Bijay Kumar 
When working with time series data in Pandas, setting a date column as an index is one of my first steps. This simple transformation makes it much easier to analyze trends, resample data, and plot time-based visualizations. In this tutorial, I will show you how to convert a date column to an index in a … Read more >>
Suppose you’re building an admin panel for a web app where users can have one of several roles, such as admin, editor, or viewer. You receive the user role from a backend API as a string, and you want to check whether this string is a valid role according to your enum before using it … Read more >>
When I was working with DataFrames in Pandas, I often found myself needing to set the first column as an index. This is a common task when dealing with datasets where the first column contains unique identifiers, names, or dates that would serve better as row labels rather than regular data. In this article, I … Read more >>
While I was working on a data analysis project for a US retail dataset, I needed to convert price columns from float to integer format. The challenge was maintaining data accuracy while removing decimal places. In this article, I will share five practical methods to convert float values to integers in Pandas, based on my … Read more >>
When I was working on a large dataset containing US sales figures, I needed to quickly preview the data without loading the entire DataFrame. This is a common task when dealing with large datasets, and printing the first few rows can give you a quick overview of your data structure. In this article, I will … Read more >>
Recently, I was working on a data analysis project where I needed to filter a large dataset to focus on specific information. Pandas, a useful Python library, makes this task incredibly easy with its filtering capabilities. In this article, I will share various methods to filter DataFrames in Pandas, from basic boolean filtering to advanced … Read more >>
Working with data often requires filtering and counting specific information. Recently, I was analyzing US sales data and needed to count the number of transactions that exceeded $1,000. This is a common requirement when processing large datasets. Pandas makes this task simple with several different approaches. In this article, I’ll share nine practical ways to … Read more >>
When I was working on a TypeScript project recently, I got a requirement to show dates from a system that sent me big numbers like 1623456789000. These numbers are called timestamps, and they represent a date and time, but in a format that’s hard to read. In this blog, I will show you how to … Read more >>
Avoiding duplicate enum values in TypeScript is important to maintain clarity and avoid unexpected behavior when using enums. Here’s a realistic scenario showing how duplicate values can cause problems and how to avoid them. In this tutorial, we will learn how to avoid duplicate Enum values in TypeScript, how duplicate enum values can lead to … Read more >>
Have you ever seen your app behave strangely just because someone entered the wrong date? For example, a user might type “2025-02-30”, which is not even a real date or the used date format is not valid for the app’s date settings. These small issues can cause big problems if we don’t handle them properly. … Read more >>
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