diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 4e7a5ebdf6f67..d47cb05285370 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -3079,6 +3079,50 @@ def dropna(self, axis=0, how='any', thresh=None, subset=None,
         Returns
         -------
         dropped : DataFrame
+
+        Examples
+        --------
+        >>> df = pd.DataFrame([[np.nan, 2, np.nan, 0], [3, 4, np.nan, 1],
+        ...                    [np.nan, np.nan, np.nan, 5]],
+        ...                   columns=list('ABCD'))
+        >>> df
+             A    B   C  D
+        0  NaN  2.0 NaN  0
+        1  3.0  4.0 NaN  1
+        2  NaN  NaN NaN  5
+
+        Drop the columns where all elements are nan:
+
+        >>> df.dropna(axis=1, how='all')
+             A    B  D
+        0  NaN  2.0  0
+        1  3.0  4.0  1
+        2  NaN  NaN  5
+
+        Drop the columns where any of the elements is nan
+
+        >>> df.dropna(axis=1, how='any')
+           D
+        0  0
+        1  1
+        2  5
+
+        Drop the rows where all of the elements are nan
+        (there is no row to drop, so df stays the same):
+
+        >>> df.dropna(axis=0, how='all')
+             A    B   C  D
+        0  NaN  2.0 NaN  0
+        1  3.0  4.0 NaN  1
+        2  NaN  NaN NaN  5
+
+        Keep only the rows with at least 2 non-na values:
+
+        >>> df.dropna(thresh=2)
+             A    B   C  D
+        0  NaN  2.0 NaN  0
+        1  3.0  4.0 NaN  1
+
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
         if isinstance(axis, (tuple, list)):