The following should work:

import pandas as pd
from sqlalchemy import create_engine

engine = create_engine('mysql://{}:{}@{}/{}'.format(username, password, server, database_name))
connection = engine.connect().connection
cursor = self.connection.cursor()

cursor.execute('call storedProcName(%s, %s, ...)', params)

# Results set 1
column_names = [col[0] for col in cursor.description] # Get column names from MySQL

df1_data = []
for row in cursor.fetchall():
    df1_data.append({name: row[i] for i, name in enumerate(column_names)})

# Results set 2
cursor.nextset()
column_names = [col[0] for col in cursor.description] # Get column names from MySQL

df2_data = []
for row in cursor.fetchall():
    df2_data.append({name: row[j] for j, name in enumerate(column_names)})

cursor.close()

df1 = pd.DataFrame(df1_data)
df2 = pd.DataFrame(df2_data)

Edit: I've updated the code here to avoid having to manually specify the column names.

Note that the original question only specifies a "local SQL server", not a specific kind of SQL server. This answer works with MySQL, but I haven't tested it with any other variety.

This question is very old by now. pandas 0.10 is very old as well. In the newest version of pandas 0.16, the read_frame method has been depricated in favour of the read_sql. Even so, the documentation says that just like the read_csv function, it takes a parse_dates argument Pandas 0.16 read_frame

It seems the parse_dates argument appeared in 0.14, at the same time as read_frame was depricated. The read_sql function seems to be a rename of the read_frame, so just updating your pandas version to 0.14 or higher and renaming your function will give you access to this argument. Here is the doc for the read_sql function: Pandas 0.16 read_sql

SQL server was never supported before pandas 0.14 (only mysql and sqlite were, with default of sqlite. Hence the error you get), but from pandas 0.14 it is supported to write dataframes to MS SQL server.
But to use this, you have to use an sqlalchemy engine (see docs) instead of a pyobdc connection object. Eg:

from sqlalchemy import create_engine
engine = create_engine('mssql+pyodbc://scott:tiger@mydsn')
df.to_sql('test', engine)

See the pandas documentation on this: http://pandas.pydata.org/pandas-docs/stable/io.html#sql-queries