TypeScript for Data Science: From Prototype to Production

The book "TypeScript for Data Science" is a unique practical guide that combines the power of TypeScript's static typing with the flexibility of data analysis tools. Unlike traditional data science books focused solely on Python, this work offers a fresh perspective: how to use TypeScript to build reliable, scalable, and easily maintainable projects in the fields of data processing and machine learning.

What is this book about?

The book covers the full lifecycle of a data science project — from data collection and cleaning to model deployment in production. You will learn:

• How to set up an environment for a TypeScript data analysis project (Node.js, Deno, ts-node).
• How to work with tabular data using the danfojs and pandas-js libraries.
• How to use static typing to prevent errors during data processing.
• How to create visualizations with plotly.js and D3.js using TypeScript types.
• How to implement simple machine learning models (linear regression, k-nearest neighbors) in TypeScript.
• How to integrate TypeScript code with the Python ecosystem via Pyodide or REST services.
• How to write unit tests for data science components with Jest.

Who is this book for?

The book will be useful for:

• Data scientists and analysts who want to expand their toolkit and master TypeScript for production solutions.
• Frontend developers interested in data science who want to apply their TypeScript skills in a new domain.
• Students and teachers studying modern approaches to data analysis.
• Team leads and architects looking for ways to unify the technology stack within a team.

What will the reader learn?

After reading, you will be able to:

• Build data processing pipelines in TypeScript with full type safety.
• Create interactive dashboards and reports with typed visualizations.
• Implement and test simple ML algorithms without switching to Python.
• Integrate TypeScript solutions with existing Python infrastructure.
• Write clean, self-documenting code that is easy to maintain and extend.

The book contains numerous practical examples, ready-to-run code snippets, and exercises to reinforce the material. All examples are available in an online repository. Regardless of your current level — from beginner to experienced developer — you will find valuable insights and ready-made solutions for everyday data science tasks in this book.

Note: The book assumes basic familiarity with TypeScript or JavaScript. Knowledge of Python is not required but will be an advantage.