Farook Mohammad 
In this article, we are going to fully break down one of the practical problems from that series: Find the number of matches played, won, and lost by each team in the ICC World Cup. But we’re not just writing the solution. We’re going to understand the logic, the approach, the table schema, the transformation … Read more
When it comes to data visualization in Python, Seaborn stands out as one of the most powerful and intuitive libraries. Among its numerous charting options, the bar plot is one of the most widely used — perfect for representing aggregated statistics across categorical variables. In this comprehensive guide, we’ll explore how to create advanced bar … Read more
In modern data visualization, understanding the distribution of variables is one of the most fundamental and insightful analysis techniques. Seaborn’s displot() is a figure-level function that provides a flexible, high-level interface to visualize univariate and bivariate distributions. It combines the power of histplot(), kdeplot(), and ecdfplot() into one unified and advanced plotting function. In this … Read more
When analyzing real-world datasets, understanding the distribution of continuous variables is crucial. The histogram plot is one of the most powerful visual tools for this purpose. In this advanced guide, we will show you how to create, customize, and enhance histogram plots using Seaborn’s built-in penguins dataset. We will also explore all key parameters of … Read more
In this comprehensive tutorial we will walk through how to create a sophisticated line chart with Seaborn using the built-in dataset penguins. We will cover all relevant parameters, their values, and advance into grouping, styles, annotations, and best practices for visual clarity and insight. By the end of this article you will be equipped to … Read more
When working with data visualization in Python, especially using Pandas with Matplotlib, one of the most important elements for clarity is the legend. A legend helps us label and identify different data categories or plot elements, ensuring the visualization is understandable. While Pandas provides automatic legends when plotting with DataFrame.plot(), sometimes we need to manually … Read more
When working with data analytics in 2025, one of the most powerful tools we have at our disposal is Pandas, a Python library designed for data manipulation and analysis. Within Pandas, string functions play a vital role in cleaning, transforming, and extracting insights from textual data. As data grows rapidly across industries, the ability to … Read more
If you’re preparing for a Microsoft Excel interview in 2025, having a strong grasp of advanced features and problem-solving techniques is crucial. This article covers questions 21–30 from our Excel Interview Series, designed to help you stand out in any analytics, finance, or data-related interview. How do you handle errors in Excel formulas? Answer: Excel provides several ways to manage … Read more
Introduction If you’ve already mastered the first 10 Excel Interview Questions Part – 1, it’s time to dive deeper into Part 2. These next questions 11–20 focus on more advanced Excel concepts that employers often ask to test your problem-solving and automation skills. Let’s break them down one by one. What is Data Validation in … Read more
Introduction Excel has remained a must-have skill for data analysts, accountants, marketers, and business professionals. Even in 2025, interviewers often test candidates on their Excel knowledge because it shows problem-solving ability and data-handling skills. If you’re preparing for an interview, mastering these top 10 Excel questions will give you an edge. What is Microsoft Excel? … Read more