Read data from pyodbc to pandas

I was way over thinking this one!

cnxn = pyodbc.connect(r'DRIVER={Microsoft Access Driver (*.mdb, *.accdb)};DBQ=C:\users\bartogre\desktop\CorpRentalPivot1.accdb;UID="";PWD="";')
crsr = cnxn.cursor()
for table_name in crsr.tables(tableType='TABLE'):
    print(table_name)
cursor = cnxn.cursor()
sql = "Select sum(CYTM), sum(PYTM), BRAND From data Group By BRAND"
cursor.execute(sql)
data = cursor.fetchall()
print(data)
Data = pandas.DataFrame(data)
print(Data)

Another, faster method. Please see data = pd.read_sql(sql, cnxn)

import pyodbc
import pandas as pd
from pandas import DataFrame
from pandas.tools import plotting
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns

cnxn = pyodbc.connect(r'DRIVER={Microsoft Access Driver (*.mdb, *.accdb)}; DBQ=C:\users\bartogre\desktop\data.mdb;UID="";PWD="";')
crsr = cnxn.cursor()
for table_name in crsr.tables(tableType='TABLE'):
    print(table_name)
cursor = cnxn.cursor()
sql = "Select *"
sql = sql + " From data"
print(sql)
cursor.execute(sql)
data = pd.read_sql(sql, cnxn)

A shorter and more concise answer

import pyodbc
import pandas as pd

cnxn = pyodbc.connect(r'DRIVER={Microsoft Access Driver (*.mdb, *.accdb)};'
                      r'DBQ=C:\users\bartogre\desktop\data.mdb;')
sql = "Select sum(CYTM), sum(PYTM), BRAND From data Group By BRAND"
data = pd.read_sql(sql,cnxn)  # without parameters [non-prepared statement]

# with a prepared statement, use list/tuple/dictionary of parameters depending on DB
#data = pd.read_sql(sql=sql, con=cnxn, params=query_params)