You have to use a fetch method along with cursor. For Example

for row in cursor.fetchall():
    print('row = %r' % (row,))

EDIT :

The fetchall function returns all remaining rows in a list.

If there are no rows, an empty list is returned. 
    If there are a lot of rows, *this will use a lot of memory.*

Unread rows are stored by the database driver in a compact format and are often sent in batches from the database server.

Reading in only the rows you need at one time will save a lot of memory.

If we are going to process the rows one at a time, we can use the cursor itself as an interator Moreover we can simplify it since cursor.execute() always returns a cursor :

for row in cursor.execute("select bla, anotherbla from blabla"): 
    print row.bla, row.anotherbla

Documentation

I found this information useful to retrieve data from SQL database to python as a data frame.

import pandas as pd
import pymssql

con = pymssql.connect(server='use-et-aiml-cloudforte-aiops- db.database.windows.net',user='login_username',password='login_password',database='database_name')
cursor = con.cursor()

query = "SELECT * FROM <TABLE_NAME>"
cursor.execute(query)
df = pd.read_sql(query, con)
con.close()

df

import mysql.connector as mc

connection creation

conn = mc.connect(host='localhost', user='root', passwd='password') print(conn)

#create cursor object

cur = conn.cursor() print(cur)

cur.execute('show databases')

for i in cur: print(i)

query = "Select * from employee_performance.employ_mod_recent" emp_data = pd.read_sql(query, conn) emp_data