DATA DIVE DAYS

The best way to know whether you enjoy working with data — or to learn how to work with data — is to handle many different forms of messy, real-world datasets, i.e. perform the necessary data cleaning and transformations to derive meaningful insights from them. This post shares two sample Jupyter notebooks that demonstrate various data transformation steps to achieve clean data for two different data formats: - JSON output obtained from calling the Developer API of the SingSt

Github is a platform that a lot of coders use for sharing code work/ algorithms etc. And it is also especially useful for collaborative...

There are occasions where we might want to download only a folder from someone's Github repository instead of the entire repository (at...

Today I decided to poke around a little to see if it would be possible to read csv files directly from Github, and the answer is yes. As...

Over the years, the number of tools (or software) I have to install/ use increased steadily given the different types of tasks I have to...