"Behind every great love is a great story.".An epic love story centered around an older man who reads aloud to a woman with Alzheimer's. From a faded notebook, the old man's words bring to life the story about a couple who is separated by World War II, and is then passionately reunited, seven years later, after they have taken different paths.

If you want to use the notebook for code- that's great! Start typing commands. If however, you are using the notebook for writing then you need a different box- a text box. Click on the code box, and click on the 'Cell' menu at the top of the screen. From there select 'Cell type' and click 'Markdown'.

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After all things I want to record have been put into the note, I put tags to the note by the Inline tag plugin. And This allows me to use the Graph plugin to act like somewhat of notebook or contents page.

Long story short though notebooks for each (ie one personal, one profesh), notes for months, headers for days (though my personal notes are getting a bit long so I'm considering moving to notebooks for months and notes for days but I need a good way to automate that) also have some tricks to auto generate the headers and some naming tricks to make sorting flow better

Any R Markdown document can be used as a notebook, and all R Notebooks can be rendered to other R Markdown document types. A notebook can therefore be thought of as a special execution mode for R Markdown documents. The immediacy of notebook mode makes it a good choice while authoring the R Markdown document and iterating on code. When you are ready to publish the document, you can share the notebook directly, or render it to a publication format with the Knit button.

By default, RStudio enables inline output (Notebook mode) on all R Markdown documents, so you can interact with any R Markdown document as though it were a notebook. If you have a document with which you prefer to use the traditional console method of interaction, you can disable notebook mode by clicking the gear button in the editor toolbar, and choosing Chunk Output in Console (Figure 3.4).

The primary difference is that when executing chunks in an R Markdown document, all the code is sent to the console at once, but in a notebook, only one line at a time is sent. This allows execution to stop if a line raises an error.

Output: The most obvious difference is that most forms of output produced from a notebook chunk are shown in the chunk output rather than, for example, the RStudio Viewer or the Plots pane. Console output (including warnings and messages) appears both at the console and in the chunk output.

Working directory: The current working directory inside a notebook chunk is always the directory containing the notebook .Rmd file. This makes it easier to use relative paths inside notebook chunks, and also matches the behavior when knitting, making it easier to write code that works identically both interactively and in a standalone render.

If it is necessary to execute notebook chunks in a different directory, you can change the working directory for all your chunks by using the knitr root.dir option. For instance, to execute all notebook chunks in the grandparent folder of the notebook:

You can use the fig.width, fig.height, and fig.asp chunk options to manually specify the size of rendered plots in the notebook; you can also use knitr::opts_chunk$set(fig.width = ..., fig.height = ...) in the setup chunk to to set a default rendered size. Note, however, specifying a chunk size manually suppresses the generation of the display list, so plots with manually specified sizes will be resized using simple image scaling when the notebook editor is resized.

To execute an inline R expression in the notebook, put your cursor inside the chunk and press Ctrl + Enter (macOS: Cmd + Enter). As in the execution of ordinary chunks, the content of the expression will be sent to the R console for evaluation. The results will appear in a small pop-up window next to the code (Figure 3.8).

In notebooks, inline R expressions can only produce text (not figures or other kinds of output). It is also important that inline R expressions executes quickly and do not have side-effects, as they are executed whenever you save the notebook.

When you execute the empty chunk in the notebook example.Rmd, code from the external file example.R will be inserted, and the results displayed inline, as though the chunk contained that code (Figure 3.9).

In most cases, it should not be necessary to have the console open while using the notebook, as you can see all of the console output in the notebook itself. To preserve vertical space, the console will be automatically collapsed when you open a notebook or run a chunk in the notebook.

If you prefer not to have the console hidden when chunks are executed, uncheck the option from the menu Tools -> Global Options -> R Markdown -> Hide console automatically when executing notebook chunks.

When a notebook *.Rmd file is saved, a *.nb.html file is created alongside it. This file is a self-contained HTML file which contains both a rendered copy of the notebook with all current chunk outputs (suitable for display on a website) and a copy of the *.Rmd file itself.

Note that the *.nb.html file is only created for R Markdown documents that are notebooks (i.e., at least one of their output formats is html_notebook). It is possible to have an R Markdown document that includes inline chunk output beneath code chunks, but does not produce an *.nb.html file, when html_notebook is not specified as an output format for the R Markdown document.

One of the major advantages of R Notebooks compared to other notebook systems is that they are plain-text files and therefore work well with version control. We recommend checking in both the *.Rmd and *.nb.html files into version control, so that both your source code and output are available to collaborators. However, you can choose to include only the *.Rmd file (with a .gitignore that excludes *.nb.html) if you want each collaborator to work with their own private copies of the output.

While RStudio provides a set of integrated tools for authoring R Notebooks, the notebook file format itself is decoupled from RStudio. The rmarkdown package provides several functions that can be used to read and write R Notebooks outside of RStudio.

In this section, we describe the internals of the notebook format. It is primarily intended for front-end applications using or embedding R, or other users who are interested in reading and writing documents using the R Notebook format. We recommend that beginners skip this section when reading this book or using notebooks for the first time.

In general, you can provide regular R output in your output source function, but rmarkdown also provides a number of endpoints for insertion of custom HTML content. These are documented within ?html_notebook_output.

The tool can be used with voice notebook transcription module for creating video clips in foreign languages. For example, I can make a video clip in Russian, then transcribe it, and translate the subtitles to English. Then I can play the English subtitles in SRTspeaker, and record audio with the help of the virtual audio cable and any sound recorder. After that, I can change the audio track of my video to the new audio with the help of the video editor.

With TVs, the content comes from the TV station either directly, or through some cable or satellite service -- and that content contains "subtitles" that are displayed when you enable Close Captioning on yourTV.

In general, to see if Subtitles are available, you have to check the options in your specific Media Player while watching the movie. IF the movie contains subtitles, then there will be an Options setting that will allow you to select that. If the content does not include subtitles, there will be no option to turn them on.

No end of artists have recorded this song! I found a YouTube video with the lyrics in Pinyin (the singer is Timi Zhou), which makes it easier to keep my place in the music while learning the form. I also found a video with English subtitles:

It's a strange sort of intimacy that develops between a film and its translator. Entering into such close proximity to a work during the frenzied weeks in which the subtitles are made gives the translator a somewhat slanted perspective. In some ways, your ability to step back and objectively assess a film can be affected. Being so close to the work creates certain blind spots. On the other hand, translators must be so sensitive to the nuances of language, performance, and characterization that one starts to feel especially close to the characters and the ways in which they express themselves. It does seem that translators experience a film with different eyes and ears.

You learn, for example, how to work with the Accessibility Checker to tackle accessibility issues while writing your notebook. You'll also learn how to add alt texts to images so that people using screen readers are able to listen to what the image is all about. You can also read about how to use font colors and styles to maximize the inclusiveness of your notebook before sharing it with others.

Use the built-in heading styles to form an outline of the notebook pages for screen readers. Screen readers enable people to navigate by heading, but they cannot interpret a line of text with large and bold font as a heading unless the built-in styles are applied.

All tables created in OneNote automatically have a header row. It is possible to remove or add the header row using the OneNote for Windows app. If your notebook has a table with the Header Row option unselected, you can use the Windows app to resolve this issue.

Where possible, ensure that audio and video files are accessible before being inserted into OneNote. Alternatively, insert an additional file into the notebook to provide supporting subtitles, captions, or video description. 0852c4b9a8

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