Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-12T22:30:29.995Z Has data issue: false hasContentIssue false

Chapter 20 - Helpful tools

from Interlude — Good practices for scientific computing

Published online by Cambridge University Press:  06 June 2024

James Bagrow  and
Yong‐Yeol Ahn
James Bagrow
Affiliation:
University of Vermont
Yong‐Yeol Ahn
Affiliation:
Indiana University, Bloomington
Get access

Summary

Many tools exist to help scientists work computationally. In addition to general-purpose and domain-specific programming languages, a wide assortment of programs exist to accomplish specific tasks. We call attention to a number of tools in this chapter, focusing on good practices when using them, good practices computationally and good practices scientifically. Important computing tools for data scientists include computational notebooks, data pipelines and file transfer tools, UNIX-style operating systems, version control systems, and data backup systems. Of course, the world of computing moves fast, and tools are always coming and going, so we conclude with advice and a brief workflow to guide you through evaluating new tools.

Keywords

data science toolscomputational notebooksJupyterdata pipelinessnakemakesecure file transfer toolsUNIX and UNIX-like operating systemsgit and version control systemsdata backup systemsfinding and evaluating new computing tools
Type
Chapter
Information
Working with Network Data
A Data Science Perspective
 , pp. 301 - 314
Publisher: Cambridge University Press
Print publication year: 2024

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Helpful tools
  • James Bagrow, University of Vermont, Yong‐Yeol Ahn, Indiana University, Bloomington
  • Book: Working with Network Data
  • Online publication: 06 June 2024
  • Chapter DOI: https://doi.org/10.1017/9781009212601.024
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Helpful tools
  • James Bagrow, University of Vermont, Yong‐Yeol Ahn, Indiana University, Bloomington
  • Book: Working with Network Data
  • Online publication: 06 June 2024
  • Chapter DOI: https://doi.org/10.1017/9781009212601.024
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Helpful tools
  • James Bagrow, University of Vermont, Yong‐Yeol Ahn, Indiana University, Bloomington
  • Book: Working with Network Data
  • Online publication: 06 June 2024
  • Chapter DOI: https://doi.org/10.1017/9781009212601.024
Available formats
×