Overview
Over two sessions, learn how to use the Tidyverse to work with data in R. The Tidyverse is a collection of R packages designed to help you manipulate, clean and analyse data. This course will introduce you to the functionality of several key packages, while also discussing some of the conventions the Tidyverse uses when working with data. By the end of the course, participants should feel confident to continue using the Tidyverse to work with datasets in R.
Course objectives
On completion of this series of workshops, participants will:
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Be able to explain what is meant by the ‘tidy’ format (a widely recognised convention for structuring data).
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Know how to read tabular data from a file to a dataframe.
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Be able to manipulate datasets, including creating new variables, filtering data, summarising and sorting data.
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Know how to join multiple datasets together and reshape data.
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Learn how to work with strings and dates (as time permits).
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Gain hands on experience working with R notebooks for analysis.
Pre-requisite knowledge
This course is for participants who already have some programming experience with R. It assumes familiarity with things like: creating and setting variables, the basic data structures (dataframes, vectors, lists), using functions, running R code and viewing console output, installing R packages and using R packages in your own code. Experience with R notebooks is not required.
Workshop format
This is a hybrid workshop that runs over 2 sessions. The schedule can be found here. Please note that you will be expected to attend both sessions.
Upcoming course dates
The sessions will be delivered according to the following timetable.
| Session | Dates | Time | Venue |
|---|---|---|---|
| Session 1 | 12 March 2024 | 1pm – 4pm | Training Room 4, Old Library, Streatham Campus |
| Session 2 | 19 March 2024 | 1pm – 4pm | Training Room 4, Old Library, Streatham Campus |
Registration for this course is handled by University of Exeter Researcher Development (see the Software Training section).
Set-up instructions for attendees
If you have registered for this course you can find the instructions for setting up your computer and the course materials here. Also take a look at additional resources and supplementary material for the course.
Course notes
If you are unable to attend any of the dates above, the full course notes are freely available for you to work through. Please note that you will need to have completed the set up instructions linked above.
Follow-up courses
On completion of this course you will be invited to join a network of other participants. This is a supportive forum for you to ask follow-up questions and receive invites to follow-on courses.
Feedback
Please remember to complete a feedback survey at the end of the course. Our workshops are under continual review and your experiences, suggestions and criticism are invaluable for shaping the direction of this initiative. This is especially important if you complete the materials in your own time, as it enables us to measure impact. If you have ideas on other courses you would like to see then please contact Eilis Hannon: E.J.hannon@exeter.ac.uk.
Join us
If you are interested in becoming part of our community of workshop helpers, leaders and developers please contact Eilis Hannon: E.J.Hannon@exeter.ac.uk.
Acknowledgements
This course was developed by members of the University of Exeter’s Research Software Engineering Group who are enthusiastic about sharing their skills with the wider research community.
If you have benefited in any way from this course and want to support its long term sustainability then please take the time to complete our feedback survey, recommend it to your colleagues, and enthuse about it to your senior leadership team.
This workshop is brought to you by:
- The University of Exeter Research Software Engineering Group
- The Institute of Data Science and Artificial Intelligence
- The University of Exeter Researcher Development Programme
- The University of Exeter Doctoral College
Course material and datasets
The course material is adapted from Eliza Wood’s Tidyverse: Data wrangling & visualization course, which is licensed under Creative Commons BY-NC-SA 4.0. This in itself is based on material from UC Davis’s R-DAVIS course, which draws heavily on Carpentries R lessons. The penguin artwork is from Allison Horst @allison_horst.
The following datasets are used throughout the course:
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Horst AM, Hill AP, Gorman KB (2020). palmerpenguins: Palmer Archipelago (Antarctica) penguin data. R package version 0.1.1. https://allisonhorst.github.io/palmerpenguins/. doi: 10.5281/zenodo.3960218.
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Palmer Station Antarctica LTER. 2023. Daily weather averages for Palmer Station, Antarctica (1989-2023) ver 9. Environmental Data Initiative. https://doi.org/10.6073/pasta/3eefb45dbfb784c3cabe3690ea46fe9e (accessed 2024-01-08). (Further details available from the data README in the course materials and relevant course notebooks.)
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Friedlingstein, P., et al. (2023). Global Carbon Budget 2023, Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023. Fossil CO2 emissions by country (territorial) data obtained from https://globalcarbonbudgetdata.org/downloads/latest-data/National_Fossil_Carbon_Emissions_2023v1.0.xlsx (accessed 2024-02-28). We acknowledge the Global Carbon Project, which is responsible for the Global Carbon Budget and we thank the fossil carbon emissions modelling groups for producing and making available their model output. (Further details available from the data README in the course materials and relevant course notebooks.)