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

This post shows an example of how to query data using the MAS API. The results returned are in bytes format and has to be transformed to...

It took me really long to figure out how to plot the charts out using matplotlib and seaborn. If you need to use major/ minor ticks,...