Rust for Data Science: A Practical Guide to Data Analysis

The book "Rust for Data Science" is the first practical guide in Russian dedicated to using the Rust language in the field of data analysis and machine learning. If you are tired of slow Python scripts, memory issues, and instability, Rust will become your reliable tool for working with large volumes of data.

Unlike traditional approaches, Rust combines the performance of C/C++ with the safety of a modern language. This book will show you how to use these advantages to solve real-world data science tasks: from loading and cleaning data to building models and visualization.

Who is this book for?

• Data scientists and analysts looking to speed up their data processing pipelines.
• Python developers who want to learn Rust for working with big data.
• Backend engineers transitioning into data science and seeking performant solutions.
• Students in technical fields interested in modern approaches to data analysis.

What will you learn?

• Rust fundamentals: ownership, borrowing, lifetimes — no boring theory, only practice.
• Working with CSV, JSON, Parquet, and other data formats.
• Using the Polars library (an analog of Pandas) and ndarray for matrix computations.
• Creating charts with plotters and egui.
• Integrating Rust with Python via PyO3 — use the best parts of both worlds.
• Performance optimization: parallel computing, SIMD, working with GPU.

Book structure

The book is divided into 12 chapters, from simple to complex. You will start with installing tools and writing your first programs, then move on to full-fledged projects:

• Chapters 1-3: Introduction to Rust, data types, functions, error handling.
• Chapters 4-6: Reading and writing data, working with dataframes, statistics.
• Chapters 7-9: Visualization, machine learning (linear regression, clustering).
• Chapters 10-12: Advanced topics: memory safety, working with big data, model deployment.

Each chapter contains practical examples, ready-to-use code, and exercises for independent practice. At the end of the book, you will find an appendix with a cheat sheet for the main libraries.

Why should you read it?

Rust is actively being adopted in the data science industry: it is used at Amazon, Google, and Dropbox for processing terabytes of data. This book will give you a competitive advantage and teach you to write code that runs 10-100 times faster than Python equivalents, while being completely memory-safe.

Whether you are a beginner in Rust or an experienced developer, "Rust for Data Science" will become your go-to guide on the path to efficient data analysis.