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Fix typos (#444)

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behrman 2016-10-03 06:23:00 -07:00 committed by Hadley Wickham
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rmarkdown-formats.Rmd
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@ -28,7 +28,7 @@ knitr::include_graphics("screenshots/rmarkdown-knit.png")
## Output options
Each output format is an R function. You can either write `foo` or `pkg::foo`. If you omit, `pkg` the default is assumed to be rmarkdown. It's important to know the name of the function that makes the output because that's where you get help. For example, to figure out what parameters you can set with `html_document`, look at `?rmarkdown:html_document()`
Each output format is associated with an R function. You can either write `foo` or `pkg::foo`. If you omit, `pkg` the default is assumed to be rmarkdown. It's important to know the name of the function that makes the output because that's where you get help. For example, to figure out what parameters you can set with `html_document`, look at `?rmarkdown:html_document()`
To override the default parameter values, you need to use an expanded `output` field. For example, if you wanted to render an `html_document` with a floating table of contents, you'd use:
@ -88,7 +88,7 @@ output:
## Notebooks
A notebooks, `html_notebook`, is a variation on a `html_document`. The rendered outputs are very similar, but the purpose is different. A document is focussed on communicating with decisions makers, while a notebook is focussed on collaborating with other data scientists. These different purposes lead to using the HTML output in different ways. Both HTML outputs will contain the fully rendered output, but the notebook also contains the full source code. That means you can use the `.nb.html` generated by the notebook in two ways:
A notebook, `html_notebook`, is a variation on a `html_document`. The rendered outputs are very similar, but the purpose is different. A `html_document` is focussed on communicating with decisions makers, while a notebook is focussed on collaborating with other data scientists. These different purposes lead to using the HTML output in different ways. Both HTML outputs will contain the fully rendered output, but the notebook also contains the full source code. That means you can use the `.nb.html` generated by the notebook in two ways:
1. You can view it in a web browser, and see the rendered output. Unlike
`html_document`, this rendering always includes an embedded copy of
@ -96,10 +96,10 @@ A notebooks, `html_notebook`, is a variation on a `html_document`. The rendered
1. You can edit it in RStudio. When you open an `.nb.html` file, RStudio will
automatically recreate `.Rmd` file that generated it. In the future, you
will also be able include supporting files (e.g. `.csv` data files), that
will also be able include supporting files (e.g. `.csv` data files), which
will be automatically extracted when needed.
Emailing `.nb.html` files is a simple way to share analyses with your colleagues. But things will get painful as soon as they want to make changes. If this starts to happen, it's a good time to learn Git and Github. Learning Git and GitHub is definitely painful at first, but the collaboration payoff is huge. As mentioned earlier, Git and GitHub are outside the scope of the book, but there's one tip that's useful if you're already using them: use both `html_notebook` and `github_document` outputs:
Emailing `.nb.html` files is a simple way to share analyses with your colleagues. But things will get painful as soon as they want to make changes. If this starts to happen, it's a good time to learn Git and GitHub. Learning Git and GitHub is definitely painful at first, but the collaboration payoff is huge. As mentioned earlier, Git and GitHub are outside the scope of the book, but there's one tip that's useful if you're already using them: use both `html_notebook` and `github_document` outputs:
```yaml
output:
@ -111,7 +111,7 @@ output:
## Presentations
You can also use R Markdown to produce presentations. You get less visual control that with a tool like Keynote or Powerpoint, but automatically inserting the results of your R code into a presentation can save a huge amount of time. Presentations work by dividing your content into slides, with a new slide beginning at each first (`#`) or second (`##`) level header. You can also insert a horizontal rule (`***`) to create a new slide without a header.
You can also use R Markdown to produce presentations. You get less visual control than with a tool like Keynote or PowerPoint, but automatically inserting the results of your R code into a presentation can save a huge amount of time. Presentations work by dividing your content into slides, with a new slide beginning at each first (`#`) or second (`##`) level header. You can also insert a horizontal rule (`***`) to create a new slide without a header.
R Markdown comes with three presentations formats built-in:
@ -158,17 +158,17 @@ Any HTML format (document, notebook, presentation, or dashboard) can contain int
### htmlwidgets
HTML is an interactive format, and you can take advantage of that interactivity with __htmlwidgets__, R functions that produce interactive html visualisations. For example, take the __leaflet__ map below. If you're viewing this page on the web, you can drag the map around, zoom in and out, etc. You obviously can't do that on a book, so rmarkdown automatically inserts a static screenshot for you.
