What is the difference between using R console vs writing R code in a text file? I wrote this question on Kaggle but there were no previous questions on this matter.
When you supply code via text file (.R file) you "run the file with R" without visualizing it and it can stop somewhere due to error i.e. (which can be handled, etc.). Also running an .R file with R (for example via .bat file) generates a .Rout file, which is basically a print out of the console and some aditional info like runtime, etc.
If you feed the code in the console, each line is treated independently: even if there is an error you can process an aditional line (if it depends on the failed comand then it will fail also though) and you get to see each result as soon as the comand is run. In comparision to the .R file you will have no copy of the code other than that stored in the session - meaning you will end up needing to save to disk the code you have written if you want it to persist between session. Now you can choose to use whatever text format you like for this task from simple .txt to .docx BUT if you use .R format you can manipulate with notepad++ or the notepad editor and still run/complipe the file with R (via .bat file for example). In case of opting against .R file to store the written code, you will have to feed it to the console again to run.
In R Studio you can open .R files and manage (extend, correct) your code and feed it comand per comand or as a block to the console. So one could say you use .R files to manage you code, having the possiblity to compile/run these .R files directly with R to execute on a button click or repeatedly for example.
Not sure if that is what you are looking for?
Related
Whenever I knit to a PDF in RStudio, the error "The system cannot find the file specified."
Here is the code that I'm using:
##importing data
library(readr)
Quiz1data_2 <- read_csv("C:/Users/erinp/Downloads/Quiz1data-2.csv")
I have restarted RStudio multiple times and I have copied and pasted the exact link that my file is saved to and it's still not working.
What am I not seeing or what am I not thinking?
Some suggestions/questions:
Without knitting, when you run the line reading in the csv, does it work?
Also, are you sure that the error is referring to the data csv? Could it be referring to the (I'm assuming) markdown file you are writing your code in? Have you moved that file since you started working in it?
Are you able to knit other documents to pdf? You need MiKTeX on a windows machine. Does knitting to html work?
I've found R to be a little tricky reading in files. I usually use the base function like this:go to the environment tab>import dataset>from text(base)> (select the file you want, hit open)>(select settings so that the dataframe preview looks right>import. Code that does this will run in the console, and I copy it into my markdown file so that every time it knits, it replicates that successful process.
I figured it out. It's because I forgot to assign a value to an object so it wouldn't knit into a PDF. I made a comment earlier, but it's small so I thought I would add this to the answer section.
I want to save my code in R. I did:
save(Data,file="Code_Data.R")
When I open the file in R again, the code looks like hieroglyphics.
How can I save the code in a way, that I can read the code in an editor or RStudio again?
save outputs a binary copy of the objects you tell it to save, not R code. Because you are naming this file with a ".R" extension, RStudio is blindly trying to open this binary file as R code, and you are seeing the results of that mess.
Technically, the R language doesn't care what the extension of the file is. As long as you know that the file contains, you can load it back in with the command load("Code_Data.R"). However, if you want to get RStudio to recognize that this is actually a file containing binary data and not R code, try saving the file with the canonical ".RData" extension:
save(Data, file="Code_Data.RData")
Using the ".RData" extension will also help you and other programmers who look at your code avoid this confusion in the future.
I'm writing an R script whose contents can change from time to time. It would be really helpful if I could insert a command that would copy the current contents of the script to a file, so I can go back later and see exactly what commands I executed during that run of the code.
How can I do this?
You can do this with the teaching demos package:
install.packages("TeachingDemos")
library(TeachingDemos)
#Will write to a file in the working directory
txtStart("captureCode.txt")
#This comment will not appear in the file, all commands and output will
Sys.Date()
#This command ends writing to the file
txtStop()
Source
I have an R data frame that I run through knitr using the following code:
knit('reportTemplate.Rnw', 'file.tex') # creates a .tex file from the .Rnw one
texi2pdf('file.tex') # creates a .pdf file from the .tex one
Inside my R script, I want to remove 'file.tex' from my computer folder afterwards. How do I achieve this? It is important that I do this within my .R file, since those lines are actually inside a loop that generates 1000 different reports from that template.
