DOC: several minor doc improvements

doc/source/indexing.rst

@@ -186,7 +186,7 @@ Attribute Access
 
 .. _indexing.attribute_access:
 
-You may access an index on a ``Series``, column on a ``DataFrame``, and a item on a ``Panel`` directly
+You may access an index on a ``Series``, column on a ``DataFrame``, and an item on a ``Panel`` directly
 as an attribute:
 
 .. ipython:: python
@@ -1513,7 +1513,7 @@ Compare these two access methods:
 These both yield the same results, so which should you use? It is instructive to understand the order
 of operations on these and why method 2 (``.loc``) is much preferred over method 1 (chained ``[]``)
 
-``dfmi['one']`` selects the first level of the columns and returns a data frame that is singly-indexed.
+``dfmi['one']`` selects the first level of the columns and returns a DataFrame that is singly-indexed.
 Then another python operation ``dfmi_with_one['second']`` selects the series indexed by ``'second'`` happens.
 This is indicated by the variable ``dfmi_with_one`` because pandas sees these operations as separate events.
 e.g. separate calls to ``__getitem__``, so it has to treat them as linear operations, they happen one after another.

pandas/core/strings.py

@@ -967,13 +967,14 @@ def str_get(arr, i):
 
 def str_decode(arr, encoding, errors="strict"):
     """
-    Decode character string in the Series/Index to unicode
-    using indicated encoding. Equivalent to :meth:`str.decode`.
+    Decode character string in the Series/Index using indicated encoding.
+    Equivalent to :meth:`str.decode` in python2 and :meth:`bytes.decode` in
+    python3.
 
     Parameters
     ----------
-    encoding : string
-    errors : string
+    encoding : str
+    errors : str, optional
 
     Returns
     -------
@@ -985,13 +986,13 @@ def str_decode(arr, encoding, errors="strict"):
 
 def str_encode(arr, encoding, errors="strict"):
     """
-    Encode character string in the Series/Index to some other encoding
-    using indicated encoding. Equivalent to :meth:`str.encode`.
+    Encode character string in the Series/Index using indicated encoding.
+    Equivalent to :meth:`str.encode`.
 
     Parameters
     ----------
-    encoding : string
-    errors : string
+    encoding : str
+    errors : str, optional
 
     Returns
     -------

pandas/tools/merge.py

@@ -792,7 +792,7 @@ def concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False,
         If True, do not use the index values along the concatenation axis. The
         resulting axis will be labeled 0, ..., n - 1. This is useful if you are
         concatenating objects where the concatenation axis does not have
-        meaningful indexing information. Note the the index values on the other
+        meaningful indexing information. Note the index values on the other
         axes are still respected in the join.
     copy : boolean, default True
         If False, do not copy data unnecessarily