Adoption of Python has been enormous over the last decade. Why? It’s easy to use, accessible, versatile and can be used for AI, machine learning, data analytics, data visualization, and all types of science. Tune into how 3 experts are [See the full post…]

Data scientists spend 60% of their time cleaning and preprocessing data, transforming this dirty data into crystallized insights. Dataframes, such as Pandas, provide exceptional tooling to address data wrangling tasks, yet Pandas themselves increasingly lack ease and speed as they [See the full post…]