mromanello/ADA-DHOxSS 开源项目中文解读：技术栈、适用场景与上手建议

项目介绍

mromanello/ADA-DHOxSS 是一个托管在 GitHub 上的开源项目，主要使用 Jupyter Notebook 编写，采用 MIT License 许可证，目前获得 41 个 Star、13 次 Fork。

仓库全名: mromanello/ADA-DHOxSS

README 摘要

ADA-DHOxSS Teaching materials for the Applied Data Analysis (ADA) activity strand at the Digital Humanities Oxford Summer School. The authors of these materials are Giovanni Colavizza and Matteo Romanello. Syllabus 2023 Convenors: Matteo Romanello (University of Lausanne) Nilo Pedrazzini (The Alan Turing Institute/University of Oxford) Day.session | Topic | Materials | :| 1.1 | Introduction | slides | 1.2 | Data…

完整内容见 GitHub 原始 README 或本页。

常见问题

ADA-DHOxSS 用什么语言开发？

主要使用 Jupyter Notebook 编写，采用 MIT License 许可证，目前有 41 个 Star。

ADA-DHOxSS 可以免费商用吗？

如何获取 ADA-DHOxSS 的源码？

可以直接克隆仓库：git clone https://github.com/mromanello/ADA-DHOxSS.git，默认分支为 master；安装与运行步骤见仓库 README。

ADA-DHOxSS 最近还在维护吗？

仓库最近一次更新为 1月7日，当前没有未关闭的 Issue；Star 数为 41，可作为社区活跃度的参考。

关于

Teaching materials for the Applied Data Analysis course at DHOxSS. Data science methods to analyse humanities data.

applied-data-analysis data-science dhoxss digital-humanities humanities

MIT License
41 Stars
13 Forks
5 Watching

描述取自 GitHub 官方 API，中文内容由 GitRead 中文社区编辑团队整理。

简要分析

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活跃

GitHub

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Jupyter Notebook

Release

ADA-DHOxSS20232023年9月19日
ADA-DHOxSS20222022年10月4日
ADA-DHOxSS20192019年7月28日

贡献者

mromanello

npedrazzini

ADA-DHOxSS

Teaching materials for the Applied Data Analysis (ADA) activity strand at the Digital Humanities Oxford Summer School. The authors of these materials are Giovanni Colavizza and Matteo Romanello.

Syllabus 2023

Convenors:

Matteo Romanello (University of Lausanne)
Nilo Pedrazzini (The Alan Turing Institute/University of Oxford)

Day.session	Topic	Materials
1.1	Introduction	slides
1.2	Data carpentry	slides + notebook
1.3	Python refresher	notebook
1.4	The Python data analysis stack, pt. I	notebook
2.1	Tidy data pt. I-II	slides + notebook
2.2	Tidy data pt. III	notebook
2.3	Data transformation with Pandas	notebook
3.1	Applied data analysis, pt. I: The basics	slides + notebook
3.2	Applied data analysis, pt. II: Advanced	notebook
4.1	Applied data analysis, pt. III: Visualization	slides + notebook
4.2	Applied data analysis, pt. IV: Mapping	From Melanie Walsh’s ICAP
5.1	Social network analysis	From Melanie Walsh’s ICAP
5.2	Communicating results and epilogue	slides

Previous editions

2022: Giovanni and Matteo Romanello (archived teaching materials)
2020-2021: hiatus due to global pandemic
2019: Giovanni Colavizza and Matteo Romanello (archived teaching materials)

Acknowledgements

Inspiration for ADA was given by the following courses/teachers:

[ICAP] Melanie Walsh’s Introduction to Cultural Analytics & Python https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html
Ryan Cordell’s Humanities Data Analysis http://s17hda.ryancordell.org/schedule/
Massimo Franceschet’s Dear Data Science http://users.dimi.uniud.it/~massimo.franceschet/ds/syllabus/syllabus.html
Bob West’s Applied Data Analysis (ADA) https://dlab.epfl.ch/teaching/fall2018/cs401

References

Garrett Grolemund and Hadley Wickham, R for data science, https://r4ds.had.co.nz/index.html
Julia Silge and David Robinson, Text mining with R: A tidy approach, https://www.tidytextmining.com
Folgert Karsdorp, Mike Kestemont and Allen Riddell, Humanities Data Analysis: Case Studies with Python, https://www.humanitiesdataanalysis.org

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ADA-DHOxSS

项目介绍

README 摘要

常见问题

相关仓库

关于

简要分析

语言占比

Release

贡献者

ADA-DHOxSS

Syllabus 2023

Previous editions

Acknowledgements

References

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