A repository to house materials for a 2 day course introducing participants to data science using R.

The goal of this 2 day workshop is to teach new-to-programming data professionals to import data, clean up and summarize a data set, and make some static data visualizations using the program R. This is an introductory course to programming, specifically programming with R. R is a popular statistical computing language, commonly used in many scientific disciplines for statistical analysis, generating production-quality graphics, and automating data workflow tasks. The workshop content will follow best practices for using R for data analysis, giving attendees a foundation in the fundamentals of R and scientific computing.

• Anyone who works with data or who is interested in learning efficient ways to make meaning from data
• Anyone comfortable troubleshooting issues on their computer
• Anyone keen to learn a programming language

Course Notes: https://bcgov.github.io/ds-intro-to-r-2-day/

• Introduction to Course (30 min) (Bonnie)
• Demo (10 min) (Bonnie)
• Introduction to R & RStudio (50 minutes) (Bonnie)
• BREAK ☕
• Seeking Help in R (15 minutes) (Julie)
• Project Management with RStudio (60 minutes) (Julie)
• Lunch
• Data Structures (75 minutes) (Bonnie)
• Extra Practice + Questions (15 minutes)
• BREAK ☕
• Data Manipulation with dplyr (90 minutes) (Julie)
• Day 1 Wrap-up + Questions (15 minutes)

• Review + Questions (30 minutes)
• Making Publication Quality Plots with ggplot2 Pt. 1 (60 minutes) (Bonnie)
• BREAK ☕
• Making Publication Quality Plots with ggplot2 Pt. 2 (60 minutes) (Bonnie)
• Extra Practice + Questions (15 minutes)
• Lunch
• Data Manipulation with tidyr (60 minutes) (Julie)
• Extra Practice + Questions (15 minutes)
• BREAK ☕
• Joins with dplyr (45 minutes) (Julie)
• Mini-Analysis Project: (45 minutes)
• Day 2 Wrap-up + Questions (15 minutes)

Most of the above lesson material is sourced or an adaptation of the Software Carpentry Foundation (now The Carpenties) R for Reproducible Scientific Analysis lesson material: Thomas Wright and Naupaka Zimmerman (eds): Software Carpentry: R for Reproducible Scientific Analysis. Version 2016.06, June 2016, https://github.com/swcarpentry/r-novice-gapminder, 10.5281/zenodo.57520.

The R Markdown sections also draw material from Nicholas Tierney's excellent R Markdown for Scientists course which is available here: https://rmd4sci.njtierney.com/

• Instructors: Bonnie Robert, Julie Hawkins, Stephanie Yurchuk
• Suggested pre-reading: Good Enough Practices for Scientific Computing
• Course material: https://bcgov.github.io/ds-intro-to-r-2-day/
• What we actually did on the day:

• Instructors: Andy Teucher, Sam Albers & Bonnie Robert
• Suggested pre-reading: Good Enough Practices for Scientific Computing
• Course material: https://bcgov.github.io/ds-intro-to-r-2-day/
• What we actually did on the day: https://github.com/bcgov/ds-intro-to-r-2-day/tree/master/what_we_actually_did/online-Feb-2022

• Instructors: Sam Albers, Stephanie Hazlitt, Genevieve Perkins & Andy Teucher
• Suggested pre-reading: Good Enough Practices for Scientific Computing
• Course material: https://bcgov.github.io/ds-intro-to-r-2-day/
• What we actually did on the day: https://github.com/bcgov/ds-intro-to-r-2-day/tree/master/what_we_actually_did/online-May-6-and-7-2020

To report bugs/issues/feature requests, please file an issue.

If you would like to contribute, please see our CONTRIBUTING guidelines.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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Original Work Copyright © Software Carpentry, content modified by the Province of British Columbia.

This work is licensed under the Creative Commons Attribution 4.0 International License.
To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.

This project was created using the bcgovr package.