https://github.com/mnr/r-for-data-science-lunchbreak-lessons
Source files for the LinkedIn Learning Course
https://github.com/mnr/r-for-data-science-lunchbreak-lessons
data-science linkedin-learning mark-niemann-ross r rlang rstats tutorials
Last synced: 5 months ago
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Source files for the LinkedIn Learning Course
- Host: GitHub
- URL: https://github.com/mnr/r-for-data-science-lunchbreak-lessons
- Owner: mnr
- License: gpl-3.0
- Created: 2017-04-20T23:09:10.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2024-03-03T07:33:55.000Z (over 2 years ago)
- Last Synced: 2025-09-04T20:31:53.522Z (10 months ago)
- Topics: data-science, linkedin-learning, mark-niemann-ross, r, rlang, rstats, tutorials
- Language: HTML
- Homepage: https://linkedin-learning.pxf.io/r_lunchbreak
- Size: 16.7 MB
- Stars: 90
- Watchers: 19
- Forks: 54
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Citation: CITATION.cff
- Support: support text files/asciiDailyTemp.txt
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README
# R Language Mini Tutorials
[Source files for the LinkedIn Learning Course](http://niemannross.com/link/rlunchlessons)
Programming is learned in small bits. You build on basic concepts. You transfer the knowledge you already have to the next language. Lunch Break Lessons teaches R—one of the most popular programming languages for data analysis and reporting—in short lessons that expand on what existing programmers already know.
The five minutes you spend each week will provide you with a building block you can use in the next two hours at work. Review language basics, discover methods to improve existing R code, explore new and interesting features, and learn about useful development tools and libraries that will make your time programming with R that much more productive.
Copyright Mark Niemann-Ross, 2017 - [join the discussion](https://groups.google.com/d/forum/r-for-data-science-lunchbreak-lessons) - [My LinkedIn Profile](https://www.linkedin.com/in/markniemannross/) - [My Github account](https://github.com/mnr) - [More of my courses at LinkedIn Learning](https://linkedin-learning.pxf.io/mnr) - [niemannross.com](http://www.niemannross.com)
# Index to topics covered in my LinkedIn Learning R courses
[apply](https://linkedin-learning.pxf.io/apply)
[apropos](https://linkedin-learning.pxf.io/apply)
[array](https://linkedin-learning.pxf.io/rweekly_array)
[barplot()](https://linkedin-learning.pxf.io/rweekly_factor)
[cbind](https://linkedin-learning.pxf.io/rweekly_cbind)
[change
variable](https://linkedin-learning.pxf.io/data.frame_read_update)
[character](https://linkedin-learning.pxf.io/rweekly_atomics)
[complex](https://linkedin-learning.pxf.io/rweekly_atomics)
[create
variable](https://linkedin-learning.pxf.io/data.frame_read_update)
[data()](https://linkedin-learning.pxf.io/rwkly_dataSets)
[data.frame](https://linkedin-learning.pxf.io/rweekly_dataframe)
[delete
variable](https://linkedin-learning.pxf.io/data.frame_read_update)
[dimnames](https://linkedin-learning.pxf.io/rweekly_array)
[factor](https://linkedin-learning.pxf.io/rweekly_factor)
[integer](https://linkedin-learning.pxf.io/rweekly_atomics)
[lapply](https://linkedin-learning.pxf.io/apply)
[levels()](https://linkedin-learning.pxf.io/rweekly_factor)
[list](https://linkedin-learning.pxf.io/rweekly_lists)
[logical](https://linkedin-learning.pxf.io/rweekly_atomics)
[matrix](https://linkedin-learning.pxf.io/rweekly_matrix)
[merge](https://linkedin-learning.pxf.io/rweekly_sortmerge)
[nlevels()](https://linkedin-learning.pxf.io/rweekly_factor)
[order](https://linkedin-learning.pxf.io/rweekly_sortmerge)
[ordered()](https://linkedin-learning.pxf.io/rweekly_factor)
[raw](https://linkedin-learning.pxf.io/rweekly_atomics)
[rbind](https://linkedin-learning.pxf.io/rbind)
[real](https://linkedin-learning.pxf.io/rweekly_atomics)
[sort](https://linkedin-learning.pxf.io/rweekly_sortmerge)
[str()](https://linkedin-learning.pxf.io/rweekly_lists)
[string](https://linkedin-learning.pxf.io/rweekly_atomics)
[sum()](https://linkedin-learning.pxf.io/rweekly_factor)
[t()](https://linkedin-learning.pxf.io/rweekly_matrix)
[table()](https://linkedin-learning.pxf.io/rweekly_factor)
[vector math](https://linkedin-learning.pxf.io/rweekly_vectormath)
[vector subsetting](https://linkedin-learning.pxf.io/rweekly_subset)
[vectors](https://linkedin-learning.pxf.io/rwkly_vector)