A histogram is a powerful plot for visualizing the distribution of numerical data. It displays data by grouping values into bins and showing the frequency of values within each bin. With Matplotlib, creating and customizing …

The Pareto distribution is a power-law probability distribution used to model heavy-tailed data — that is, distributions where a small number of events account for the majority of the effect (e.g., wealth distribution, internet traffic, …

Introduction: Why PHP Strings Matter Strings are at the core of almost every PHP application. Whether you're building a blog, handling user input, creating URLs, or displaying content — strings are everywhere. Knowing how to …

One of the most fundamental concepts in programming is scope — it defines the visibility and lifetime of variables. In Python, understanding how scope works is essential for writing clean, bug-free code. In this tutorial, …

In Django REST Framework, building RESTful APIs can be done manually or with the help of powerful abstractions. One of the most convenient tools in DRF is the ModelViewSet — a class that automatically provides …

When building RESTful APIs, understanding how to manually handle HTTP methods like GET, POST, PUT, and DELETE is essential. While Django REST Framework (DRF) provides powerful abstractions like ModelViewSet, sometimes you need more control — …

Creating and managing databases programmatically is a critical skill for developers and data engineers. With Python and Microsoft SQL Server (MSSQL), you can automate database creation, configuration, and maintenance using libraries like pyodbc. This article …

Labels are essential in any data visualization—they help the viewer understand what the data represents. In Matplotlib, labels include: Axis labels (xlabel, ylabel) Titles (title) Legends (legend) Tick labels (xticks, yticks) Annotations (annotate) This guide …

When working with time-sensitive data — such as user activity logs, sales records, or system logs — it’s often necessary to retrieve records from the last month or year relative to today’s date. This guide …

In data analysis with Python, Pandas is one of the most powerful and popular libraries. One of its foundational components is the Series object—a one-dimensional labeled array capable of holding any data type (integers, strings, …

When working with numerical data in Python—especially using NumPy—visualization is essential to explore patterns, relationships, and trends. While matplotlib is powerful, Seaborn offers a simpler and more elegant interface for statistical plotting. In this article, …

Django is a powerful Python-based web framework that follows the MVT architecture—an intuitive and efficient software design pattern. If you’ve worked with other frameworks, you might be familiar with MVC (Model-View-Controller). Django’s MVT is similar, …

Matplotlib is the cornerstone of data visualization in Python. Its core plotting capabilities allow users to visualize data as line plots, bar charts, histograms, scatter plots, and more. This guide walks you through the fundamentals …

When working with real-world datasets, empty cells (missing values) are extremely common — and if not handled properly, they can skew analysis or even break your code. Fortunately, Python's Pandas library makes it easy to …

Preventing form resubmission and ensuring a smooth user experience is essential when handling data in PHP. The Post/Redirect/Get (PRG) pattern is a reliable approach to achieve this. ✅ PHP Form Handling with Page Refresh <?php …