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- #Rstudio source on save how to
- #Rstudio source on save pdf
- #Rstudio source on save portable
- #Rstudio source on save code
#Rstudio source on save pdf
View the PDF in an external viewer, view the plain text files (the script and the average of the \(x\)'s) any way you wish. Understand why certain files are or are not there. Inspect the folder associated with your project if you wish.
![rstudio source on save rstudio source on save](https://www.tcd.ie/Economics/staff/frainj/main/freeSoftware/RStudio02.png)
R, I used toyline.R and note that, by default, it will go in the directory associated with your project. Now you have a new pane containing a nascent R script. Select these commands, skipping any that didn't work or contained typos. Visit the History tab of the upper right pane. Let's say this is a good start of an analysis and you're ready to preserve the logic and code. Y <- a + b * x + rnorm( 40, sd = sqrt(sigSq)) To emulate a real analysis, let's write a numerical result to file for later use - the average of the \(x\)'s - and let's save a scatterplot to PDF - a scatterplot of \(y\) versus \(x\) with the true data-generating line superimposed. I'm going to set the intercept \(a\) and slope \(b\) of a line, generate some \(x\) values uniformly on the interval \(\), and finally generate \(y\) values as \(a + bx\) plus some noise from a Gaussian distribution. Let's enter a few commands in the Console, as if we are just beginning an analytical project. I won't print my output here because this document itself does not reside in the RStudio Project we just created and it will be confusing. Now verify that the directory associated with your project is also the working directory of our current R process: getwd() Call it whatever you want (but bear in mind that good names are short and informative). The directory name you choose here will be the project name. Do this: Projects menu -> Create project. Let's make one to use for the rest of this tutorial. Keeping all the files associated with a project organized together - input data, R scripts, analytical results, figures - is such a wise and common practice that RStudio has built-in support for this via it's projects. A way that also puts you on the path to managing your R work like an expert. Or within the Files pane, choose More and Set As Working Directory.īut there's a better way. x Set Working Directory -> To Files Pane Location. Make an assignment and then inspect the object you just created. Go into the Console, where we interact with the live R process.
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#Rstudio source on save portable
If your script starts with setwd ('c:\\Users\\Me\\This\\Folder\\Only\\I\\Have'), than it is most likely not portable.īelow are a few issues you may need to pay attention to when producing reproducible and portable R script. But if you want to share the script with others, you need to make sure that it is also portable, i.e. If you make the script just for yourself, it's fine (you are likely to open it on the same computer with the same files stored on the same file paths, so it should run just make sure that your future you will know what the script is doing). Remember that script could be fully reproducible on your computer (with your structure of file folders, your R version, and all libraries already installed), but it may not run on computers of others.
#Rstudio source on save code
Reproducible and portable is a script which also the others can open, run and get the same result as you did, with no (or minimal) need for interference with the code itself. Reproducible script is the one which you can open, run, and get the same result as you got when you created it. You can find many similar suggestions online, so take this just as my personal recommendation and google further to see more advanced suggestions.
#Rstudio source on save how to
These are simple instructions on how to prepare a reproducible R script, the one that you can share with your colleagues/friends/teachers in a way which will make it easy to co-operate.
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