MAINT: Address final comments

Author: gfyoung

pandas/core/frame.py

@@ -1674,6 +1674,15 @@ def to_records(self, index=True, convert_datetime64=None,
         for i, v in enumerate(arrays):
             index = i
 
+            # When the names and arrays are collected, we
+            # first collect those in the DataFrame's index,
+            # followed by those in its columns.
+            #
+            # Thus, the total length of the array is:
+            # len(index_names) + len(DataFrame.columns).
+            #
+            # This check allows us to see whether we are
+            # handling a name / array in the index or column.
             if index < index_len:
                 dtype_mapping = index_dtypes
                 name = index_names[index]
@@ -1682,6 +1691,11 @@ def to_records(self, index=True, convert_datetime64=None,
                 dtype_mapping = column_dtypes
                 name = self.columns[index]
 
+            # We have a dictionary, so we get the data type
+            # associated with the index or column (which can
+            # be denoted by its name in the DataFrame or its
+            # position in DataFrame's array of indices or
+            # columns, whichever is applicable.
             if is_dict_like(dtype_mapping):
                 if name in dtype_mapping:
                     dtype_mapping = dtype_mapping[name]
@@ -1690,6 +1704,11 @@ def to_records(self, index=True, convert_datetime64=None,
                 else:
                     dtype_mapping = None
 
+            # If no mapping can be found, use the array's
+            # dtype attribute for formatting.
+            #
+            # A valid dtype must either be a type or
+            # string naming a type.
             if dtype_mapping is None:
                 formats.append(v.dtype)
             elif isinstance(dtype_mapping, (type, compat.string_types)):

pandas/tests/dtypes/test_inference.py

@@ -181,7 +181,7 @@ def test_is_dict_like_fails(ll):
 @pytest.mark.parametrize("has_keys", [True, False])
 @pytest.mark.parametrize("has_getitem", [True, False])
 @pytest.mark.parametrize("has_contains", [True, False])
-def test_is_dict_like_duct_type(has_keys, has_getitem, has_contains):
+def test_is_dict_like_duck_type(has_keys, has_getitem, has_contains):
     class DictLike(object):
         def __init__(self, d):
             self.d = d