The vitae package makes creating and maintaining a Résumé or CV with R Markdown simple. It provides a collection of LaTeX templates, with helpful functions to add content to the documents. These functions allow you to dynamically include CV entries from any data source, which is particularly useful when this data is obtained/prepared by other R packages. Some examples of what this allows you to do includes:
If using RStudio, a new CV document can be easily produced from one
of the templates provided in the package. This using the RStudio R
Markdown template selector, accessible via File >
New File > R Markdown..., and lastly
From Template. This will show a list of R Markdown
templates provided by all installed packages, and you should be able to
find some templates from the vitae package to use.
If not using RStudio, you can create a new *.Rmd
document and use an output format that is provided by the package. A
list of output formats provided by the package can be found on the
package website: https://pkg.mitchelloharawild.com/vitae/#templates.
Examples of a YAML header that use one of these output formats is shown
below.
Like other R Markdown documents, the file is split into two sections: the YAML header, and the main body.
The YAML header contains general entries that are common across many templates, such as your name, address and social media profiles. This is also where the output format (the CV template used) is specified, along with any options that the template supports. An example of what this header may look like is shown below:
<pre> <code>--- name: Mitchell O'Hara-Wild date: "r
format(Sys.time(), ‘%B,
%Y’)" profilepic: pic.jpg www: mitchelloharawild.com github: mitchelloharawild linkedin: mitchelloharawild twitter: mitchoharawild headcolor: 414141 docname: CV/Resume output: vitae::awesomecv
You can also see that the output is set to
vitae::awesomecv, which indicates that this CV uses the Awesome CV template.
Some of the templates allow for the choosing of a theme, or changing
other options. These options can be found in the help file for each
output format (say ?moderncv). For example, the
moderncv template allows for the selection of one of five
themes: “casual”, “classic”, “oldstyle”, “banking” or “fancy”. To change
default options of output formats you can modify the yaml as
follows:
Currently, the YAML header allows these fields to be specified:
name: Your namesurname: Your family or last nameposition: Your current workplace title or fieldaddress: Your addressdate: The current dateprofilepic: A local file path to an imagewww: Your website addressemail: Your email addresstwitter: Your twitter handlegithub: Your GitHub handlelinkedin: Your LinkedIn usernameaboutme: A short description that is included in a
template specific locationheadcolor: A featured colour for the templatedocname: Control the document name (typically
curriculum vitae, or résumé)Like other R Markdown documents, the body allows you to mix R code with markdown to create the main content for your document. Below is an example of the start for a typical CV:
`
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)
library(vitae)
```
# Professional Summary
This is a good opportunity to introduce yourself professionally and summarise
why your skills are well suited to the job you are applying for!
`{=html}
The setup chunk is useful to load in any packages that you may use, and also prevent R code and warnings/notes from appearing in your CV. The above code also includes a professional summary using markdown syntax, which will appear in the final CV.
Unlike other R markdown formats, the vitae package and its templates
support functions to generate CV entries from data:
detailed_entries() and brief_entries(). Both
functions provide sections for what, when, and
with, and the detailed_entries() additionally
supports where and why. They use an interface
similar to dplyr,
in that the data can be piped (%>%) into these
functions, and the arguments can involve some calculations.
Let’s add to the main body with some education history. I’m creating a dataset in R to do this, although you can read in the data from excel, or if you have it documented somewhere online like ORCID you can dynamically access it via their API.
```{r education} library(vitae) edu <- tribble( ~ degree, ~ start, ~ end, ~ institution, ~ location, "Bachelor of Commerce (Honours) (Econometrics)", 2013, 2017, "Monash University", "Clayton", "Bachelor of Science (Mathematical Statistics and Computational Science)", 2013, 2016, "Monash University", "Clayton", ) edu %>% detailed_entries( what = degree, when = glue::glue("{start} - {end}"), with = institution, where = location ) ```
In the example above, the glue package has been
used to combine the start and end years for our when input.
Excluding any arguments is also okay (as is done for why),
it will just be left blank in the CV.
Brief entries can be included with the same interface as
detailed_entries(), and is appropriate for entries that do
not need as much detail (such as skills). Another application of this is
to include a list of R packages that you have published to CRAN using
the pkgsearch
package.
# R Packages
```{r rpkgs}
pkgsearch::ps("O'Hara-Wild",size = 100) %>%
filter(purrr::map_lgl(package_data, ~ grepl("Mitchell O'Hara-Wild", .x$Author, fixed = TRUE))) %>%
arrange(desc(downloads_last_month)) %>%
brief_entries(
what = title,
when = lubridate::year(date),
with = description
)
```
`{=html}
This example also uses several other packages to prepare the data: -
dplyr to
filter() my contributed packages, and
arrange() the data by downloads - purrr to map over
package_data column to find packages I’ve contributed to -
lubridate to
display only the year from the date column
The package also supports bibliography entries from a
*.bib file using the bibliography_entries()
function. This outputs the contents of a bibliography using a citation
style, and is suitable for CVs containing publications.
```{r publications} bibliography_entries("publications.bib", "Publications") ```