diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 743d623ee5e44..907959c42323e 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -241,17 +241,47 @@ class DataFrame(NDFrame):
         Column labels to use for resulting frame. Will default to
         np.arange(n) if no column labels are provided
     dtype : dtype, default None
-        Data type to force, otherwise infer
+        Data type to force. Only a single dtype is allowed. If None, infer
     copy : boolean, default False
         Copy data from inputs. Only affects DataFrame / 2d ndarray input
 
     Examples
     --------
-    >>> d = {'col1': ts1, 'col2': ts2}
-    >>> df = DataFrame(data=d, index=index)
-    >>> df2 = DataFrame(np.random.randn(10, 5))
-    >>> df3 = DataFrame(np.random.randn(10, 5),
-    ...                 columns=['a', 'b', 'c', 'd', 'e'])
+    Constructing DataFrame from a dictionary.
+
+    >>> d = {'col1': [1, 2], 'col2': [3, 4]}
+    >>> df = pd.DataFrame(data=d)
+    >>> df
+       col1  col2
+    0     1     3
+    1     2     4
+
+    Notice that the inferred dtype is int64.
+
+    >>> df.dtypes
+    col1    int64
+    col2    int64
+    dtype: object
+
+    To enforce a single dtype:
+
+    >>> df = pd.DataFrame(data=d, dtype=np.int8)
+    >>> df.dtypes
+    col1    int8
+    col2    int8
+    dtype: object
+
+    Constructing DataFrame from numpy ndarray:
+
+    >>> df2 = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)),
+    ...                    columns=['a', 'b', 'c', 'd', 'e'])
+    >>> df2
+        a   b   c   d   e
+    0   2   8   8   3   4
+    1   4   2   9   0   9
+    2   1   0   7   8   0
+    3   5   1   7   1   3
+    4   6   0   2   4   2
 
     See also
     --------