Python Programming Training Certification

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Course Overview
Python is one of the world’s top programming languages used today and Python training has become the most popular training across individuals. Training Basket’s Python Training & Certification course covers basic and advanced Python concepts and how to apply them in real-world applications.Python is a flexible and powerful open-source language that is easy to learn and consists of powerful libraries for data analysis and manipulation. Our Python training course content is curated by experts as per the standard Industry curriculum. The curriculum, coding challenges and real-life problems cover data operations in Python, strings, conditional statements, error handling, shell scripting, web scraping and the commonly used Python web framework Django. Take this Python training and certification course and become job-ready now.

Join Operation
We can combine the columns from two or more tables by using some common column among them by using the join statement.
We have only one table in our database, let’s create one more 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 table Departments as shown in the above image. However, we haven’t yet inserted any value 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 look 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 IT
Right Join
Right join shows all the columns of the right-hand side table as we have two tables in the database PythonDB, i.e., Departments and Employee. We do not have any Employee in the table who is not working for any department (Employee for which department id is null). However, to understand the concept of right 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 doesn’t work for any department (department id is null).
Now, we have an employee in the Employee table whose department id is not present in the Departments table. Let’s perform 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 None
Left Join
The left join covers all the data from the left-hand side 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
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