Featured Post

Python Set Operations Explained: From Theory to Real-Time Applications

-
Image
A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...
Post a Comment

Relational Operators in Python: A Quick Guide On How to Use Them

-
Relational operators in Python are helpful, If you are working with numeric values to compare them. Here we explore eight different relational operators and provide examples of how each one works. So to compare numeric values it is a useful guide to refresh.


Relational Operators


Python Relational Operators

Here's a frequently used list of relational operators, and these you can use to compare numeric values. The list shows how to use each operator helpful for data analysis.


<
<=
>
>=
==
!=
Is
is not

Python program: How to use relational operators

Assign 23 to a and 11 to b. Then, apply all the comparison operators. The output is self-explanatory. Bookmark this article to refresh when you are in doubt.

Example

a = 23
b = 11
print("Is a greater than b?", a > b) #greater than
print("Is a less than b?", a < b) #less than
print("Is a greater or equal to b?", a >= b) #greater or equal
print("Is a less or equal to b?", a <= b) #less or equal
print("Is a equal to b (option 1)?", a == b) #test for equality
print("Is a equal to b (option 2)?", a is b) #test for equality
print("Is a not equal to b (option 1)?", a != b) #test for inequality
print("Is a not equal to b (option 2)?", a is not b) #test for inequality


The output

Is a greater than b? True
Is a less than b? False
Is a greater or equal to b? True
Is a less or equal to b? False
Is a equal to b (option 1)? False
Is a equal to b (option 2)? False
Is a not equal to b (option 1)? True
Is a not equal to b (option 2)? Tru



** Process exited - Return Code: 0 **
Press Enter to exit terminal

Conclusion

Relational operators are very helpful for developers who work on data analysis projects, and act as a quick guide they can use as a refresher.

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

SQL Query: 3 Methods for Calculating Cumulative SUM

-
Image
SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than...
Read more

Big Data: Top Cloud Computing Interview Questions (1 of 4)

-
Image
The below are frequently asked interview questions on Cloud computing: 1) What is the difference between Cloud and Grid? Grid: -Information service -Security Service -Data management -Execution Manageement Cloud: - Maintains up-to-date information of resources -Create VMs according to user requirement -Application deploment -User management 2) What are the different cloud standards? -Interoperability standards -Security standards -Portability Standards -Governance and Risk standards 3) What are the two different sub-systems in Cloud computing ? -Management sub system -Resource sub system 4)What is Cloud compouting? The promise of cloud computing is ubiquitous access to a broad set of applications and services, which are delivered over the network to multiple customer. 5) Why we need specialized network for Cloud services? The public Internet is the simplest choice for delivering cloud-based services. In this model, the cloud provider simply purchases Inter...
Read more

5 SQL Queries That Popularly Used in Data Analysis

-
Image
 Here are five popular SQL queries frequently used in data analysis. 1. SELECT with Aggregations Summarize data by calculating aggregates like counts, sums, averages, etc. SELECT department, COUNT(*) as employee_count, AVG(salary) as average_salary FROM employees GROUP BY department; 2. JOIN Operations  Combine data from multiple tables based on a related column. SELECT e.employee_id, e.name, d.department_name FROM employees e JOIN departments d ON e.department_id = d.department_id; 3. WHERE Clause for Filtering Filter records based on specified conditions. SELECT * FROM sales WHERE sale_date BETWEEN '2024-01-01' AND '2024-12-31'   AND amount > 1000; 4. ORDER BY Clause for Sorting Sort results in ascending or descending order based on one or more columns. SELECT product_name, price FROM products ORDER BY price DESC; 5. GROUP BY with HAVING Clause Group records and apply conditions to the aggregated results. SELECT department, SUM(salary) as total_salaries FROM employ...
Read more