Update doctests

Author: avinashpancham

pandas/io/sql.py

@@ -493,36 +493,51 @@ def read_sql(
     ...                   columns=['int_column', 'date_column'])
     >>> df.to_sql('test_data', conn)
 
-    >>> pd.read_sql('SELECT * FROM test_data', con)
+    >>> pd.read_sql('SELECT int_column, date_column FROM test_data', conn)
+       int_column date_column
+    0           0    10/11/12
+    1           1    12/11/10
 
-    >>> pd.read_sql('table_name', 'postgres:///db_name')  # doctest:+SKIP
+    >>> pd.read_sql('test_data', 'postgres:///db_name')  # doctest:+SKIP
 
     Apply dateparsing to columns through the ``parse_dates`` argument
 
-    >>> pd.read_sql('SELECT * FROM test_data',
+    >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
     ...             parse_dates=["date_column"])
+           int_column date_column
+    0           0  2012-10-11
+    1           1  2010-12-11
 
     The ``parse_dates`` argument calls ``pd.to_datetime`` on the provided columns.
     Custom argument values for applying ``pd.to_datetime`` on a column are specified
     via a dictionary format:
     1. Ignore errors while parsing the values of "date_column"
 
-    >>> pd.read_sql('SELECT * FROM test_data',
+    >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
-    ...             parse_dates={"date_column": {"errors": "ignore"})
+    ...             parse_dates={"date_column": {"errors": "ignore"}})
+           int_column date_column
+    0           0  2012-10-11
+    1           1  2010-12-11
 
     2. Apply a dayfirst dateparsing order on the values of "date_column"
 
-    >>> pd.read_sql('SELECT * FROM test_data',
+    >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
-    ...             parse_dates={"date_column": {"dayfirst": True})
+    ...             parse_dates={"date_column": {"dayfirst": True}})
+       int_column date_column
+    0           0  2012-11-10
+    1           1  2010-11-12
 
     3. Apply custom formatting when dateparsing the values of "date_column"
 
-    >>> pd.read_sql('SELECT * FROM test_data',
+    >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
-    ...             parse_dates={"date_column": {"format": "%d/%m/%Y"})
+    ...             parse_dates={"date_column": {"format": "%d/%m/%y"}})
+           int_column date_column
+    0           0  2012-11-10
+    1           1  2010-11-12
     """
     pandas_sql = pandasSQL_builder(con)