We can mix the columns from two or greater tables with the aid of the usage of some frequent column amongst them by using the use of the be part of statement.
We have solely one desk in our database, let’s create one extra table Departments with two columns department_id and department_name.
create table Departments (Dept_id int(20) primary key not null, Dept_Name varchar(20) not null);
As we have created a new desk Departments as proven in the above image. However, we have not but inserted any price inside it.
Let’s insert some Departments ids and departments names so that we can map this to our Employee table.
insert into Departments values (201, "CS");
insert into Departments values (202, "IT");
Let’s seem to be at the values inserted in each of the tables. Consider the following image.
Now, let’s create a python script that joins the two tables on the common column, i.e., dept_id.
Example
import mysql.connector
#Create the connection object
myconn = mysql.connector.connect(host = "localhost", user = "root",passwd = "google",database = "PythonDB")
#creating the cursor object
cur = myconn.cursor()
try:
#joining the two tables on departments_id
cur.execute("select Employee.id, Employee.name, Employee.salary, Departments.Dept_id, Departments.Dept_Name from Departments join Employee on Departments.Dept_id = Employee.Dept_id")
print("ID Name Salary Dept_Id Dept_Name")
for row in cur:
print("%d %s %d %d %s"%(row[0], row[1],row[2],row[3],row[4]))
except:
myconn.rollback()
myconn.close()
Output:
ID Name Salary Dept_Id Dept_Name
101 John 25000 201 CS
102 John 25000 201 CS
103 David 25000 202 IT
104 Nick 90000 201 CS
105 Mike 28000 202 ITRight Join
Right be a part of shows all the columns of the right-hand facet desk as we have two tables in the database PythonDB, i.e., Departments and Employee. We do now not have any Employee in the desk who is no longer working for any branch (Employee for which department id is null). However, to apprehend the notion of proper join let’s create the one.
Execute the following query on the MySQL server.
insert into Employee(name, id, salary, branch_name) values ("Alex",108,29900,"Mumbai");
This will insert an employee Alex who would not work for any department (department identity is null).
Now, we have an worker in the Employee desk whose branch identification is now not present in the Departments table. Let’s operate the right join on the two tables now.
Example
import mysql.connector
#Create the connection object
myconn = mysql.connector.connect(host = "localhost", user = "root",passwd = "google",database = "PythonDB")
#creating the cursor object
cur = myconn.cursor()
try:
#joining the two tables on departments_id
result = cur.execute("select Employee.id, Employee.name, Employee.salary, Departments.Dept_id, Departments.Dept_Name from Departments right join Employee on Departments.Dept_id = Employee.Dept_id")
print("ID Name Salary Dept_Id Dept_Name")
for row in cur:
print(row[0]," ", row[1]," ",row[2]," ",row[3]," ",row[4])
except:
myconn.rollback()
myconn.close()
Output:
ID Name Salary Dept_Id Dept_Name
101 John 25000.0 201 CS
102 John 25000.0 201 CS
103 David 25000.0 202 IT
104 Nick 90000.0 201 CS
105 Mike 28000.0 202 IT
108 Alex 29900.0 None NoneLeft Join
The left join covers all the data from the left-hand facet table. It has just opposite effect to the right join. Consider the following example.
Example
import mysql.connector
#Create the connection object
myconn = mysql.connector.connect(host = "localhost", user = "root",passwd = "google",database = "PythonDB")
#creating the cursor object
cur = myconn.cursor()
try:
#joining the two tables on departments_id
result = cur.execute("select Employee.id, Employee.name, Employee.salary, Departments.Dept_id, Departments.Dept_Name from Departments left join Employee on Departments.Dept_id = Employee.Dept_id")
print("ID Name Salary Dept_Id Dept_Name")
for row in cur:
print(row[0]," ", row[1]," ",row[2]," ",row[3]," ",row[4])
except:
myconn.rollback()
myconn.close()
Output:
ID Name Salary Dept_Id Dept_Name
101 John 25000.0 201 CS
102 John 25000.0 201 CS
103 David 25000.0 202 IT
104 Nick 90000.0 201 CS
105 Mike 28000.0 202 IT