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I know that using knitr one can generate reports, etc but is it possible to write a complete paper in R? That is, including all diagrams, citation of referred works, heading styles, etc like you do in Microsoft Word. I am asking about non R research i.e. analyses done in R (for example Road Traffic Engineering analyses) but not related to R or programming.
I think citations and header styles seem like a problem.
You might want to have a look at brew package, which in my opinion is better for mixing output with R (presentation). I think there are mostly tools to render R objects into specific formatting like (Pander, xtable, stargazer, etc).
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I am trying to extract the data in the tables that start on p.52 of this document (a report from FAA).
The problem is that the tables are included as pictures. Any chance I can get some pointers on how to do that without doing it manually?
I have tried converting it to text using Adobe's OCR function, and I have also tried using the extract_tables function in R's tabulized package.
I could of course do this manually, but it would be good to know if there is a more efficient way of doing it.
It's possible, however its accuracy depends on the image. I always use grayscale images. Here an example of available tools. In your case, I'd suggest you take some screenshots of the tables and use the OCRFeeder to compare the results from GOCR and Tesseract.
sudo apt-get install gocr tesseract-ocr ocrfeeder
ocrfeeder -i image.jpg
After some manual checks, you can import this file in LibreOffice Calc, save it as 'csv', and import in R.
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I am new to R and am learning about the dplyr package. In the documentation for %>% I can read about how the packages changes the grammar or the language. For example,
The magrittr pipe operators use non-standard evaluation.
I would like to learn more about how this is done, but am unsure of what keywords to use. Can someone point me to a documentation page on what features R exposes that allows one to write code that modifies the order of evaluation?
From the R console enter:
?Syntax
Also see the infix and prefix section of the R Language Definition manual.
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I have 22 companies response about 22 questions/parameters in a 22x22 matrix. I applied clustering technique which gives me different groups with similarities.
Now I would like to find correlations between parameters and companies preferences. Which technique is more suitable in R?
Normally we build Bayesian network to find a graphical relationship between different parameters from data. As this data is very limited, how i can build Bayesian Network for it?
Any suggestion to analyze this data.
Try looking at Feature selection and Feature Importance in R, it's simple,
this could lead you: http://machinelearningmastery.com/feature-selection-with-the-caret-r-package/
Some packages are good: https://cran.r-project.org/web/packages/FSelector/FSelector.pdf
, https://cran.r-project.org/web/packages/varSelRF/varSelRF.pdf
this is good SE question with good answers: https://stats.stackexchange.com/questions/56092/feature-selection-packages-in-r-which-do-both-regression-and-classification
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I inherited legacy code from 2009 that includes the many of the following types of expressions -
variable %in% cs(do, ph, t, secchi)
I get the following error - Error: could not find function "cs" when I try to run anything like this, have not seen 'cs' before, and can't locate any info in help files, google, or on this site so far. I'm guessing it is a deprecated way of concatenating strings but would like to confirm before I update the legacy code.
There is a Cs function in Hmisc package. I think it is that.
See this
library(Hmisc)
Cs(a,cat,dog)
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In the R official docs, the term ''variable'' is used to describe two distinct things:
The name we give to any type of object with the <-operator or with assign
For instance, we could say that in a <- data.frame(0), a is a variable, i.e. a symbol that links that particular dataframe to it.
A vector or a factor, belonging or not to a structure like a matrix or a dataframe, and containing units of data which, we assume, can take any of several or many values.
In this case it's akin to the statistical version of the term, such as in ''random variable''.
So my question is the following:
How do I help students understand the difference between programmatic and statistical usage of the term variable when teaching R?
(thanks and credits to #Gregor who formulated it in a better way than I would.)