I'm trying to build a webpage displaying a few graphs. I want to use R to build the graphs, and I want these graphs to automatically update themselves periodically. For example, a webpage showing a graph of the stock price of a particular company over time, which refreshes every day with new data.
what is the best way to approach this? Using Rook to run the R-scripts? can I use it along Markdown, for example, to make the html webpage? Or do you suggest something else?
You can make your plots in a R file and write your webpage in markdown in which you call your R objects and plots. Alternatively you can also run the R code directly in the markdown file. With the knit2html function of the knitr package you can create the html page with the desired output. You can find basic examples on the knitr webpage.
You can schedule these file(s) on your own computer or on a server to update the data of the html output every day. If you have a machine that runs on Windows you can use the Windows Task Manager to run the batch file.
EDIT:
Here you can find a worked out example.
Related
So I recently helped write a code for my lab which takes our processed data and makes a merged data frame of it. For purpose of keeping the lab updated, we keep our data tables updated on a secure wiki and thus I need an HTML made so I can basically upload the dataframe onto the wiki easily. It's worked before - all I did was basically copy what was already written and working and edited it to work for a different time point in our data collection. I have no errors given back to me and the data looks how I want it to look. As far as I know this script should be written logically and working well and so far it does except for one issue: R will make a file for the HTML, but there is no HTML written in the text document.
I have HTML's written from the other data time points which are written the exact same as this one, so I don't think it is a script construction thing.
Any ideas as to why this could be happening? I just need to know where to triage.
The package used for HTML is R2HTML, included in my packages list up at the top of the script. For HTML(, file=paste()), you will need to use your own directory to see if the HTML is written as a text file.
If I am not wrong , You are trying to get the dataframe in html format .
In this case you need to use xtable package in R
Just the below code in bottom of the script
## install the xtable package before importing it
library("xtable")
print(xtable(ChildSRPtotsFU_wiki), type="html", file="check_stack_overflow.html")
I am trying to automate some of my tests in R to produce a static report in Excel. I have created a template in Excel which has a few charts and tables(sheet 1).
Now I run my R code to generate the data to fill in the same excel template file on Sheet 2.
I am using Openxlsx package to loadworkbook(excel template), next I overwrite data in sheet 2 by deleting the sheet and recreating it again with the new data so that the excel template has data for new test runs.
This runs without any error. But when I open my excel back the charts disappear with the !REF# error whereas as the tables are overwritten properly in the template(sheet1).
Has anyone come across such a scenario? The method I am using is a bit weird but can't think of any other alternative.
Thanks in advance!!
This definitely sounds weird. Something seems off, but I'm sorry I can't tell you what the issue may be. Anyway, I would say, just use R to generate the data and dump everything into Excel. Then, run some VBA in Excel to create the charts. I have no idea what your VBA skills are like, but I'm guessing it would be much easier to crate charts in Excel using VBA, rather than trying to do all of this with R.
Here are a few resources that you may find useful.
https://www.thespreadsheetguru.com/blog/2015/3/1/the-vba-coding-guide-for-excel-charts-graph
https://analysistabs.com/excel-vba/chart-examples-tutorials/
http://www.sthda.com/english/wiki/r-xlsx-package-a-quick-start-guide-to-manipulate-excel-files-in-r
Finally, you can learn a lot by recording Macros and hitting F8 to step-through the code to see how everything works.
I have written my R script with some functions to do some calculations. On the output of my calculations, I have created plots in shiny(4 tab panels in that as of now, which is using the data specified in my global.R). Now I am trying to automate the process and deliver it to non technical users. So something like, users feed in 2 csv files in web UI and click a button in the web UI, which will then call my r scripts to do the calculations, then my server.R script should build plots on the output of it. Any similar examples? I tried different links, but nothing seems to be relevant.
If I add my R script using source(**.R) and use the functions mentioned in there. Or Do I still have to save output in data folder and specify something in global.R or just use the output of the function in my plot construction?
If I have the fileInput option in first tab in my tabpanels, how can I make stop the user from viewing the other tabs(tabs with graphs) without loading the input csv files and clicking the "Go" button?
Can I do this whole thing in Shiny ? Or better to go for rook or some other framework which calls my r script just for calculations?
I wonder whether I can use knitr markdown to just create a report on the fly with objects stemming from my current workspace. Reproducibility is not the issue here. I also read this very fine thread here.
But still I get an error message complaining that the particular object could not be found.
1) Suppose I open a fresh markdown document and save it.
2) write a chunk that refers to some lm object in my workspace. call summary(mylmobject)
3) knitr it.
Unfortunately the report is generated but the regression output cannot be shown because the object could not be found. Note, it works in general if i just save the object to .Rdata and then load it directly from the markdown file.
Is there a way to use objects in R markdown that are in the current workspace?
This would be really nice to show non R people some output while still working.
RStudio opens a new R session to knit() your R Markdown file, so the objects in your current working space will not be available to that session (they are two separate sessions). Two solutions:
file a feature request to RStudio, asking them to support knitting in the current R session instead of forcibly starting a new session;
knit manually by yourself: library(knitr); knit('your_file.Rmd') (or knit2html() if you want HTML output in one step, or rmarkdown::render() if you are using R Markdown v2)
Might be easier to save you data from your other session using:
save.image("C:/Users/Desktop/example_candelete.RData")
and then load it into your MD file:
load("C:/Users/Desktop/example_candelete.RData")
The Markdownreports package is exactly designed for parsing a markdown document on the fly.
As Julien Colomb commented, I've found the best thing to do in this situation is to save the large objects and then load them explicitly while I'm tailoring the markdown. This is a must if your data is coming through an ODBC and you don't want to run the entire queries repeatedly as you tinker with fonts and themes.
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.