HTML is an interactive format, and you can take advantage of that interactivity with __htmlwidgets__, R functions that produce interactive HTML visualisations. For example, take the __leaflet__ map below. If you're viewing this page on the web, you can drag the map around, zoom in and out, etc. You obviously can't do that on a book, so rmarkdown automatically inserts a static screenshot for you.
```{r}
library(leaflet)
leaflet() %>%
setView(174.764, 36.877, zoom = 16) %>%
setView(174.764, -36.877, zoom = 16) %>%
addTiles() %>%
addMarkers(174.764, 36.877, popup = "Maunga Whau")
addMarkers(174.764, -36.877, popup = "Maungawhau")
```
The great thing about htmlwidgets is that you don't need to know anything about HTML or javascript to use them. All the details are wrapped inside the package so you don't need to worry about it.
The great thing about htmlwidgets is that you don't need to know anything about HTML or JavaScript to use them. All the details are wrapped inside the package, so you don't need to worry about it.
There are many packages that provide htmlwidgets, including:
@ -180,13 +180,13 @@ There are many packages that provide htmlwidgets, including:
* __threejs__, <https://github.com/bwlewis/rthreejs> for interactive 3d plots.
* __DiagrammeR__, <http://rich-iannone.github.io/DiagrammeR/> for diagrams
(like flow charts and simple node-link digrams).
(like flow charts and simple node-link diagrams).
To learn more about htmlwidgets and see a more complete list of packages that provide them visit <http://www.htmlwidgets.org/>.
### Shiny
htmlwidgets provide __client-side__ interactivity --- all the interactive happens in the browser, independently of R. On one hand, that's great because you can distribute the HTML file without any connection to R. However, that fundamentally limits what you can do to things that have been implemented in HTML and javascript. An alternative approach is to use __shiny__, a package that allows you to create interactivity using R code, not javascript.
htmlwidgets provide __client-side__ interactivity --- all the interactive happens in the browser, independently of R. On one hand, that's great because you can distribute the HTML file without any connection to R. However, that fundamentally limits what you can do to things that have been implemented in HTML and JavaScript. An alternative approach is to use __shiny__, a package that allows you to create interactivity using R code, not JavaScript.
To call Shiny code from an R Markdown document, add `runtime: shiny` to the header:
@ -209,7 +209,7 @@ knitr::include_graphics("screenshots/rmarkdown-shiny.png")
```
You can then refer to the values with `input$name` and `input$age`, and the code that uses them will be automatically re-run whenever they change.
I can't show you a live shiny app here because shiny interactions occur on the __server-side__. This means you can write interactive apps without knowing javascript, but it means that you need a server to run it on. This introduces a logistical issue: Shiny apps need a Shiny server to be run online. When you run shiny apps on your own computer, shiny automatically sets up a shiny server for you, but you need a public facing shiny server if you want to publish this sort of interactivity online. That's the fundamental trade-off of shiny: you can do anything in a shiny document that you can do in R, but it that requires someone to be running R.
I can't show you a live shiny app here because shiny interactions occur on the __server-side__. This means you can write interactive apps without knowing JavaScript, but it means that you need a server to run it on. This introduces a logistical issue: Shiny apps need a Shiny server to be run online. When you run shiny apps on your own computer, shiny automatically sets up a shiny server for you, but you need a public facing shiny server if you want to publish this sort of interactivity online. That's the fundamental trade-off of shiny: you can do anything in a shiny document that you can do in R, but it that requires someone to be running R.
Learn more about Shiny at <http://shiny.rstudio.com/>.
@ -258,7 +258,7 @@ To learn more about effective communication in these different formats I recomme
* To improve your presentation skills, I recommend
[_Presentation Patterns_](https://amzn.com/0321820800), by Neal Ford,
Matthew McCollough, and Nathaniel Schutta. It provides a set of effective
patterns (both low- and high-level) that you can imply to improve your
patterns (both low- and high-level) that you can apply to improve your
presentations.
* If you give academic talks, I recommend reading the [_Leek group guide