Is there any way in R to write a macro like one would in SAS? That is, I want to write a macro with some input variable (corresponding to a row in a dataset) so I can quickly make a plot of certain characteristics from said row. Any information regarding a package/method to do so would be greatly appreciated.
R will generate some very, very, very basic code for you. If you have RStudio installed, you can click File > Import Dataset > From ... point to your file and click 'Open'. R will automatically create the code to do the import. Again, this is very basic. You really need to know how to code to do anything useful.
You get out of it what you put into it, so spend some time learning this stuff, and inevitably you'll learn a ton. I've found that it's very helpful to read through people's questions that are posted here, and try to solve the problem yourself. You'll learn a lot that way and you'll see what the current trends are. Reading books is great, of course, but sometimes I feel like some authors are too academic, and in the real world, sometimes it's done differently than what you see in textbooks.
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i imported exel to R now i do not know how to solve the question, as it is my 1st time with R
As this looks like an assignment/homework question, and you mention this is your 1st time with R, I think you would benefit more from looking at an in-depth introduction to R than a quick answer here. This site seems to be a good introduction: https://intro2r.com/index.html . The site recommend RStudio which is far more intuitive and easy to use than base R.
There is also often good documentation on basic functions within R itself. Type ? into the console before any command and it will direct you to some helpful information. For example, you may find these useful to get started.
?hist
?plot
?min
?max
I have a large population survey dataset for a project and the first step is to make exclusions and have a final dataset for analyses. To organize my work, I must continue my work in a new file where I derive survey variables correctly. Is there a command used to continue work by saving all the previous data and code to the new file?
I don´t think I understand the problem you have. You can always create multiple .R files and split the code among them as you wish, and you can also arrange those files as you see fit in the file system (group them in the same folder with informative names and comments, etc...).
As for the data side of the problem, you can load your data into R, make any changes / filters needed, and then save it to another file with one of the billions of functions to write stuff to the disk: write.table() from base, fwrite() from data.table (which can be MUCH faster), etc...
I feel that my answer is way too obvious. When you say "project" you mean "something I have to get done" or the actual projects that you can create in rstudio. If it´s the first, then I think I have covered it. If it´s the second, I never got to use that feature so I am not going to be able to help :(
Maybe you can elaborate a bit more.
I have been searching for a solution/library or any function that performs text categorization of a single paragraph without any training involved in R. I need to categorize/classify contact center call data individually. The calls need to be categorized according to the terms used by the agent or caller. The terms may not be consecutive, and so it doesn't follow bigram.
For example, the following sample text should be categorized something like "Router Internet issues"
"Hello thank you for calling XYZ solutions. This is Mark. How can I help you?
Hi, I have been facing issues in connecting to internet. There seems to be some issue with my router. "
I have tried OpenNLP, RTextTools libraries in R, but could not figure out how to process a single paragraph. Does anyone have any ideas? Any help is appreciated.
Edited
As I am a beginner in R so would much appreciate a thorough solution if possible
It looks like you are trying to extract keywords from a document and using those as tags/labels. You may want to look at this R package {RKEA} - http://www.nzdl.org/Kea/Download/Kea-5.0-Readme.txt
I've started teaching myself sage and I'm a bit confused about the naming of some commands in graphics. The most basic command for graphics is perhaps plot with its variants polar_plot, contour_plot, etc. However, I've also seen some variants of plot that are obtained from it by adding postfixes to it, for instance, plot_vector_field.
Does anyone know the reason why some graphical commands belong to the first category (prefix_plot) and some to the second (plot_postfix)? I'm asking this because of there is a good reason for this, then it can help me remember the names more easily, and if there is no special reason this might be something to suggest for changes in future releases of sage as it is open source.
PS This is my first question on stackoverflow and I hope this is the right place for asking it, otherwise please feel free to move it anywhere that you feel it might belong.
This question already has an answer here:
Automatic documentation of datasets
(1 answer)
Closed 8 years ago.
Is there any code self-documenting system for R?
I think writing documentation is a very important part of any statistical analysis. There are always important details in your code or the steps of data cleaning that are not reflected in the final analysis report. I wonder whether there is any efficient self-documenting system (or approach) in R that can help me documenting my codes including my comments o my codes with structure files explaining the structure of the datasets (or tables) used in my code?
Beyond using Sweave or knitr in R, is there any other way of doing that?
I'd suggest bundling up your code and data sets in an R package. There's a steep learning curve the first time you do it, but if you're at the point where you're asking, "how can I better manage this code documentation thing", you're likely ready to take the plunge.
Plus, doesn't the idea of typing ?myOwnFunction or ?myOwnDataset, and having the appropriate help file pop up (just as it does when you do ?mean or ?iris) sound appealing?
You might try writing your code as a Sweave or kntr file, which contains LaTeX text along with R code. This process produces a pdf of your text, including your code, and executes your code.
If you choose to organise your analysis as package, you can use roxygen2 for documentation of your code and data.