Author name: Bao Nguyen

Think of the most boring task you’ve ever done at work. Chances are, you can automate it with Python. You only need to open your favorite text editor and start writing code. However, you might struggle to automate some tasks more than others and end up wasting more time. What most people don’t know, however,

According to Forbes, data scientists and analysts spend 60% of their time on cleaning and organizing data. This shows how important data cleaning and data wrangling are in a project. Data cleaning consists in cleaning the data we’ll use, so we don’t have incorrect, corrupted, duplicate, or incomplete data. Real-world data isn’t as clean as

One common task data analysts have to deal with when collecting and cleaning data is working with strings. This involves formatting as well as joining strings (also known as string concatenation). Joining strings in Python   is as simple as using the plus operator +. You’ve probably used the code below hundreds of times to join

Here’s the second part of web scraping with Python. In this tutorial, we’ll learn how to web scrape with Selenium. In part 1, I mentioned that there was missing data and that we would scrape it with Selenium in part 2, but I checked again and there isn’t missing data thanks to some changes to

Hi! I prepared two tutorials to help you get started with Beautiful Soup and Selenium. In these tutorials, we’ll scrape a simple website from scratch so that you see with your own eyes what are the differences between these two libraries. In this article, we’ll extract football data from all the FIFA World Cups played