Using tools such as sqlmagic or pyodbc for ipython (below) you can let the sql database perform most of the heavy lifting of getting "raw" result sets into a da

Using tools such as sqlmagic or pyodbc for ipython (below) you can let the sql database perform most of the heavy lifting of getting "raw" result sets into a dataframe and then perform some lighter, possibly more ptyhon-idiomatic tweaks to the data once the focused set is loaded in-memory. def getdataframe(sql): try: connection = pyodbc.connect("DSN=myDSN", autocommit=True) return pandas.read_sql(sql, connection) except Exception as e: print repr(e) finally: connection.close()