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Data frame is an abstraction for working with structured data. Essentially it’s a 2-dimensional table with labeled columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dictionary of series objects. The handiness of this abstraction is not in the table itself but in a set of operations defined on it. The Kotlin Dataframe library is an idiomatic Kotlin DSL defining such operations. The process of working with data frame is often called data wrangling which is the process of transforming and mapping data from one "raw" data form into another format that is more appropriate for analytics and visualization. The goal of data wrangling is to assure quality and useful data.
Features
- The Kotlin DataFrame library provides an ability to read and present data from different sources including not only plain CSV but also JSON or SQL databases
- Hierarchical data layout also opens a possibility of converting any objects structure in application memory to a data frame and vice versa
- The Kotlin DataFrame library provides a mechanism of on-the-fly generation of extension properties that correspond to the columns of a data frame
- Columns can store objects of any type, not only numbers or strings
- If all columns of DataFrame are presented in some other DataFrames, then the first one could be a superclass for latter
- All operations on DataFrame produce new instance, while underlying data is reused wherever it's possible
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