similar to: Dataframe subset - why doesn't this work?

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

Dear Sirs, I am Professor at Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India. While taking classes, I found the *by() *function producing following error when I use FUN=mean or median and some other functions, however, FUN=summary works. Given below is the output of the example I used on a built-in dataset "mtcars", along with error message reproduced herewith: >

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Dear all; I need to run heatmap. Because my first column in my data is alphanumeric, I can not run as.matrix(scale(my_data)). So I need to make my data readable as in data(mtcars). In *mtcars *data the first column is alphanumeric and has no name. Thanks, Greg [[alternative HTML version deleted]]

Dear All, Thanks for your help. However, I would like to draw your attention to the following: Actually, I was replicating the Example 2.3, using the dataset "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, of a famous book "R by Example" written by "Jim Albert and Maria Rizzo" published in Springers (2012) in a Use R! Series. The

Buen día estimados Estoy tratando de hacer un tibble con los resultados de un apply que se muestran en la consola que me da R, no estoy seguro si eso se pueda hacer, pero me gustaría organizar los resultados de esa manera. mi código es: data("mtcars") Mtcars_matriz <- as.matrix(mtcars) apply(Mtcars_matriz, MARGIN =2, FUN = shapiro.test) DF2 <- tibble(Variable = NA, W = NA, Pvalue =

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by

I have applied the same linear model to several different subsets of a dataset. I recently read that in R, code should never be repeated. I feel my code as it currently stands has a lot of repetition, which could be condensed into fewer lines. I will use the mtcars dataset to replicate what I have done. My question is: how can I use fewer lines of code (for example using a for loop, a function or

I have been successfully using RODBC for a long time (years) to connect to MS SQL Server from R. This week I wanted to try using odbc but I am seeing some problems which may be related to how I set up my driver and/or connection. The dbWriteTable manual page gives as an example command: dbWriteTable( pDB$con, "mtcars", mtcars[1:5,]) When I try this I get the following error Error:

Dear All, I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code of their time (2012). Therefore, I have now modified my R-code, as per R-3..2.4 version, according to my requirement

> On Apr 15, 2016, at 1:16 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > Thanks for your help. However, I would like to draw your attention to the > following: > > Actually, I was replicating the Example 2.3, using the dataset > "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, > of a

> On Apr 16, 2016, at 2:03 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code

Double quotes are not legal SQL syntax. Use single quotes. -- Sent from my phone. Please excuse my brevity. On August 29, 2017 2:21:44 AM PDT, Eric Berger <ericjberger at gmail.com> wrote: >I have been successfully using RODBC for a long time (years) to connect >to >MS SQL Server from R. >This week I wanted to try using odbc but I am seeing some problems >which >may be

Dear all, What is the quickest and most efficient way to diff two data frames, so as to obtain a vector of indices (or logical) for rows/columns that differ in the two data frames? For example, > Xe <- head(mtcars) > Xf <- head(mtcars) > Xf[2:4,3:5] <- 55 > all.equal(Xe, Xf) [1] "Component 3: Mean relative difference: 0.6863118" [2] "Component 4: Mean relative

Dear R-help This is a follow-up to my previous post here: http://groups.google.com/group/r-help-archive/browse_thread/thread/d9b6f87ce06a9fb7/e9be30a4688f239c?lnk=gst&q=dobomode#e9be30a4688f239c I am working on developing an open-source automated system for running batch-regressions on very large datasets. In my previous post, I posed the question of obtaining VIF's from the output of

Dear List I have math test scores for male and female students where gender is a dummy code (female =1). I also have a variety of other demographic variables. However to begin, I want to create a very simple stripchart where female math scores are a blue circle and male scores are a red triangle. I am having difficulty using conditional statements to accomplish this. Thank you. ------

The model frame shows the response and predictors in a data frame with nicely labelled columns: fm <- lm(wt~qsec+log(hp)+sqrt(disp), data=mtcars) model.frame(fm) # ok When the left hand side consists of more than one response, those response variables still look good, inside a matrix: fm <- lm(cbind(qsec,hp,disp)~wt, data=mtcars) model.frame(fm)[[1]] # ok A problem arises when

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of

is it possible to map 2 plots(c and d) in a single output plot? library(ggplot2) c <- ggplot(mtcars, aes(qsec, wt)) d <- ggplot (mtcars, aes(qsec, wt)) c + stat_smooth(fill="darkgrey", colour="blue", size=2, alpha = 0.2) d + stat_smooth(fill="darkgrey", colour="red", size=2, alpha = 0.2) -- View this message in context: