Matplotlib is undoubtedly one of the most well-known and widely used of the features that make Python a potent language for data visualisation. Line plots, which are essential tools for displaying data trends, are only one of the many plot styles that can be created using its adaptable framework. In order to help you better grasp how to alter line plot styles in Matplotlib, this article takes you on a thorough exploration of the topic. Remember that Matplotlib has a multitude of other plot customization options that are tailored to the various demands of data visualisation projects, even though our ... Read More

Plotly is an interactive, open-source toolkit that enables users to build a wide range of aesthetically pleasing and intelligent charts in the field of data visualisation in Python. The line chart, one of the most popular chart forms, is the subject of this article. In order to help you comprehend, we'll go over how to make line charts using Plotly while using practical examples. Even though we'll focus mostly on line charts, keep in mind that Plotly is a flexible library that supports a wide range of additional chart styles, offering countless opportunities to tell engaging tales with data. A ... Read More

Pygal stands out among the different Python data visualisation tools. The SVG (Scalable Vector Graphics) outputs from Pygal strike an excellent balance between elegance and customization. This article is devoted to building line charts in Pygal and includes pertinent examples to aid with comprehension. The development of line charts is the main emphasis of this book, however Pygal has many other features and a wide range of chart styles to meet a variety of data visualisation requirements. Pygal: A Quick Recap An open-source Python package called Pygal is used to produce stunning SVG charts that are both interactive and browser-friendly. ... Read More

Pandas, a Python package, is now the tool of choice for data scientists and analysts all around the world. Row and column selection from dataframes is one of its many functions for data manipulation and analysis. This article examines, using real-world examples, how to use Pandas to pick a set number of rows with a particular column. While we emphasise one particular feature of Pandas, keep in mind that the library's capabilities go much beyond this, making it a crucial tool for data processing. Pandas DataFrame: A Brief Introduction For Python, Pandas offers a fast, user-friendly data structure (DataFrame) and ... Read More

With over a billion members, Instagram is a hugely successful social networking website. It is a favourite platform for data scientists, marketers, and developers alike because to its strong API and data accessibility. With the aid of 2-3 examples, we will examine how to like Instagram photos programmatically using Python and Selenium in this article. Please be aware that this information is only meant to be instructive. Respecting Instagram's rules and refraining from behaviour that can be construed as spamming are crucial. Getting Started: Installation and Setup You need to set up your environment before you start coding. Python and ... Read More

A GUI (Graphical User Interface) that fluidly alternates between bright and dark themes may be something you're interested in programming. Tkinter is your go-to library for creating such apps if you're using Python. This tutorial will show you how to use Tkinter to make a light or dark theme changer. What is Tkinter? Python's default GUI package is Tkinter. It is a preferred method for developing desktop apps. One of Tkinter's numerous advantages is its simplicity and adaptability, which let you design widgets and interfaces with changeable properties like buttons, labels, text boxes, menus, and more. Importance of Theme Changing ... Read More

Debugging is an essential skill for developers to identify and resolve issues in their code. With the arrival of ES6 (ECMAScript 2015), JavaScript introduced several new features and syntax improvements. We can debug code in ES6 using various methods like Using Console Statements, Leveraging Debugging Tools, Employing Breakpoints, Analyzing Stack Traces, Debugging Asynchronous Code, and Advanced Debugging Techniques. This article will provide a detailed guide on how to effectively debug code in ES6. Setting Up a Development Environment Before we start debugging ES6 code, it's important to set up a suitable development environment. We can choose any code editor or ... Read More

When working with lists in Python, there may be cases where you need to compare whether two lists are reverse equal. This means that the elements in one list are the same as the elements in the other list but in reverse order. In Python, we can check if two lists are reverse equal using methods like Reversing and Comparing Lists, using the zip() Function, converting Lists to Strings, etc. In this article, we will understand these methods and check if two lists are reverse equal with the help of various examples. Method 1:Reversing and Comparing Lists The first method ... Read More

In Python, the concatenation of strings is a common operation that allows you to combine two or more strings into a single string. While concatenating strings vertically (i.e., one below the other) is straightforward, concatenating strings horizontally (i.e., side by side) requires some additional handling, especially when dealing with multiline strings. In this article, we will explore different approaches for performing horizontal concatenation of multiline strings in Python. Method 1:Using the + Operator The + operator can be used to combine two or more strings into a single string. However, when dealing with multiline strings, using the + operator may ... Read More

In data analysis and processing, it is necessary to group similar elements together for better organization and analysis of data. Python provides several methods to group elements into a matrix efficiently, using matrices. In this article, we will explore different approaches to grouping similar elements into a matrix using Python. Method 1:Using Numpy NumPy is a widely−used Python library for scientific computing, particularly for working with arrays. It provides powerful functions to create and manipulate matrices efficiently. If the elements are numeric, we can use the NumPy library to group them into a matrix efficiently. Example In the below example, ... Read More