similar to: Curiously short cycles in iterated permutations with the same seed

Hi Boris, Do a search on "the order of elements of the symmetric group". (This search will also turn up homework questions and solutions.) You will understand why you are seeing this once you understand how a permutation is decomposed into cycles and how the order relates to a partition of n (n=10 in your case). Enjoy! Eric On Fri, Dec 8, 2017 at 6:39 AM, Boris Steipe <boris.steipe

Muchísimas gracias Carlos, de verdad que te agradezco la ayuda, pero no es lo que voy buscando. Quiero colocar en el eje de abscisas la secuencia temporal de los meses, es decir, agosto septiembre, octubre, etc? pero no las fechas de las toma de datos, sino que aparezca la marca de un mes, y la siguiente marca sea la del siguiente mes, etc?, y además que las muestras estén separadas de acuerdo con

Muchas gracias Carlos, previo a mi correo, entre las pruebas que hice estaba una parecida a la que apuntas de la siguiente manera: attach (Libro1) plot (xbar~as.Date(fechas,"%d/%m/%y"), ylim=c(400,660), xaxt="n", type="b", pch=19,cex=1) xlabels<-strptime(fecha,format="%d/%m/%Y") axis.Date (1,at=xlabels,format="%b-%y")

Hi, Given that cdplot() is used to produce the conditional density of a categorical y along a numerical x, it seems natural that it could be used with a date or time x (such as 'POSIXct'). Is this desirable? If so, I've created a patch that would allow this, by coercing the POSIXct x variable to produce the density, but use the original POSIXct x to draw the x axis. Index:

myDF <- data.frame(a = c("<0.1", NA, 0.3, 5, "Nil"), b = c("<0.1", 1, 0.3, 5, "Nil"), stringsAsFactors = FALSE) # you can subset the b-column in several ways myDF[ , 2] myDF[ , "b"] myDF$b # using the column, you make a logical vector ! is.na(as.numeric(myDF$b)) # This can be used to select the

I responded to the unhelpful suggestion "Why don't you implement and uplad the package to CRAN?" No mention of a search engine. Is this what you are commenting on Jeff? > On Jun 28, 2017, at 5:41 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > > In what way does reminding people that packages exist because others just like them contributed something

Always via logical expressions. In this case you can use the logical expression myDF$b != "0" to give you a vector of TRUE/FALSE B. > On Sep 25, 2017, at 8:00 AM, Shane Carey <careyshan at gmail.com> wrote: > > This is super, really helpfull. Sorry, one final question, lets say I wanted to remove 0's rather than NAs , what would it be? > > Thanks >

ChatGPT-4: ------ Query: ---------------------------------- Thank you. The `value` in the code example is 2874. The plot shows a large number at the center and a smaller value computed as a delta relative to the `reference` of 4800. But the large value is given as 2870, and the smaller value is given as -1930 i.e. both values are rounded. Can I control the precision of these two numbers?

Super, Thanks On Fri, Sep 22, 2017 at 4:57 PM, Boris Steipe <boris.steipe at utoronto.ca> wrote: > > a <- c("<0.1", NA, 0.3, 5, "Nil") > > a > [1] "<0.1" NA "0.3" "5" "Nil" > > > b <- as.numeric(a) > Warning message: > NAs introduced by coercion > > b > [1] NA NA 0.3

No. The empty sum is zero. Adding it to another sum should not change it. Nothing audacious about that. This is consistent; other definitions just cause trouble. -pd > On 21 Mar 2018, at 18:05 , Boris Steipe <boris.steipe at utoronto.ca> wrote: > > Surely the result of summation of non-existent values is not defined, is it not? And since the NA values have been _removed_,

The loop : AllMAFs <- list() for (i in length(SeparatedGroupsofmealsCombs) { AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) )) } gives these errors (I tried this many times and I'm sure I copied it entirely) :- Error in apply(SeparatedGroupsofmealsCombs[[i]], 2, function(x) maf(tabulate(x + : object 'i' not found > }

This is super, really helpfull. Sorry, one final question, lets say I wanted to remove 0's rather than NAs , what would it be? Thanks On Mon, Sep 25, 2017 at 12:41 PM, Boris Steipe <boris.steipe at utoronto.ca> wrote: > myDF <- data.frame(a = c("<0.1", NA, 0.3, 5, "Nil"), > b = c("<0.1", 1, 0.3, 5, "Nil"), >

> On Nov 18, 2017, at 1:52 AM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > Although the loop seems to be formulated correctly I wonder why > it gives me these errors : > > -object 'i' not found > - unexpected '}' in "}" You probably did not copy the entire code offered. But we cannot know since you did not "show your code",

Although the loop seems to be formulated correctly I wonder why it gives me these errors : -object 'i' not found - unexpected '}' in "}" the desired output is expected to be very large as for each dataframe in the list of dataframes I expect to see maf value for each of the 600 columns! and this is only for for one dataframe in the list .. I have around 150-200

Please keep messages on the list so others can pitch in. _Which_ words do you want to consider identical for the purpose of frequency count? _What_ do you want to plot? B. > On Aug 3, 2017, at 4:36 PM, Riaan Van Der Walt <Riaan.VanDerWalt at nwu.ac.za> wrote: > > Hallo Boris, > I've loaded the Rstem, Snowball. > But I am clueless how to get a list eg. whal* (whale,

The help text for row+colnames {base} states: "For a data frame, rownames and colnames eventually call row.names and names respectively, but the latter are preferred." Why are they "preferred"? Why is it names(), not col.names()? I have only ever used names() for vectors - I'm surprised it works on data.frames... IMO this is not great for code readability, thus

I see: consistency with additive identity. That makes sense. Thanks. B. > On Mar 21, 2018, at 1:22 PM, peter dalgaard <pdalgd at gmail.com> wrote: > > No. The empty sum is zero. Adding it to another sum should not change it. Nothing audacious about that. This is consistent; other definitions just cause trouble. > > -pd > >> On 21 Mar 2018, at 18:05 , Boris

Thanks I too wondered about the tone. The first suggestion was that I should "google it" and the second, write my own code. I think if I did I'd be reinventing the wheel, (and it'd be a big challenge for me). Also, I have been searching and not found such code, despite evidence that it has been coded (just not sure if it was in R). BTW I did write to authors of the article I

"I see: consistency with additive identity. " Ummm, well: > 1+NULL numeric(0) > sum(1,NULL) [1] 1 Of course, there could well be something here I don't get, but that doesn't look very consistent to me. However, as I said privately, so long as the corner case behavior is documented, which it is, I don't care. Cheers, Bert Bert Gunter "The trouble with

Hi, Lets say this was a dataframe where I had two columns a <- c("<0.1", NA, 0.3, 5, "Nil") b <- c("<0.1", 1, 0.3, 5, "Nil") And I just want to remove the rows from the dataframe where there were NAs in the b column, what is the syntax for doing that? Thanks in advance On Fri, Sep 22, 2017 at 5:04 PM, Shane Carey <careyshan at