#!/usr/bin/python3
import mysql.connector
 
import pandas as df
import pandas.io.sql as psql
 
# Get MySQL connection.
host="localhost"
username="root2"
password="password"
db_name="test_db_name"
connection = mysql.connector.connect(
                                      host=host,
                                      user=username,
                                      passwd=password,
                                      database=db_name
                                    )
 
# Fetch data into pandas.
sql_query = "SELECT * FROM Price LIMIT 10"
df = psql.read_sql(sql_query, connection)
print(df)

   ticker_id        date       open        low       high      close  adj_close   volume
0          1  1962-01-02  71.550003  70.709999  71.959999  70.959999  70.959999  3120000
1          1  1962-01-03  70.959999  70.379997  71.480003  71.129997  71.129997  3590000
2          1  1962-01-04  71.129997  70.449997  71.620003  70.639999  70.639999  4450000
3          1  1962-01-05  70.639999  69.349998  70.839996  69.660004  69.660004  4630000
4          1  1962-01-08  69.660004  68.169998  69.839996  69.120003  69.120003  4620000
5          1  1962-01-09  69.120003  68.830002  69.930000  69.150002  69.150002  3600000
6          1  1962-01-10  69.150002  68.620003  69.580002  68.959999  68.959999  3300000
7          1  1962-01-11  68.959999  68.570000  69.540001  69.370003  69.370003  3390000
8          1  1962-01-12  69.370003  69.230003  70.169998  69.610001  69.610001  3730000
9          1  1962-01-15  69.610001  69.059998  69.959999  69.470001  69.470001  3450000