The Essential Toolbox of Data Science: Python, R, Git, and Docker.
Clicks: 173
ID: 83321
2020
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 |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.