Master core data analysis skills using Julia. Interesting hands-on projects guide you through time series data, predictive models, popularity ranking, and more.

In Julia for Data Analysis you will learn how to:

• Read and write data in various formats
• Work with tabular data, including subsetting, grouping, and transforming
• Visualize your data
• Build predictive models
• Create data processing pipelines
• Create web services sharing results of data analysis
• Write readable and efficient Julia programs

Julia was designed for the unique needs of data scientists: it's expressive and easy-to-use whilst also delivering super-fast code execution. Julia for Data Analysis shows you how to take full advantage of this amazing language to read, write, transform, analyze, and visualize data—everything you need for an effective data pipeline. It’s written by Bogumil Kaminski, one of the top contributors to Julia, #1 Julia answerer on StackOverflow, and a lead developer of Julia’s core data package DataFrames.jl. Its engaging hands-on projects get you into the action quickly. Plus, you’ll even be able to turn your new Julia skills to general purpose programming!

Foreword by Viral Shah.

About the technology

Julia is a great language for data analysis. It’s easy to learn, fast, and it works well for everything from one-off calculations to full-on data processing pipelines. Whether you’re looking for a better way to crunch everyday business data or you’re just starting your data science journey, learning Julia will give you a valuable skill.

About the book

Julia for Data Analysis teaches you how to handle core data analysis tasks with the Julia programming language. You’ll start by reviewing language fundamentals as you practice techniques for data transformation, visualizations, and more. Then, you’ll master essential data analysis skills through engaging examples like examining currency exchange, interpreting time series data, and even exploring chess puzzles. Along the way, you’ll learn to easily transfer existing data pipelines to Julia.

What's inside

• Read and write data in various formats
• Work with tabular data, including subsetting, grouping, and transforming
• Create data processing pipelines
• Create web services sharing results of data analysis
• Write readable and efficient Julia programs

Why choose Julia for data analysis?

Julia is a powerful, easy-to-use language that offers the versatility of other languages often used in data science, along with lightning-quick execution they can’t deliver. And given its growing popularity in business, Julia skills are a lucrative addition to your résumé.

In Julia for Data Analysis, you’ll learn to write production-quality, highly performant Julia code for data science tasks, including those involving multi-threading, a process that can be challenging with other languages.

About the reader

For data scientists familiar with Python or R. No experience with Julia required.

Table of Contents

1 Introduction

PART 1 ESSENTIAL JULIA SKILLS

2 Getting started with Julia

3 Julia’s support for scaling projects

4 Working with collections in Julia

5 Advanced topics on handling collections

6 Working with strings

7 Handling time-series data and missing values

PART 2 TOOLBOX FOR DATA ANALYSIS

8 First steps with data frames

9 Getting data from a data frame

10 Creating data frame objects

11 Converting and grouping data frames

12 Mutating and transforming data frames

13 Advanced transformations of data frames

14 Creating web services for sharing data analysis results

Review

"You may wonder, why use Julia for Data Analysis? This book answers both the 'why' and the 'how.' I really enjoyed that the examples are real-world data—for instance, a set of chess puzzles with 2 million rows!"—From the Foreword by Viral Shah, Co-Founder and CEO of Julia Computing

"A brilliant guide to data analysis with Julia."—Kevin Cheung, Carleton University

"One of the best structured and well-written presentations of language fundamentals and analysis concepts that I've encountered. I highly recommend this book."—Maureen Metzger, Kumanu

"A solid, hands-on, and really enjoyable introduction to Julia."—Sonja Krause-Harder, Elastic

From the Foreword by Viral Shah, Co-Founder and CEO of Julia Computing

Julia for Data Analysis teaches you how to read and write data in different formats, transform data, analyze data, and create insightful visualizations using the Julia language. The book guides you through the most important features of Julia using plenty of hands-on examples, including analyzing currency exchange, time series data, ranking the popularity of chess puzzles, and more. You'll explore every step of the data science process, from acquiring and cleaning data right through to analysis. When you're finished, you'll be a confident Julia programmer ready to apply what you know.

About the Author

Bogumil Kaminski is one of the lead developers of DataFrames.jl—the core package for data manipulation in the Julia ecosystem. He has over 20 years of experience delivering data science projects for corporate customers. He has been teaching data science at the undergraduate and graduate levels for two decades.