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

I recently cultivated the habit of using virtual environment a.k.a virtualenv (should have done it long time ago for better project...

With R, and Ananconda installed, we can also use R in Jupyter notebook. So my previous laptop died and now I have to re-install...

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...