similar to: ext3 from whithin W2K

Hello to all, I have two dataframes, the first with two columns sunrise and sunset (for 10 years). Each of these columns is formatted for date time (ex: 01-Jan-2010 15:37:00) In the second data frame I have GPS information and also a date time column (same format ). What I would like to do is a subset of all the rows from the second dataframe that occurred in day time only so between sunrise

I have these two dataframes in which 'id' is the key field > tabella id nome 1 1 PIEMONTE 2 2 VALLED'AOSTA 3 3 LOMBARDIA 4 4 TRENTINO 5 5 VENETO 6 6 FRIULI AND > tab id nome 1 1 PIEMONTE 2 2 VALLED'AOSTA 3 3 LOMBARDIA 4 4 TRENTINO 5 25 CAMPANIA 6 28 LAZIO Is there any

Hello again, (FYI, I took the liberty to change the topic since I started the former thread "How is Win/Dos syscalls implemented in Wine?" which I feel has gone a little bit off-topic) I had some more thoughts on the issue... I believe most wine users trust wine not to touch anything outside of its configured drive space. Malicious Linux/Unix syscalls could be embedded in windows

Dear Massimo, It seems straightforward to use weighted.mean() in a dplyr context library(dplyr) mydf %>% group_by(date_time, type) %>% summarise(vel = weighted.mean(speed, n_vehicles)) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team

Hello, One of my Julia programs failed to execute with the following error, DICompileUnit not listed in llvm.dbg.cu !11 = distinct !DICompileUnit(language: DW_LANG_C89, file: !3, producer: "julia", isOptimized: true, runtimeVersion: 0,emissionKind: FullDebug, enums : !12) This was generated by verifyModule(*GPUModule,&(llvm::errs())From whithin PPCGCodeGeneration.cpp in Polly.

Hello, I want to implement a perl logon script which would map network shares depending on group membership. This way when I move a user to or from a group it automatically gets the new shares. The PDC is Samba 2.2.1 or 2.2.2 on BSD and clients are NT workstation and 2000 Pro. Perl is latest activestate for win32 and is intended to run on Win32 clients. The big trouble is getting user Group

Dear R-helpers, How do I tell panel.polygon what greoup and panel it applies to whithin xyplot(y ~ x | c, groups = g panel = function(x, y, groups, ...){ panel.polygon(x = xpol[c, g], y = ypol[c, g], default.units = 'native') panel.xYplot(x, y, groups, ...) llines(x = c(1, 6), y = c(-24.283333, 35.941667), lwd = 2, lty = 3, col = 4) } x[c, g] and y[c, g] describe

yes, it works, even if I do not really get how and why it's working the combination of logical results (could you provide some insights for that?) moreover, and most of all, I was hoping for a compact solution because I need to deal with MANY columns (more than 40) in data frame with the same basic structure as the simplified example I posted thanks m ----- Messaggio originale ----- Da:

Hello an update about my question: I worked out the following solution (with the package "dplyr") library(dplyr) mydf%>% mutate(speed_vehicles=n_vehicles*mydf$speed) %>% group_by(date_time,type) %>% summarise( sum_n_times_speed=sum(speed_vehicles), n_vehicles=sum(n_vehicles), vel=sum(speed_vehicles)/sum(n_vehicles) ) In fact I was hoping to manage everything in a

hi everyone, here i have a question: is there any chance in llvm intermediate representation to compare whether a operand (ie a value) is used as a user without iterating over all the instructions in a basic block. i will explain this with an example: i=p+4; j=i+p; in the above example i mean p,4,i,p which are on the RHS are operands and the terms i,j which are on the LHS are users. so what i

Hi, I have got a problem with the semantics of file permissions on a file system mounted by smbmount on a Linux box (kernel 2.2.14, Samba 2.0.6, and after looking through the 2.0.7 announcement, it appears that the problem has not been addressed there). Consider the following case: I mount a share from an NT server on a Linux box, which I then use at the Linux box. I create a file on that

Hi all, I''m sure I''m soing something wrong here. I am trying to set up a rate limit inside another rate limit. eg. I have a 512K rate limit on a particular VLAN. I am using an IFB so that packets passing through the bridge are counted at each port.(ie the throughput is limited to 512K, not just the traffic in one direction.) This part works OK, but I also want to limit a

...well, I don't think this is exactly the expected result (see my post) to be noted that the columns affected should be "A" and "B" thanks for the help max ----- Messaggio originale ----- Da: "Rui Barradas" <ruipbarradas at sapo.pt> A: "Massimo Bressan" <massimo.bressan at arpa.veneto.it>, "r-help" <r-help at

Hi All, I'm trying to compile clang+llvm on my desktop with cross-compiler to be able to work with llvm commands in ubuntu-arm image whithin gem5. If anybody has done this before I'd be so thankful to know the exact process and commands. I tried to configure llvm as follows but I couldn't get the arm-arm version correctly. To sum up, I need to cross-compile llvm for ARM to work in

Hi, suppose I have data from 3 experiments which show conversion as a function of time for different boundary conditions, e.g. pressure, temperature. I want to plot all experiments as conversion over time grouped according to the temperature. However, since I have more than one experiment performed at the same temperature (but different pressures) I end up figuring out which curve belongs

Hi all, I'm new to the list, so please be patient with me. Samba 2.0.7 is running on a compaq alpha server es40 with tru64 4.D. We got a problem with powerpoint files on a samba share. As soon as I open a powerpoint file on a samba share the modification time of the file changes, even if I'm not changing anything whithin the file. This only happens if I open *.ppt files which where

For time scale that are truly discrete Cox proposed the "exact partial likelihood". I call that the "exact" method and SAS calls it the "discrete" method. What we compute is precisely the same, however they use a clever algorithm which is faster. To make things even more confusing, Prentice introduced an "exact marginal likelihood" which is not

Do you mean like this: mydf <- within(mydf, { is.na(A)<- !A_flag is.na(B)<- !B_flag } ) > mydf A A_flag B B_flag 1 8 10 5 12 2 NA 0 6 9 3 10 1 NA 0 4 NA 0 1 5 5 5 2 NA 0 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into

> On 9 Nov 2017, at 14:58, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > Thanks for working example. > > you could use split/ lapply approach, however it is probably not much better than dplyr method. > > sapply(split(mydf, mydf$type), function(speed, n_vehicles) sum(mydf$speed*mydf$n_vehicles)/sum(mydf$n_vehicles)) > gives you averages > The

Hi Thanks for working example. you could use split/ lapply approach, however it is probably not much better than dplyr method. sapply(split(mydf, mydf$type), function(speed, n_vehicles) sum(mydf$speed*mydf$n_vehicles)/sum(mydf$n_vehicles)) gives you averages aggregate(mydf$n_vehicles, list(mydf$type), sum)$x gives you sums Cheers Petr > -----Original Message----- > From: R-help