It is easy for people to point to the par help page. But at least for R version 3.5.2 the solution is not on that page! In the barplot the x-axis is technically not an axis since it uses the names of the supplied vector. System details RStudio Edition: RStudio Version: 1.1.442 OS Version: Ubuntu 16.04 R Version: 3.4.4 (2018-03-15) Steps to reproduce the problem Select menu from Tools - Global Options - Appearance Describe the proble.

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quartzFonts {grDevices}

R Documentation

quartz Fonts

Description

These functions handle the translation of a device-independent R graphicsfont family name to a quartz font description.

Usage

Arguments

family	a character vector containing the four PostScript fontnames for plain, bold, italic, and bolditalic versions ofa font family.
..	Manycam 4.1.2 for mac. either character strings naming mappings to display,or new (named) mappings to define.

Details

A quartz device is created with a default font (seethe documentation for quartz), but it is also possibleto specify a font family when drawing to the device(for example, see the documentation for gpar in thegrid package).

The font family sent to the device is a simple string name, which must bemapped to something more specific to quartz fonts. A list ofmappings is maintained and can be modified by the user.

The quartzFonts function can be used to list existingmappings and to define new mappings. The quartzFontfunction can be used to create a new mapping.

Default mappings are provided for three device-independent font familynames: 'sans' for a sans-serif font, 'serif' for a seriffont and 'mono' for a monospaced font.

See Also

Examples

here. Obviously for many users RStudio offersa superior way to work, and as far as I know works with all of the material presentedin these tutorials and with all the packages included. (However, some of themiscellaneous scripts at the bottom of the LabDSV R page will cause RStudio tocrash.) Personally, I'm an OldSchool guy, and I'm not completely sold on RStudio. As a linux user, it solvesproblems I don't have and it encourages (if not enforces) a way of working Idon't appreciate. Nonetheless, since so many people find it useful I'llcontribute some thoughts on best practices using RStudio with LabDSV.

If you just want advice on best practices in RStudio, skip down to here and avoid my rant.

The Good

Projects

One of the excellent things RStudio does is encourage users to define 'projects'and work within the projects. This keeps all the related data and work together in asingle workspace and separates it from other projects you might be working on.Windows users, in particular, that start R by clicking on the icon ontheir desktop often end up with much (or all) of their work in a singleworkspace, commingling work from many potentially different projects. Rof course has facilities to work with separate projects natively, but usersenamored of the desktop often do not use them to full extent. So, RStudioprojects are a good idea. You will certainly want a 'project' for the labspresented in LabDSV, and you might want to separate the labs into separateprojects like 'species modeling', 'ordination', and 'clustering.'

Script Editor

RStudio encourages users to work from a script file rather than directly at theconsole. In addition, it provides a text editor for those script files that ismuch superior to generic Wordpad. (Word obviously should never be used to writeR scripts.) As a bonus, the editor can be made to mimic vi, but that's perhapsmoot to most Windows and even Mac users.

Tool Tips

When you use the console or script editor window RStudio pops up the command-line version oftool-tips, providing the list of arguments for any function you start to enter.This can be really helpful for commands you're less familiar with and makes itunnecessary to start up the help file just to get the command arguments. Bravofor this innovation.

The Bad

Panel Format

By default, RStudio starts up with a four-panel configuration packed into asingle frame. This packaging is very Windowsesque and in my mind impractical.The distribution (and number) of window types within the frame is configurable, and each ofthe windows may have tabs allowing you to select exactly what will appear in thewindow. However, even if you have a large, high resolution monitor the four panel arrangementtries to pack too much into too small a space and results in undesirablecompression of information.

Command Redirection

Even if you work in the console, RStudio traps and redirects many simple Rcommands. In particular, I dislike the way it crams R help files into a tinylittle window. Normally,?command will produce a formatted output to theconsole that is easily negotiated with the arrow keys. If you want to stretchout, help.start() pops up the help file system in your browser with fullhot-link capability. It's the same browser with the same capability you'realready familiar with, and you can shrink it or pop it behind your R session to get it out ofthe way when you don't need it. It's a vastly superior solution to the RStudiobox, but RStudio captures the help.start() command and redirects it tothe little box. Bummer.

Wasted Space

Some of the little windows are of limited utility and waste space, e.g. theEnvironment, History, Connections window. The information it providesis normally easily printed to the console (if and when you want it) except thatnow RStudio traps those function calls. For example, history(100) willcall up the last 100 commands entered at the console which you can browse andmanage with your arrow keys. You can easily cut-and-paste commands from yourhistory into the console. Instead, in RStudio it redirects the output to thelittle Environment, History, Connections box. Bummer.

