Data Visualization with Kotlin for Finance

Data representation and analysis in finance has a large literature already present in R and Python, two of the most common suspects. They have the community, tooling and a long tradition. But what about Kotlin with some of the libraries in the family, like DataFrame and Kandy? Kotlin, traditionally known for its focus in mobile and backend development, has emerged as a strong contender in the data science space. This session explores the potential of Kotlin for financial data analysis, focusing on the use of the DataFrame library and the Kandy visualization framework.

Enrique will demonstrate how Kotlin provides a rich, statically typed language environment, ensuring safety, conciseness, and performance in handling large datasets commonly encountered in financial contexts. DataFrame provides the capacity to manipulate structured data, while Kandy enables high-quality visualizations.

This presentation will also provide a comparative analysis between Kotlin, R, and Python. We will examine common use cases such as dividend history, stock valuation based on price and yields. While R and Python have established ecosystems for data science, Kotlin's performance, tooling, and modern features offer new possibilities for finance professionals looking for a more efficient alternative.

Lernziele

• Understand the basics of Kotlin DataFrame and Kandy for working with structured data and creating rich visualizations
  
• Learn how to build a simple end-to-end data visualization pipeline in Kotlin
  
• Discover how Kotlin compares to Python and R in terms of developer experience, performance, and safety in data-related tasks