| title | Resource Introduction |
|---|
Each student will be expected to introduce an R-related resource that is relevant to their research interests in a 5 minute presentation during a class session. Most students elect to introduce an R package, but you could also introduce a data source, interesting blog, etc., as long as it's relevant to the course. If you are aren't sure, please ask Professor Wilson. The objectives are:
- Learn how to find/download/install a new package and learn how to use it
- Teach your peers about existing R packages that may be useful in their research
The presentation must include:
- Brief introduction: what does the package do and why is it useful? (1-2 slides, 1 minute)
- Author introduction: a short background (affiliation and other packages, etc.) on at least one of the package authors (1 slide, 1 minute)
- Simple demonstration of package code: example input/output from the examples or custom coded examples (2-3 slides, 3 minutes)
There will not be time to actually run any code on-the-fly during your presentation. Instead, use RMarkdown to create a presentation (html) or markdown (md) file so that you can simply display it during class (like the lectures). Then paste your github link into the schedule spreadsheet so we can easily open/view it during class. For the first few weeks, you may simply share your screen and use a powerpoint or other presentation software.
To select a package, I recommend starting with the views on CRAN for a topic of interest. Then read the narrative in the task view for something interesting to you and install the package in R with install.package("packagename") in R and take a look at what it can do. Most package functions include sample code that performs a function. For example, if I was introducing the dplyr package, I might choose the filter() function. If you look in the help you will find a section called "Examples" that you can use for your example code in your presentation. All you have to do is copy-paste it from the help into the R console and them summarize what it's doing in your presentation. For example, I might demonstrate (from the filter() documentation) that the following code will select all characters from Star Wars that are human.
library(dplyr)
filter(starwars, species == "Human")## # A tibble: 35 x 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke S… 172 77 blond fair blue 19 male mascu…
## 2 Darth … 202 136 none white yellow 41.9 male mascu…
## 3 Leia O… 150 49 brown light brown 19 fema… femin…
## 4 Owen L… 178 120 brown, grey light blue 52 male mascu…
## 5 Beru W… 165 75 brown light blue 47 fema… femin…
## 6 Biggs … 183 84 black light brown 24 male mascu…
## 7 Obi-Wa… 182 77 auburn, wh… fair blue-gray 57 male mascu…
## 8 Anakin… 188 84 blond fair blue 41.9 male mascu…
## 9 Wilhuf… 180 NA auburn, gr… fair blue 64 male mascu…
## 10 Han So… 180 80 brown fair brown 29 male mascu…
## 11 Wedge … 170 77 brown fair hazel 21 male mascu…
## 12 Jek To… 180 110 brown fair blue NA male mascu…
## 13 Palpat… 170 75 grey pale yellow 82 male mascu…
## 14 Boba F… 183 78.2 black fair brown 31.5 male mascu…
## 15 Lando … 177 79 black dark brown 31 male mascu…
## 16 Lobot 175 79 none light blue 37 male mascu…
## 17 Mon Mo… 150 NA auburn fair blue 48 fema… femin…
## 18 Arvel … NA NA brown fair brown NA male mascu…
## 19 Qui-Go… 193 89 brown fair blue 92 male mascu…
## 20 Finis … 170 NA blond fair blue 91 male mascu…
## 21 Shmi S… 163 NA black fair brown 72 fema… femin…
## 22 Mace W… 188 84 none dark brown 72 male mascu…
## 23 Gregar… 185 85 black dark brown NA male mascu…
## 24 Cordé 157 NA brown light brown NA fema… femin…
## 25 Cliegg… 183 NA brown fair blue 82 male mascu…
## 26 Dormé 165 NA brown light brown NA fema… femin…
## 27 Dooku 193 80 white fair brown 102 male mascu…
## 28 Bail P… 191 NA black tan brown 67 male mascu…
## 29 Jango … 183 79 black tan brown 66 male mascu…
## 30 Jocast… 167 NA white fair blue NA fema… femin…
## 31 Raymus… 188 79 brown light brown NA male mascu…
## 32 Finn NA NA black dark dark NA male mascu…
## 33 Rey NA NA brown light hazel NA fema… femin…
## 34 Poe Da… NA NA brown light brown NA male mascu…
## 35 Padmé … 165 45 brown light brown 46 fema… femin…
## # … with 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>
Here is an example presentation about the ggrepel package that was built using this R Markdown file, which is also visible on github.