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SQL INTERVIEW PREPARATION PART-8 How can you find the second highest salary in a table without using the LIMIT clause? You can use a subquery to find the maximum salary that is less than the overall maximum salary. Example:

SELECT MAX(salary)
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

Tip: Explain that this approach can be useful when the LIMIT clause is not supported or if you want to demonstrate proficiency in using subqueries. Share with credits: https://t.me/sqlspecialist Like this post if you want me to continue SQL Interview Preparation Series 👍❤️ Hope it helps :)

SQL INTERVIEW PREPARATION PART-8 How do you find the nth highest salary from a table in SQL? Answer: You can use the LIMIT clause in combination with the ORDER BY clause to find the nth highest salary. Example:

SELECT DISTINCT salary
FROM employees
ORDER BY salary DESC
LIMIT n-1, 1;

Replace 'n' with the desired rank of the salary. Tip: Emphasize the importance of using DISTINCT to handle cases where there are duplicate salaries, and ensure the ORDER BY clause is sorting the salaries in descending order to find the nth highest salary. Share with credits: https://t.me/sqlspecialist Like this post if you want me to continue SQL Interview Preparation Series 👍❤️ Hope it helps :)

6. Add Basic CSS Styling: Create a new file named styles.css and link it to your HTML document. Add styles for your layout, focusing on making it visually appealing.   

   body {
       font-family: Arial, sans-serif;
       margin: 0;
       padding: 0;
       background-color: #f8f8f8;
       color: #333;
   }

   .header {
       background-color: #4CAF50;
       color: white;
       text-align: center;
       padding: 50px 0;
   }

   .navbar {
       display: flex;
       justify-content: space-between;
       align-items: center;
       padding: 10px 20px;
   }

   .logo {
       font-size: 24px;
       font-weight: bold;
   }

   .nav-links {
       list-style-type: none;
       padding: 0;
   }

   .nav-links li {
       display: inline;
       margin: 0 10px;
   }

   .nav-links a {
       color: white;
       text-decoration: none;
   }

   .hero {
       padding: 100px 20px;
   }

   .hero h1 {
       font-size: 48px;
       margin-bottom: 20px;
   }

   .hero p {
       font-size: 18px;
       margin-bottom: 40px;
   }

   .btn {
       background-color: #333;
       color: white;
       padding: 10px 20px;
       text-decoration: none;
       border-radius: 5px;
   }

   .features, .testimonials, .call-to-action {
       padding: 50px 20px;
       text-align: center;
   }

   .feature, .testimonial {
       margin-bottom: 20px;
   }

   .footer {
       background-color: #333;
       color: white;
       text-align: center;
       padding: 20px 0;
   }
   

7. Customize and Refine: Adjust the layout and styling to fit your content and design preferences. Use CSS Grid or Flexbox for advanced layouts, and add custom styles to enhance the appearance. 8. Save and View: Save your landing_page.html and styles.css files. Open the HTML file in a web browser to see how the layout looks. Make adjustments as needed. 9. Resources:    - [Unbounce - Anatomy of a Landing Page](https://unbounce.com/landing-page-articles/anatomy-of-a-landing-page/)    - [HubSpot - Best Practices for Landing Page Design](https://blog.hubspot.com/marketing/landing-page-best-practices-list)    - [MDN Web Docs - HTML Elements](https://developer.mozilla.org/en-US/docs/Web/HTML/Element) 10. Publish Your Landing Page: Once you're satisfied with your landing page, upload your HTML and CSS files to your hosting service to share it online. Web Development Best Resources: https://topmate.io/coding/930165 Share with credits: https://t.me/webdevcoursefree ENJOY LEARNING 👍👍

21 Days Web Development Project Plan Day 15: Landing Page 1. Understand Landing Pages: A landing page is a single web page designed to capture a visitor's attention and encourage them to take a specific action, such as signing up for a newsletter or purchasing a product. The focus is on aesthetics and user experience. 2. Plan Your Layout: Sketch out the layout of your landing page. Common sections include a header, hero section, features, testimonials, call-to-action, and footer. Decide on the content and images you'll need. 3. Create a New HTML File: Open your text editor and create a new file named landing_page.html. 4. Set Up the Structure: Add the basic structure of an HTML document, including the <!DOCTYPE html> declaration, <html>, <head>, and <body> tags. 5. Build the Layout: Inside the <body> tag, create the structure of your landing page. Use semantic HTML tags like <header>, <section>, and <footer>.

