When you have divided the data in two tables you can fetch combined records from these two tables using Joins.

Example

Assume we have created a table with name CRICKETERS using the following query −

sqlite> CREATE TABLE CRICKETERS (
   First_Name VARCHAR(255),
   Last_Name VARCHAR(255),
   Age int,
   Place_Of_Birth VARCHAR(255),
   Country VARCHAR(255)
);
sqlite>

Let us create one more table OdiStats describing the One-day cricket statistics of each player in CRICKETERS table.

sqlite> CREATE TABLE ODIStats (
   First_Name VARCHAR(255),
   Matches INT,
   Runs INT,
   AVG FLOAT,
   Centuries INT,
   HalfCenturies INT
);
sqlite>

Following statement retrieves data combining the values in these two tables −

sqlite> SELECT
   Cricketers.First_Name, Cricketers.Last_Name, Cricketers.Country,
   OdiStats.matches, OdiStats.runs, OdiStats.centuries, OdiStats.halfcenturies
   from Cricketers INNER JOIN OdiStats ON Cricketers.First_Name = OdiStats.First_Name;
First_Name  Last_Name   Country  Matches  Runs   Centuries   HalfCenturies
----------  ----------  -------  -------  ----   ---------   -------------- 
Shikhar     Dhawan      Indi     133      5518   17          27
Jonathan    Trott       Sout     68       2819   4           22
Kumara      Sangakkara  Sril     404      14234  25          93
Virat       Kohli       Indi     239      11520  43          54
Rohit       Sharma      Indi     218      8686   24          42
sqlite>

Join Clause Using Python

Following SQLite example, demonstrates the JOIN clause using python −

import sqlite3
#Connecting to sqlite
conn = sqlite3.connect(''example.db'')

#Creating a cursor object using the cursor() method
cursor = conn.cursor()

#Retrieving data
sql = ''''''SELECT * from EMP INNER JOIN CONTACT ON EMP.CONTACT = CONTACT.ID''''''

#Executing the query
cursor.execute(sql)

#Fetching 1st row from the table
result = cursor.fetchall();

print(result)

#Commit your changes in the database
conn.commit()

#Closing the connection
conn.close()

Output

[
   (''Ramya'', ''Rama priya'', 27, ''F'', 9000.0, 101, 101, ''[email protected]'', ''Hyderabad''), 
   (''Vinay'', ''Battacharya'', 20, ''M'', 6000.0, 102, 102,''[email protected]'', ''Vishakhapatnam''), 
   (''Sharukh'', ''Sheik'', 25, ''M'', 8300.0, 103, 103, ''[email protected]'', ''Pune''), 
   (''Sarmista'', ''Sharma'', 26, ''F'', 10000.0, 104, 104, ''[email protected]'', ''Mumbai'')
]