Update doctests

Author: avinashpancham

pandas/io/sql.py

@@ -478,45 +478,51 @@ def read_sql(
     -------
     DataFrame or Iterator[DataFrame]
 
+    See Also
+    --------
+    read_sql_table : Read SQL database table into a DataFrame.
+    read_sql_query : Read SQL query into a DataFrame.
+
     Examples
     --------
-    Read data from SQL via either a SQL tablename or a SQL query
+    Read data from SQL via either a SQL query or a SQL tablename (latter not
+    possible for SQLite tables)
+    >>> from sqlite3 import connect
+    >>> conn = connect('file.db')
+    >>> df = pd.DataFrame(data=[[0, '10/11/12'], [1, '12/11/10']],
+    ...                   columns=['int_column', 'date_column'])
+    >>> df.to_sql('test_data', conn)
 
-    >>> pd.read_sql('table_name', 'postgres:///db_name')  # doctest:+SKIP
+    >>> pd.read_sql('SELECT * FROM test_data', con)
 
-    >>> pd.read_sql('SELECT * FROM table_name', 'postgres:///db_name')  # doctest:+SKIP
+    >>> pd.read_sql('table_name', 'postgres:///db_name')  # doctest:+SKIP
 
-    Apply dateparsing to columns through the "parse_dates" argument
+    Apply dateparsing to columns through the ``parse_dates`` argument
 
-    >>> pd.read_sql('table_name',
-    ...             'postgres:///db_name',
-    ...             parse_dates=["date_column"])  # doctest:+SKIP
+    >>> pd.read_sql('SELECT * FROM test_data',
+    ...             conn,
+    ...             parse_dates=["date_column"])
 
-    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:
+    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('table_name',
-    ...             'postgres:///db_name',
-    ...              parse_dates={"date_column": {"errors": "ignore"})  # doctest:+SKIP
+    >>> pd.read_sql('SELECT * FROM test_data',
+    ...             conn,
+    ...             parse_dates={"date_column": {"errors": "ignore"})
 
     2. Apply a dayfirst dateparsing order on the values of "date_column"
 
-    >>> pd.read_sql('table_name',
-    ...             'postgres:///db_name',
-    ...             parse_dates={"date_column": {"dayfirst": True})  # doctest:+SKIP
+    >>> pd.read_sql('SELECT * FROM test_data',
+    ...             conn,
+    ...             parse_dates={"date_column": {"dayfirst": True})
 
     3. Apply custom formatting when dateparsing the values of "date_column"
 
-    >>> pd.read_sql('table_name',
-    ...             'postgres:///db_name',
-    ...             parse_dates={"date_column": {"format": "%d/%m/%Y"})  # doctest:+SKIP
-
-    See Also
-    --------
-    read_sql_table : Read SQL database table into a DataFrame.
-    read_sql_query : Read SQL query into a DataFrame.
+    >>> pd.read_sql('SELECT * FROM test_data',
+    ...             conn,
+    ...             parse_dates={"date_column": {"format": "%d/%m/%Y"})
     """
     pandas_sql = pandasSQL_builder(con)