PHP for Data Science: Data Processing and Analysis in PHP

Many believe that PHP is not suitable for serious data work. This book shatters that myth. "PHP for Data Science" is the first practical guide of its kind, showing how to leverage PHP's capabilities for collecting, processing, analyzing, and visualizing data, as well as building simple machine learning models.

The book is intended for intermediate and advanced PHP developers who want to expand their skills toward Data Science but are not ready to fully switch to Python or R. You already know how to write in PHP and want to apply your knowledge to work with data? This book is for you.

What you will learn from the book:

• Data Science Fundamentals in PHP: how to think statistically, which PHP libraries and extensions (PECL, php-ml, Rubix ML) to use for analysis.
• Data Collection and Cleaning: web scraping, working with APIs, processing CSV, JSON, XML, data cleaning and normalization.
• Statistical Analysis: calculating means, medians, correlations, building distributions, and hypothesis testing using PHP.
• Machine Learning: implementing algorithms (linear regression, decision tree, K-means clustering) using Rubix ML and php-ml.
• Data Visualization: creating charts and graphs using libraries (Chart.js, pChart, SVG rendering) directly in PHP.
• Database Integration: working with large datasets via PDO, MySQL, PostgreSQL, using indexes and query optimization.
• Practical Projects: building a recommendation system, log analysis, sales forecasting, and a business dashboard.

Unlike books on Python, this book does not require you to learn a new syntax or ecosystem. You stay in the familiar PHP environment but gain tools that are usually considered the prerogative of other languages. All code examples are real, working, and explained. You can immediately apply them in your projects.

The book is written by a practicing developer and analyst. It contains a minimum of theory and a maximum of practice. After reading it, you will be able to:

• automate data collection and processing in PHP;
• build simple machine learning models for classification and regression;
• create interactive reports and dashboards;
• make data-driven decisions without leaving the PHP ecosystem.

The book is suitable for both freelancers and teams working on web applications with analytics elements. If you want your PHP code to not just output data but analyze it, this book will become your indispensable assistant.