R for Excel Users
Chapter 1 Welcome
Hello! This is a course taught by Dr. Julie Stewart Lowndes and Dr. Allison Horst at the RStudio Conference: January 27-28 in San Francisco, California.
This course is for Excel users who want to add or integrate R and RStudio into their existing data analysis toolkit. It is a friendly intro to becoming a modern R user, full of tidyverse, RMarkdown, GitHub, collaboration & reproducibility.
This book is written to be used as a reference, to teach, or as self-paced learning. And also, awesomely, it’s created with the same tools and practices we will be talking about: R and RStudio — specifically bookdown — and GitHub. It is being fine-tuned but the most recent version is always available:
This book: https://rstudio-conf-2020.github.io/r-for-excel/
Book GitHub repo: https://github.com/rstudio-conf-2020/r-for-excel
Accompanying slides: Google Slides
We are environmental scientists who use and teach R in our daily work. We both work at the University of California Santa Barbara, USA.
Julie Lowndes is a Senior Fellow and Director of Openscapes at the National Center for Ecological Analysis and Synthesis.
Allison Horst is a Lecturer of Data Science & Statistics at the Bren School of Environmental Science and Management. She is also Artist in Residence at RStudio!
|Time||Day 1||Day 2|
|9-10:30||Overview, R & RStudio, RMarkdown (JL)||Tidying (AH)|
|11-12:30||Intro to GitHub (JL)||Filters & joins (AH)|
||Collaborating & getting help (JL)|
|15:30-17:00||Pivot Tables &
Before the training, please do the following (20 minutes). All software is free.
- Download and install R and RStudio
- Create a GitHub account
- Download and install Git
- Git: https://git-scm.com/downloads
- Follow your operating system’s normal installation process. Note: you will not see an application called Git listed but if the installation process completed it was likely successful, and we will confirm together
- Download workshop data
- Google Drive folder: r-for-excel-data
- Save it temporarily somewhere you will remember; we will move it together
1.3 Data citations
We use the following data from the Santa Barbara Coastal Term Ecological Research and National Oceanic and Atmospheric Administration in this workshop:
- Description: Reef fish abundance, SB coast
- Link: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=17&revision=newest
- Citation: Reed D. 2018. SBC LTER: Reef: Kelp Forest Community Dynamics: Fish abundance. Environmental Data Initiative. doi.
- Description: Invertebrate counts, SB coast
- Link: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=19&revision=newest
- Citation: Reed D. 2018. SBC LTER: Reef: Kelp Forest Community Dynamics: Invertebrate and algal density. Environmental Data Initiative. doi.
- Description: Giant kelp abundance and size, SB coast
- Link: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=18&revision=newest
- Citation: Reed D. 2018. SBC LTER: Reef: Kelp Forest Community Dynamics: Abundance and size of Giant Kelp (Macrocystis Pyrifera), ongoing since 2000. Environmental Data Initiative. doi.
- lobsters.xlsx and lobsters2.xlsx
- Description: Lobster size, abundance and fishing pressure (SB coast)
- Link: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=77&revision=newest
- Citation: Reed D. 2019. SBC LTER: Reef: Abundance, size and fishing effort for California Spiny Lobster (Panulirus interruptus), ongoing since 2012. Environmental Data Initiative. doi.
- Description: NOAA Commercial Fisheries Landing data (1950 - 2017)
- Link: https://www.st.nmfs.noaa.gov/commercial-fisheries/commercial-landings/
- Source: Fisheries Statistics Division of the NOAA Fisheries
- Description: Algal cover, invertebrates and substrates near Santa Cruz Island
- Link: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=38&revision=newest
- Citation: Schmitt R. J., S. J. Holbrook. 2012. SBC LTER: Santa Cruz Island: Cover of Algae, Invertebrates and Benthic Substrate. Environmental Data Initiative. doi.
- ca_np.csv and ci_np.xlsx
- Description: US National Parks visitation data (1904 - 2016)
- Link: https://data.world/inform8n/us-national-parks-visitation-1904-2016-with-boundaries
- Source: Data originally accessed from the US Department of the Interior National Park Service’s Integrated Resource Management Applications data portal (https://irma.nps.gov/)