Data Cleaning and Preparation

Data cleaning and preparation are essential steps in any data analysis project, as data is often messy, incomplete or inconsistent. In order to perform accurate analysis and modeling, it is necessary to clean and preprocess data, which involves tasks such as removing duplicates, filling in missing values and converting data types.

With DataFrame and Kotlin’s language features, a high-level, flexible, and fast set of tools enable the analyst to manipulate data into the desired form. All those tools also integrate seamlessly with Kotlin’s functional programming capabilities, resulting into a very powerful tool for the accomplishment of various data analysis task.