
- 200 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.
Key Features
- overview: breakdown of complex data science software stacks into core components
- applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software
- reader guidance: different entry points and rich references to deepen the understanding of selected aspects
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Information
Table of contents
- Cover Page
- Half-Title Page
- Series Page
- Title Page
- Copyright Page
- Contents
- List of Figures
- List of Tables
- Preface
- Acknowledgments
- 1 Introduction
- 2 Stack: A Developer's Toolkit
- 3 Programming 101
- 4 Interaction Environment
- 5 Git Version Control
- 6 Data Management
- 7 Infrastructure
- 8 Automation
- 9 Community
- 10 Publishing and Reporting
- 11 Case Studies
- Glossary
- References
- Index
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