similar to: SQL and R

Just a slight technical note -- Ben gave you a good answer already, imo. The note is: R is Turing complete, which mean that *anything* any language can do, R could be programmed to do also. The point is what can be done well in R and what can be done (often much) better with other tools, as Ben explained. Cheers, Bert On Wed, Dec 11, 2024 at 5:17?AM akshay kulkarni <akshay_e4 at

Dear Askay, I believe my grey hair allows me to help answer your question. SQL, and its progenitor SEQUEL, were developed specifically to manipulate relational databases. It was developed in the early 1970s (equivalent to the historical bronze age) when the concept of a relational database (see https://en.wikipedia.org/wiki/Relational_database) and Codd's 12-rules were being developed (see

The advantages of SQL are that - it can be used from many languages so if you know SQL you can easily move that part of your code to python, say, and visa versa - it is widely used - it can handle data stored outside of R and possibly otherwise too large for R - some SQL databases support multiple concurrent users - depending on the database it may be used to communicate the data to others - one

And to answer the dependency question. Neither is dependent on the other. But both can be complimentary. If you consider that SQL*may* be a route to accessing your data (if it's in a database). And R *may* be a route to analysis of the data. If the data is in a CSV file, Excel file, API etc. you don't need SQL. IF it is in a database, you might extract it to CSV etc. or you might

My late friend Morven Gentleman, not long after he stepped down from being chair of Computer Science at Waterloo, said that it seemed computer scientists had to create a new computer language for every new problem they encountered. If we could use least squares to measure this approximation, we'd likely be suspicious of a terribly small error measure or overly high R^2. JN On 2024-12-11

Akshay, Your question has way too many answers. SQL has a long history and early versions came long before R arrived on the scene. There is a huge embedded base of hardware and software dedicated to managing databases. It has some features that most R programs do not even dream of doing. Besides easily handling massive amounts of data or sometimes tweaking queries to possibly run more

dear members, I am a stock trader. I am using R for my research. I want to service my laptop, wherein resides all my R code, which, for obvious reasons, has to be secured. I am using Windows 7 Ultimate. I cannot encrypt the R data by Bitdefender, as it encrypts the entire drive. I anyway need to give the key when the system, if at all, gets locked when servicing. My

Dear R Staff You can see my data.csv file in the annex. I try to count non-zero values in dataset but I need to exclude NA in this calculation My code is very long (following), How can I write this code more efficiently and shortly? ## [NA_Count] - Find NA values data.na =sapply(data[,3:ncol(data)], function(c) sum(length(which(is.na (c))))) ## [Zero] - Find zero values

Good morning. I've ran a test against MP3 format. Code: (first convert tested audio file to 16 bit 48khz with sox.exe if needed) lame.exe -b 320 48khzfilein.wav -o fileout.mp3 lame --decode fileout.mp3 -o fileout.mp3.wav opusenc.exe --bitrate 320 48khzfilein.wav fileout.opus opusdec.exe fileout.opus fileout.opus.wav wavdiff.exe 48khzfilein.wav fileout.mp3.wav -diff fileout.mp3.delta.wav

Oops, wrong language ;D Okay Rowland. Thank you very much for this help. To the next. <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> Livre de v?rus. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>.

This is what I was looking for. Thank you everyone! Sincerely, Milu <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> Mail priva di virus. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>

On 22/06/2020 14:00, Fernando Gon?alves wrote: > Good morning Rowland. > > As you may have noticed, I am no expert in deploying SAMBA in an AD > domain. > Could you give me a link with a tutorial that explains in a simple way > the procedure for this? You could start here: https://wiki.samba.org/index.php/Setting_up_Samba_as_a_Domain_Member > > Just to not leave

Ista, et. al: efficiency? (Note: I needed to correct my previous post: do.call() is required for pmax() over the data frame) > x <- data.frame(matrix(runif(12e6), ncol=12)) > system.time(r1 <- do.call(pmax,x)) user system elapsed 0.049 0.000 0.049 > identical(r1,r2) [1] FALSE > system.time(r2 <- apply(x,1,max)) user system elapsed 2.162 0.045 2.207 ##

Hi Guys I am wanting to test running tinc in openwrt. I need help on how to run it in openwrt. How do I compile tinc ? Regards Yazeed Fataar <yazeedfataar at hotmail.com> <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> This email has been sent from a virus-free computer protected by Avast. www.avast.com

What was suggested by Eric and Rui works well, but here is a short and may be simpler answer provided your data is similar what Eric posted. It should work for your l data too. aa <- is.na(data)|data==0 nrow(data)-colSums(aa) EK On Sun, Oct 29, 2017 at 6:25 AM, Engin YILMAZ <ispanyolcom at gmail.com> wrote: > Dear R Staff > > You can see my data.csv file in the annex. >

Since i could not see your data, the easiest thing comes to mind is court values excluding NAs, is something like this sum(!is.na(x)) Best of luck--EK On Sun, Oct 29, 2017 at 6:25 AM, Engin YILMAZ <ispanyolcom at gmail.com> wrote: > Dear R Staff > > You can see my data.csv file in the annex. > > I try to count non-zero values in dataset but I need to exclude NA in this >

Hola buenos días hice un gráfico combinado de líneas, puntos y barras en ggplot2, pero no sé cómo puedo poner la leyenda de eso gráfico para que me represente para las líneas con puntos los valores estimados por un modelo y observados. este es mi código: ggplot(MLM,aes(x=Individuo)) + geom_bar(aes(y=Observada), stat = "identity", color= "gray") + geom_line(aes(y=Estimada),

Dear R Staff This is my file (www.fiscalforecasting.com/data.csv) if you don't download this file, my dataset same as following Year Month A B C D E 2005 July 0 *4* NA NA *1* 2005 July 0 NA NA 0 *9* 2005 July NA *4* 0 *1* 0 2005 July *4* 0 *2* *9* NA I try to count non-zero values which are not NA values for every *column* *Sincerely* *Engin YILMAZ*

Dear all, I have monthly data in wide format, I am only providing data (at the bottom of the email) for the first 24 columns but I have 2880 columns in total. I would like to take max of every 12 columns. I have taken the mean of every 12 columns with the following code: byapply <- function(x, by, fun, ...) { # Create index list if (length(by) == 1) { nc <- ncol(x)

Good day Sir/Ma'am! This is Alyssa Fatmah S. Mastura taking up Master of Science in Statistics at Mindanao State University-Iligan Institute Technology (MSU-IIT), Philippines. I am currently working on my master's thesis titled "Comparing the Three Estimation Methods for the Four Parametric Logistic (4PL) Item Response Model". While I am looking for a package about Markov chain