R Novice Gapminder
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pythonidae | 810 | 2 years ago | 5 | other | Julia | |||||
| Curated decibans of scientific programming resources in Python. | ||||||||||
| R Novice Gapminder | 153 | 12 days ago | 25 | other | R | |||||
| R for Reproducible Scientific Analysis | ||||||||||
| R Novice Inflammation | 147 | a month ago | 49 | other | R | |||||
| Programming with R | ||||||||||
| Scid | 79 |  | 2 | 4 | 3 years ago | 6 | April 30, 2020 | 8 | bsl-1.0 | D |
| Scientific library for the D programming language | ||||||||||
| Introduction To Programming For Geoscientists | 41 | 4 years ago | other | Jupyter Notebook | ||||||
| Introduction to programming for geoscientists. Designed for 1st year undergraduates. Based on the book "A Primer on Scientific Programming with Python" by Hans Petter Langtangen. | ||||||||||
| Python_primer | 34 | 6 years ago | mit | Python | ||||||
| Solutions to exercises in 'A Primer on Scientific Programming with Python' by Hans Petter Langtangen | ||||||||||
| Programmingcoursedifa | 33 | a month ago | 1 | HTML | ||||||
| slides for the programming course of the physics department of the university of Bologna | ||||||||||
| Scientific_programming | 32 | 20 days ago | 9 | cc-by-4.0 | Jupyter Notebook | |||||
| Lectures notes of the scientific programming course at the University of Innsbruck | ||||||||||
| Lovelace Website | 23 | 2 years ago | 41 | mit | HTML | |||||
| 📜 Back end and front end code for the Project Lovelace website. | ||||||||||
| Pythonresources | 16 | a year ago | 1 | |||||||
| A list of openly available resources for learning and using the Python programming language. | ||||||||||
R for Reproducible Scientific Analysis
An introduction to R for non-programmers using the Gapminder data.
Please see https://swcarpentry.github.io/r-novice-gapminder for a rendered version of this material,
the lesson template documentation
for instructions on formatting, building, and submitting material,
or run make in this directory for a list of helpful commands.
The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
Note that this workshop focuses on the fundamentals of the programming language R, and not on statistical analysis.
The lesson contains more material than can be taught in a day. The [instructor notes page]({{ page.root }}/guide) has some suggested lesson plans suitable for a one or half day workshop.
A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
Current Maintainers:
Previous Maintainers:
- David Mawdsley
- Jeff Oliver
- Tom Wright