There are a family of functions in R that allow the user to interact with the computer's file system. Run ?files to see functions that make it possible to, for instance, create, rename and remove files.
As noted by Josh O'Brien, in a comment to the OP, in this specific case, the command to be used is file.remove('file.tex').
my question(s) might be less general than the title suggests. I am running R on Mac OS X with a MySQL database to store the data. I have been working with the Komodo / Sciviews-R for some time. Recently I had the need for auto-generated reports and looked into Sweave. I guess StatET / Eclipse appears to be the "standard" solution for Sweavers.
1) Is it reasonable to switch from Komodo to StatET Eclipse? I tried StatET before but chose Komodo over StatET because I liked the calltip / autosuggest and the more convenient config from Komodo so much.
2) What´s a reasonable workflow to generate Sweave files? Usually I develop my R code first and then care about the report later. I just learned today that there is one file in Sweave that contains R code and Latex code at once and that from this file the .tex document is created. While the example files look handily and can't really imagine how to enter my 250 + lines of R code to a file and mixed it up with Latex.
Is it possible to just enter the qplot() and ggplot() statements to a such a document and source the functionality like database connection and intermediate results somehow?
Or is it just a matter of being used to the mix of Latex and R code?
Thx for any suggestions, hints, links and back-to-the-roots-shout-outs…
You've asked several questions, so here's several answers;
Is StatEt/Eclipse the right way to do Sweave ?
Not nessarily (note: I'm an avid StatEt/Eclipse user, and use it for both pure R and Sweave/R and love it, I haven't used Komodo / sciviews-R). You should be able to run the sweave command from any R command line which will generate a .tex file. You can then turn the .tex file into something readable (like pdf) from any tex environment.
What's a good Sweave workflow ?
When I have wanted to turn an r script into a sweave report I generaly start with an empty sweave template and copy/paste my entire R script into a sweave R block just after the title, i.e;
<<label=myEntireRScript, echo=false, include=false>>
#Insert code here
myTable<-dataframe(...)
myPlot<-qplot(....)
#
Then I go through and find the parts I want to report. For instance, if i want to put a table into the report, I'll cut the R block and put an xtable block in, and the same for variables and plots.
<<label=myEntireRScript, echo=false, include=false>>=
#Insert code here
#
Put any text I want before my table here, maybe with a \Sexpr{print(variable)} named variable
<<label=myTable, result=Tex>>=
myTable<-dataframe(...)
print(xtable(mytable,...),...)
#
Any text I want before my figure
<label=myplot, result=figure>>=
myPlot<-qplot(....)
print(qplot)
#
You may want to look at these related SO posts. The rest of my post relates to your question 2.
When creating reports with Sweave, I usually keep most of the R code and the report text separate. If the R code is fast to run, then I prefer I will include something like the following at the start of the .Rnw file:
<<>>
source('/path/to/script.r')
#
On the other hand, if the R code takes a long time, I will often include something like the following at the end of the R script:
Sweave('/path/to/report.Rnw'); system('pdflatex report.tex')
That way, I can re-generate the report quickly, without needing to run all the R code again. Then, the only work R has to do in the Sweave file is print tables, make graphs and maybe extract a few figures.
Like nullglob, I prefer to keep the R and Sweave files separate, but I prefer to save the workspace with save.image() rather than to source() the file. This avoids running the R calculations with each .Rnw file compiling (and I always end up tinkering with the typesetting more than I'd like).
My general work flow is to do each paper/project in it's own folder with it's own R file(s). When the calculation side is "done", I save.image() to store all the workspace variables as-is.
Then, in the .Rnw file in the same directory I set the working directory with setwd() and load all variables with load(".Rdata"). Of course, you can change the name you use for your workspace, but I do one workspace per folder and keep the default name. Oh, and if you tinker with the R file, be sure save the workspace image and watch out for variables that linger in the workspace and .Rnw file, but are no longer part of the R file... this is where the save.image() approach can cause some headaches.
I am on a Mac and I suggest TextMate if you're mildly geeky and emacs/ess if you're really geeky. I use vim and command line R, but emacs/ess works best for most. If you're in this for the long haul, I doubt you'll regret learning emacs/ess for R, Sweave, and LaTeX.