   <!DOCTYPE html>
   <html>
   <head>
       <title>Landing Page</title>
       <link rel="stylesheet" href="styles.css">
   </head>
   <body>
       <header class="header">
           <nav class="navbar">
               <a href="#" class="logo">Brand</a>
               <ul class="nav-links">
                   <li><a href="#">Home</a></li>
                   <li><a href="#">Features</a></li>
                   <li><a href="#">Pricing</a></li>
                   <li><a href="#">Contact</a></li>
               </ul>
           </nav>
           <div class="hero">
               <h1>Welcome to Our Product</h1>
               <p>Discover the amazing features and benefits</p>
               <a href="#" class="btn">Get Started</a>
           </div>
       </header>
       <section class="features">
           <h2>Features</h2>
           <div class="feature">
               <h3>Feature 1</h3>
               <p>Detail about feature 1.</p>
           </div>
           <div class="feature">
               <h3>Feature 2</h3>
               <p>Detail about feature 2.</p>
           </div>
           <div class="feature">
               <h3>Feature 3</h3>
               <p>Detail about feature 3.</p>
           </div>
       </section>
       <section class="testimonials">
           <h2>Testimonials</h2>
           <div class="testimonial">
               <p>"This product changed my life!" - Customer A</p>
           </div>
           <div class="testimonial">
               <p>"Amazing features and great support!" - Customer B</p>
           </div>
       </section>
       <section class="call-to-action">
           <h2>Ready to Get Started?</h2>
           <a href="#" class="btn">Sign Up Now</a>
       </section>
       <footer class="footer">
           <p>&copy; 2024 Brand. All rights reserved.</p>
       </footer>
   </body>
   </html>

COMC is hiring for Data Analyst Salary Range $80,000.00 - $100,000.00 Apply Link: https://www.paycomonline.net/v4/ats/web.php/jobs/ViewJobDetails?job=100986&clientkey=DB4B2E90705AD5F0635FBD274EAB4268 Job Qualifications Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field. 2+ years of experience in data analysis. Proficient in SQL for data querying and manipulation. Experience with Power BI or similar data visualization tools. Understanding of data warehousing and database structures. Basic knowledge of statistical analysis and data modeling. Excellent analytical and problem-solving skills. Ability to communicate complex data insights in a clear and concise manner. Like for more ❤️ All the best 👍👍

System Design📖.pdf

Top 10 Python libraries commonly used by data scientists 1. NumPy: A fundamental package for scientific computing with support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions. 2. pandas: A powerful data manipulation and analysis library that provides data structures and functions for working with structured data. 3. matplotlib: A widely-used plotting library for creating a variety of visualizations, including line plots, bar charts, histograms, scatter plots, and more. 4. scikit-learn: A comprehensive machine learning library that provides tools for data mining and data analysis, including algorithms for classification, regression, clustering, and more. 5. TensorFlow: An open-source machine learning framework developed by Google for building and training machine learning models, particularly for deep learning tasks. 6. Keras: A high-level neural networks API that is built on top of TensorFlow and provides an easy-to-use interface for building and training deep learning models. 7. Seaborn: A data visualization library based on matplotlib that provides a high-level interface for creating informative and attractive statistical graphics. 8. SciPy: A library that builds on NumPy and provides a wide range of scientific and technical computing functions, including optimization, integration, interpolation, and more. 9. Statsmodels: A library that provides classes and functions for the estimation of many different statistical models, as well as conducting statistical tests and exploring data. 10. XGBoost: An optimized gradient boosting library that is widely used for supervised learning tasks, such as regression and classification. Cracking the Data Science Interview 👇👇 https://topmate.io/analyst/1024129 Credits: https://t.me/datasciencefun Like if you need similar content ENJOY LEARNING 👍👍

Industrial Internet of Things Anand Sharma, 2022

Top 5 SQL Functions https://t.me/sqlanalyst 1. SELECT Statement:    - Function: Retrieving data from one or more tables.    - Example: SELECT column1, column2 FROM table WHERE condition; 2. COUNT Function:    - Function: Counts the number of rows that meet a specified condition.    - Example: SELECT COUNT(column) FROM table WHERE condition; 3. SUM Function:    - Function: Calculates the sum of values in a numeric column.    - Example: SELECT SUM(column) FROM table WHERE condition; 4. AVG Function:    - Function: Computes the average value of a numeric column.    - Example: SELECT AVG(column) FROM table WHERE condition; 5. GROUP BY Clause:    - Function: Groups rows that have the same values in specified columns into summary rows.    - Example: SELECT column, AVG(numeric_column) FROM table GROUP BY column; These functions are fundamental in SQL and are frequently used for various data manipulation tasks, including data retrieval, aggregation, and analysis. Like for more Here you can find essential SQL Interview Resources👇 https://topmate.io/analyst/864764 Hope it helps :)