Bijay Kumar 
When I first started working with data visualization in Python, I quickly realized that plotting data on a logarithmic scale is essential for many real-world datasets. Log-log plots, where both the x-axis and y-axis are on a logarithmic scale, are particularly useful for visualizing relationships that span several orders of magnitude. In this guide, I … Read more >>
One of the libraries I keep coming back to for data visualization is Matplotlib. It’s flexible and widely used across industries in the USA, from finance to healthcare. But if you’ve ever created multiple plots in the same figure, you might have noticed how tricky it can be to get the spacing just right. That’s … Read more >>
I’ve worked extensively with data visualization. One library that has always been a go-to is Matplotlib. It’s useful, flexible, and widely used across industries, especially here in the USA, where data-driven decisions are the norm. One feature I often rely on is subplots. They allow you to display multiple plots in a single figure, making … Read more >>
Recently, I was working on a TypeScript project where I had to fetch user data from an object based on dynamic string IDs. In that process, I got a TypeScript compile error stating that we couldn’t index the object with a string. After searching for the solutions, I came to know that the issue was … Read more >>
As a Python developer, I’ve worked extensively with data visualization libraries. Among them, Matplotlib remains one of the most useful and versatile tools for creating a variety of charts, including bar charts. In this article, I’ll walk you through how to create bar charts using Matplotlib. I’ll share practical examples relevant to real-world data, such … Read more >>
When I was working with data visualization in Python, plotting horizontal lines in Matplotlib was one of the fundamental skills I needed. In this guide, I’ll share my firsthand experience with several methods to draw horizontal lines in Matplotlib. I’ll keep it simple, practical, and focused on real-world examples relevant to data analysts and developers … Read more >>
As a Python developer with over a decade of experience, I’ve found Matplotlib to be an invaluable tool for data visualization. In this guide, I’ll walk you through simple and practical ways to draw vertical lines in Matplotlib. The methods I share come from real-world experience, designed to help you quickly add vertical markers to … Read more >>
As a developer, I’ve worked extensively with Matplotlib for data visualization. One of the most common yet useful ways to enhance your plots is by using dashed lines. In this article, I’ll walk you through everything you need to know about creating and customizing dashed lines in Matplotlib. I’ll share practical tips and different methods … Read more >>
I’ve found that visualizing data effectively is just as important as analyzing it. One of the most common tasks I encounter is plotting a best-fit line to understand trends and relationships within data. Matplotlib, Python’s go-to plotting library, provides easy ways to add a best-fit line to your scatter plots. In this article, I’ll walk … Read more >>
When I first started working with Python for data visualization, I often wondered about the term Matplotlib inline. It’s a phrase that pops up frequently, especially when working with Jupyter notebooks. But what does it mean? And how can you use it effectively? In this article, I’ll share my firsthand experience with Matplotlib inline, explain … Read more >>
Download a FREE PDF (112 Pages) Containing 51 Useful Python Programs.
Download a FREE PDF on how to become a Python developer.