Julia for Data Analysis

Julia is a powerful programming language for data analysis that offers fast code execution, expressive syntax, and easy-to-use features for working with tabular data, statistical analysis, predictive models, and data processing pipelines. This book teaches you how to use Julia for data science tasks, including reading and writing data, visualizing data, performing statistical analysis, building predictive models, and creating complex data processing pipelines. It is written by a top contributor to Julia and a lead developer of Julia's core data package DataFrames.jl, and is suitable for data scientists familiar with Python or R, with no prior experience with Julia required.

Format: Paperback / softback
Length: 426 pages
Publication date: 10 January 2023
Publisher: Manning Publications

Julia is a powerful high-performance programming language with many developer-friendly features like garbage collection, dynamic typing, just-in-time compilation, and a flexible approach to concurrent, parallel, and distributed computing. Although Julia's strong numerical programming features make it a favorite of data scientists, it is also an awesome general-purpose programming language.

Julia for Data Analysis is a comprehensive guide that will help you master core data analysis skills using the Julia programming language. Written by Bogumił Kamiński, a top contributor to Julia and a lead developer of Julia's core data package DataFrames.jl, this book is designed to teach you how to perform essential data science tasks with Julia.

The book begins by introducing you to the basics of Julia, including its syntax, data types, and basic operations. It then moves on to cover more advanced topics such as time series data, predictive models, popularity ranking, and more. You will learn how to read and write data in various formats, work with tabular data, perform statistical analysis, build predictive models, and create complex data processing pipelines.

One of the key strengths of Julia is its expressive and easy-to-use syntax, which makes it ideal for data scientists who want to write production-quality code quickly. The book also emphasizes the importance of utilizing Julia's core features for data gathering, visualisation, and working with data frames, which are widely used in data science and scientific computing.

Throughout the book, you will engage in hands-on projects that will help you apply the knowledge you have learned. These projects cover a range of topics, from working with real-world data sets to building your own predictive models. By the end of the book, you will have a solid understanding of Julia and be able to use it to solve complex data analysis problems.

Whether you are a data scientist familiar with Python or R or someone who is new to programming, Julia for Data Analysis is an excellent resource for learning this powerful language. With its clear and concise explanations, hands-on projects, and emphasis on practical applications, this book will help you take your data analysis skills to the next level.

In conclusion, Julia for Data Analysis is a must-read for anyone who wants to master core data analysis skills using the Julia programming language. Whether you are a data scientist, software engineer, or researcher, this book will provide you with the knowledge and tools you need to succeed in your field. So why wait? Start learning Julia today and unlock the full potential of data science!

Weight: 832g
Dimension: 187 x 236 x 31 (mm)
ISBN-13: 9781633439368