The Environment, History, Connections window provides theEnvironment tab which gives a summary of objects in yourworkspace. It's more detail than the ls() command provides, but notnearly as much information as str() provides. Clicking on the bluearrow button will provide the str() output, however. Maybe it'shelpful, but ls() and str() in the console provide the sameinformation without taking up real estate on your screen unless you specificallywant to see something.

Data File Import

Importing data into R seems to be a significant problem for many users.Admittedly the plethora of optional arguments for read.table() and theprofusion of read.whatever() functions makes things a littlefunky. You might think that this is one area where a GUI could improve things.Unfortunately, this appears not to be the case.

In RStudio there are at least two ways to import data: (1) using the File menu andselecting 'Importing Dataset', or (2) clicking on a file in the File tab in the'Files, Plots, Etc' panel. Unfortunately (maybe deliberately?) they do thingsdifferently. The File menu approach first pops up a list of import formatoptions. Notably, it offers a choice between 'From text (base) ..' and 'FromText (readr) ..' This is important because base and readrdiffer significantly in the data formatting they support. If you choose 'Fromtext (base)' you get a file chooser. Selecting a file opens the import GUI withoptions to the left, a file previewer to the top right, and a data.framepreviewer to the bottom right. This part is nice. Unfortunately, it doesn'toffer a code preview of the R function that will ultimately be called to do theimport. After clicking on 'Import' you can see in the console that it usesread.table. Importantly, it offers options for choosing or settingrow.names() and a box to click for 'stringsAsFactors'. It follows theread.table() protocol that if the first row has one fewer entries thanthe rest of the lines then the first line is assumed to be a header with columnnames. It offers a fairly limited set of separators (e.g not including ), butis otherwise fairy flexible and functional.

The second option (clicking on a file name in the File panel) is quitedifferent. First, it only offers the option to import files with a limitednumber of file extensions (maybe just .csv?). Files with .dat or .txt extensionscannot be imported. Second, even if package readr is not loaded, it'sfirst choice is to load readr and then use read_csv(). Forexample, for a file called test.csv, it provides a 'Code Preview' that lookslike

There doesn't seem to be an option to choose (base) read.table(), butyou can edit the Code Preview and change whatever you like. To the lower left isa panel with options to select. This time, the Delimiter dropdown menu offers'other' and you can specify ' ' for example, which automatically changes theCode Preview to use read_delim() instead of read_csv.Unfortunately, read_delim() seems incapable of reading files where thefirst line has fewer entries than the rest of the lines. The previewer gives nowarning (although you can see the headings are misaligned if you look). Whenyou click 'Import', however, the console fills with error messagesending with

That's a fairly cryptic error message for a parsing failure, but the materialthat comes before that is somewhat more helpful. Curiously, despite the copiouserror messages it does not abort the import and happily reads the data into thewrong columns, pruning off the last column of data instead of manufacturing acolumn heading for the last column. As far as I know, this is standard behaviorfor readr functions, but it's disturbing.

Since read_delim() is a readr function, it returns a tibbleinstead of a data.frame whether that's what you want or not. I STRONGLY advise against using tibbles in LabDSV; row.names are critical and tibbles often mangle them. There is obviously more to say, but I'll leave it for the moment.

If you're really stubborn, you can edit the code in the Code Preview window to dowhat you want, but every time you touch something in the options panel RStudiowill rewrite the Code Preview window to its liking. Frankly, it's much easierto use the console.

The Ugly

Ridiculous Graphics

RStudio totally hoses the outstanding graphics capabilities of R. By default, in RStudiographics get plotted to a little window in a box that is much too small to allowfor a decent font or resolution. It's cramped and ugly. Worse yet, it decides on the X and Y limits depending on the size and shape of that little box. There is an option to'zoom' the plot, which produces another re-sizable graphics window. The windowis re-sizable, but it's not possible to specify an actual dimension or fontpoint size so that it's difficult to simulate a graphic you would include in alab report or publication. ?RStudioGD offers no help.

Much worse, from the perspective of LabDSV, while you can resize it (with'automatic' font and glyph size re-scaling) you cannot interact with the zoomedwindow; you still have to precisely identify points in the tiny window. You can(and generally have to) resize the box (at the expense of the console and scripteditor) to actually see what you're doing. Equally bad, it doesn't render thepoints as you draw (just pops up a stupid blue bubble), and you can't see whatyou have drawn until you click 'finish' or 'ESC'. It's ridiculously easy tomake mistakes, and if you do, all you can do is start over. RStudio usersshould avoid the RStudioGD graphics device like the plague.

Worse yet, in my mind, it only offers you a single window. It stores all ofyour plots and you can recall them later if you want, but you can't put twoplots up side-by-side to compare. You can do par(mfrow=(1,2)) to gettwo plots side-by-side, but now their aspect ratios are squished and ridiculousuntil you resize the box again at the expense of the console and script editor windows. It's difficult to switch back and forth btween them and interact withthem. It's lame.

I routinely have two or three graphics windows open with specified sizes, fontsizes and families. I can pop them to the front or back with the window managerand put them side-by-side or atop each other easily. It's beautiful.

The Script Editor

As I noted above, providing a built-in script editor is arguably a good idea,especially if you're stuck using Windows. If I had to use someone else's Windowscomputer that lacked a decent text editor I would undoubtedly be delighted tohave the one inside RStudio.

While in exploratory mode I generally use R directly from the console. Encouragingusers to write reproducible scripts is a good idea as their work matures.However, I insist 'It's only a script if you source it.' Instead, whatI observe is that students enter all their interactive coding into the scriptwindow, as opposed to the console, and then highlight specific lines and clickon 'Run' to get it transferred down to the console. It's not just that it'sinefficient (and it is, just type the command in the freakin console), it leadsto horrible habits. The script window code gives the impression of a specificorder of execution, but when you just highlight random lines and click on 'Run'you have no real order of operation. You could easily highlight the same linetwice and get different results because you have executed other commands in themeantime. Now arguably this is user error and not RStudio's fault, but it should be impossibleto execute specific commands without re-executing all lines in the script thatprecede that line. So, instead of a script, at best the script editor becomes acloset of R code, and at worst a junk drawer of R code. It's dangerous.

The Insufferable

Window Manager

RStudio insists on managing your Windows according to its own rules. On mycomputer, to cut-and-paste I use the first and second mouse buttons with no needto use the keyboard. In RStudio to transfer code from the console to thescript window I have to use the heinous CTRL-C/CTRL-V mantra. Worse, on my computer Iuse 'focus follows Mouse.' I.e., whatever window my mouse cursor is in gets focus andI don't have to click in the window to get the old one to let go and get the newone to pay attention. Having to click in a window before you can type in it islike having to punch somebody in the nose before you can talk to them; it'sviolent and unnecessary. And it's infuriating when you are constantly typing inthe wrong window after deliberately moving the cursor to the window you want.Students have heard many an expletive from me when I have to work on Windows,and RStudio does its damnedest to convert my linux machine to Windows.

Command Redirection

In R I can generally execute the

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system() command to get to the shellinterpreter and execute miscellaneous commands. In RStudio I can sometimes dothat, i.e. system('ls -l') works and gives a list of files from mycurrent directory in the console. On the other hand, something as simple assystem('more filename.txt') crashes RStudio and you lose all your work.It's unforgivable. There is a separate 'terminal' tab in the console windowthat allows interaction with the system, but it's another unnecessary nuisancein using RStudio.

Script Editor and fix()

In R you can enter fix(function_name)and pop up an editing session withthe editor of your choice. When you are done, you exit the editor and it savesa copy of your function into your current workspace. If you are comfortable inyour editor it's a Godsend. In RStudio, if you enterfix(function_name) it pops up a ridiculous little postage stamp of aneditor and completely ignores your choice of editor. Even though I specified viemulation in the script editor the fix() editor ignores that and givesme some primitive editing functions. To further theaggravation, the window is not re-sizable, but rather offers a horizontalscrolling bar if your text is wider than some small number of characters. Give me a break!

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Instead, you have to use the script editor (even though you're writing afunction, not a script). When you're done, however, you can't just enter theexit command and save the function to your workspace. You can write it to a filewith the 'Source on Save' box ticked, or you can highlight all the lines and click on the Run button. However, that saves the whole thing to your consoleone line at a time, scrolling off anything else you were interested in and cloggingup your .Rhistory file unnecessarily. It's lame.

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Best Practices in RStudio

If you find that RStudio provides a better way to interact with R then by allmeans make use of it. However, I strongly suggest the following:

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• Do NOT import data using the RStudio file-based data import tool. It will hose your data and make your life miserable. The drop-down menu allows .read.table()and is semi-functional but certainly no better then the console.
• Take your mouse, grab the vertical bar separating the script window andconsole from the other two windows and push the bar all the way to the right toeliminate the 'Environment, History, Connections' and 'Files, Plots, etc'windows. You can always get them back if you want, but get them out of theway.
• Click in the console window, and enter x11() to pop up a floatinggraphics window to plot to. If you're on a Mac, enter quartz().As I noted above, you can specify a specific window sizeand font point size and family if you prefer. Enter the command more than once if you want to do side-by-side comparisons or have multiple plots visible at the sametime. The windows will get numbered (starting with 2) and you can specify whichwindow is the current device with dev.set(2) for example.
• If you're not actually writing a script intended to be run from the first lineto the last, enter your commands directly in the console, not the scripteditor. Don't worry, you have permission to enter text there; it doesn't belongto RStudio exclusively. The order of operation is saved to the .Rhistoryfile so you know exactly what you have done. Later, you can easily edit the .Rhistoryfile into a script if desired.