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

The previous post on Extracting data from tables in PDF was many years old and requires an update as it didn't cover a Python package...

For the latest call for proposals to include other timezones from Asia Pacific and Americas, I decided to submit a talk and am glad that...