The Essential Toolbox of Data Science: Python, R, Git, and Docker.

Clicks: 294
ID: 83321
2020
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Ranked #66 of 139 articles by views in methods in molecular biology (clifton, nj)

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Abstract
The daily work in data science involves a set of essential tools: the programming languages Python and R, the version control tool Git and the virtualization tool Docker. Proficiency in at least one programming language is required for data science. R is tied to a computing environment that focuses on statistics, in which many new algorithms in genomics and biomedicine are first published. Python has a root in system administration, and is a superb language for general programming. Version control is critical to managing complex projects, even if software development is not involved. Docker container is becoming a key tool for deployment, portability, and reproducibility. This chapter provides a self-contained practical guide of these topics so that readers can use it as a reference and to plan their training.
Reference Key
pittard2020themethods Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pittard, W Stephen;Li, Shuzhao;
Journal methods in molecular biology (clifton, nj)
Year 2020
DOI
10.1007/978-1-0716-0239-3_15
URL
Keywords
Python r bioinformatics data science docker git version control virtualization

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