similar to: Model frame when LHS is cbind (PR#14189)

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

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

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: >

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

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

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

> 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

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

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:

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:

> 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

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 =

Hello everyone, I am (happily) using ggplot2 for all my plotting now and I wondered is there is an easy way to specify xlim and ylim somewhere when using the ggplot syntax, as opposed to the qplot syntax. Eg. qplot(data=mtcars,y=wt, x=qsec,xlim=c(0,30)) <-> ggplot(mtcars, aes(y=wt, x=qsec)) + geom_point() + ??? Indeed the ggplot syntax is in general more flexible and powerful and

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

Using the mtcars dataset, how to define the grouping variable to be valid only for the upper or lower panel? The following doesn't work: # Code start splom(~data.frame(mpg, disp, hp, drat, wt, qsec), data=mtcars, pscales=0, auto.key=list(columns=3), upper.panel = function(...){ panel.grid(...) panel.xyplot(groups=cyl,...) } ) # Code end -- View

I'm interested in creating a graphic -like- this: c <- ggplot(mtcars, aes(qsec, wt)) c + geom_point() + stat_smooth(fill="blue", colour="darkblue", size=2, alpha = 0.2) but I need to show 2 sets of bands (with different shading) using 5%, 25%, 75%, 95% limits that I specify and where the heavy blue line is the median. I don't understand how to do this with

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 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

data(mtcars) mtcars[rownames(mtcars)!="Valiant",] # fails mtcars[list(rownames(mtcars))!="Valiant",] # runs but I am not getting the expected result With the latter statement, I expected all rows except the one where the name is "Valiant". I must have got something simple wrong; what is it? Thanks. [[alternative HTML version deleted]]

Hii i have been trying to do a scatter plot with ggplot2, like the plot 6 here (http://had.co.nz/ggplot2/geom_point.html) .. where the points size vary with values > p + geom_point(aes <http://had.co.nz/ggplot2/aes.html>(size = qsec)) but am not sure how to setup the parameter - qsec could anyone please give some pointers on how to define that thanks Mo. [[alternative HTML