One of the parameters specified by the user via YAML is the framework, which is a “structure layer” that dictates display (specifically, it guides the interpretation of R Markdown into HTML).
YAML can be considered an “intermediary layer” between the content and the display. The YAML is written at the front (top) of the document in a special metadata section, and it is also sprinkled between slides. There are a couple of parameters that the user specifies to control the overall look of the presentation, and the look of each slide these parameters are specified using YAML (YAML Aint Markup Language yes, the Y in YAML stands for YAML), which is a human-readable way to pass data from a human to a computer. For example, the “content layer” is specified in R Markdown, which is then automatically converted to HTML, which can be considered the “display layer”. Onions have layers, ogres have layers, and now slideshows in R have layers. In this way, slideshows in R are like Ogres they have layers. There’s a lot more to a slideshow than people think.
RMARKDOWN PRESENTATION HOW TO
Take note that much of what will occur in this chapter focuses on how to make a slideshow from R Markdown, and the implication is that you will use this process to insert plots, figures, and tables into a slideshow as well as occasionally using R Markdown to make references to values as inline code.Ī slide show created with R Markdown results from the integration of multiple programming and markup languages, and the introduction of several new terms can be confusing at first. You probably won’t actually do your data analysis inside a presentation Rmd file, but once you are comfortable with the process you will be able to convert csv files to charts and tables much faster and more flexibly than with a Powerpoint presentation.
10.3.5 Paragraph 3: Hunter Demographics.10.3 Tauntaun Annual Report Outline and R Objects Needed (Section 2).10.1 HTML Markup vs. Markdown vs. R Markdown.7.8 Summarizing the Harvest with Aggregate.6.10 Read in the Hunter CSV file, and Save as hunter_clean.RData.6.9 Save the Cleaned Data as harvest_clean.RData.6.8 Stepping through Rows and Columns with Apply Functions.6.7.1 color = fur color of the reptomammalian Tauntaun.6.7 A Brief Interruption to Discuss NA and NULL.6.6.9 weight = weight of harvested animal (arbitrary units).6.6.8 length = length of harvested animal.6.6.7 town = town in which the animal was harvested.6.6.4 individual = the unique identifier of each harvested animal.6.6.3 sex = the sex of the harvested animal.6.6.2 age = the age of the harvested animal.6.6.1 hunter.id = the unique hunter identification number.3.4.7 Function Names from Different Packages.2.3 The Files, Plots, Package, Help Pane.
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