index,
                                 _asarray_tuplesafe,
+                                _as_1d_array,
                                 _values_from_object,
                                 _maybe_match_name,
                                 SettingWithCopyError,
@@ -3214,9 +3215,7 @@ def _try_cast(arr, take_fast_path):
 
     elif isinstance(data, (list, tuple)) and len(data) > 0:
         if all(is_list_like(item) for item in data):
-            # Ensure nested lists are not interpreted as further dimensions:
-            subarr = np.empty(len(data), dtype='object')
-            subarr[:] = data
+            subarr = _as_1d_array(data)
         elif dtype is not None:
             try:
                 subarr = _try_cast(data, False)