similar to: arules - getting transaction data in

I need to allow the company operator to decide whether to record a call. (Car dealership that needs to coach salespeople). They don't want to record every sales call, just for the purposes of coaching certain employees on an ad hoc basis. The situation is: a. Call comes in on PSTN PRI b. Call is routed to operator in dialplan c. Operator ascertains that its a sales call for a salesman in

Hello, Using base R only, the following seems to do what you want. with(mydf, ave(speed, date_time, type, FUN = weighted.mean, w = n_vehicles)) Hope this helps, Rui Barradas Em 09-11-2017 13:16, Massimo Bressan escreveu: > Hello > > an update about my question: I worked out the following solution (with the package "dplyr") > > library(dplyr) > > mydf%>% >

Hi All. I have a mysql statement that I would really really like to call from my Ruby program which goes like this: SELECT a, b, DAYOFWEEK(date_time) as DOW, HOUR(date_time) at hr, AVG(x/y) FROM records; This is possible by creating a 3-dimentional array of a, b, date_time containing x/y, and then finding averages and putting it into a 4-dimensional array of a, b, dow,

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

Hi, I''d be grateful for your help. I get the error (see below) everytime I add the following into a newly generated (via scaffold) model class: validates_presence_of :myname, :mymessage, :mytel Without it, I can insert records into my database. With it, I get the error :( ERROR>> ArgumentError in AdminController#create wrong number of arguments (1 for 0) RAILS_ROOT:

Dear All, I seem to have stumbled across an AGI problem; I have written an AGI Script (bottom of this email); The script does the following; Makes a CDR entry when called Records the call Updates the CDR Finds a corresponding DNIS from the SMDR table (captured via a serial port logger) Matches up the record and updates the CDR. The script works perfectly in my test lab and has been doing so

Hi, I'm new to R and new to this forum. I'm struggling with trying to extract certain rows of data from my data.frame. The data.frame has eleven columns. Among those columns are "FISH_ID" and "DATE_TIME". FISH_ID is a factor. For each of my 21 unique FISH_IDs (levels) I have a few to a few thousand rows, each row with a unique DATE_TIME value. I would like to obtain,

Look at the bottom of the message for my question #here is a little function that I wrote USGS <- function(input="discharge", days=7){ library(chron) library(gsubfn) #021973269 is the Waynesboro Gauge on the Savannah River Proper (SRS) #02102908 is the Flat Creek Gauge (ftbrfcms) #02133500 is the Drowning Creek (ftbrbmcm) #02341800 is the Upatoi Creek Near Columbus (ftbn) #02342500 is

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 all I have this dataframe (created as a reproducible example) mydf<-structure(list(date_time = structure(c(1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000), class = c("POSIXct", "POSIXt"), tzone = ""), direction = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("A", "B"), class =

> 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, I have a irregularly spaced time series dataset, which reads in from a .csv. I need to convert this to a regularly spaced time series by filling in missing rows of data with NAs. So my data, called NtuMot, looks like this (I've removed some of the additional rows for simplicity).... ELEID date_time height slope 1 2009-06-24 00:00:00

note: whole function is below- I am sure I am doing something silly. when I use it like USGS(input="precipitation") it is choking on the precip.1 <- subset(DF, precipitation!="NA") b <- ddply(precip.1$precipitation, .(precip.1$gauge_name), cumsum) DF.precip <- precip.1 DF.precip$precipitation <- b$.data part, but runs fine outside of the function: days=7

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

> On Jul 30, 2006, at 5:11 PM, Chris H wrote: > >> Hi Ezra, >> >> thanks for the reply. >> >> There''s a ruby process that appears in top when I fire off the do_work >> method. >> It uses around 30-50% cpu and disappears once all processing has >> completed. >> >> When I try to stop processing using delete_worker I was

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =

Oh I overlooked that one.. Thanks Darren! Btw, I was wondering if anyone has tried using the echo canceller function of speex with other codec like g.711? On Tue, Jan 17, 2012 at 8:32 PM, Darren Longhorn < darren.longhorn at redembedded.com> wrote: > On 14/01/12 12:26, Christopher Adoremos wrote: > > What is the highest quality audio data rate and sample rate Speex can >

What is the best way to make use of the new "scoping" operators and otherwise search the database using deep relationship chains Take for example that I want to query what items all customers have ever bought from one salesman salesman has-many customers customers have-many orders orders have many items Now I want to write an application which is for the use of only one salesman

Hi! I'm reading a tab-seperated CVS file with: test1 <- read.table("data.txt", header=TRUE) It's in the following format: Date_Time qK qL vL vP ... 0 30 22 110 88 ... ... (BTW: It seems to me R shifts the column descriptions by one.) Anyway, I would like to Fourier-transform one column. So I say: > fft(test1$vP) Error in levels(x)[x] : invalid subscript type

If I want to test for a salesman effect on average sale, I model it as "Sale ~ Salesman". But what if I want to test for a salesman effect on total sales? How do I model that? Given a significant salesman effect, how do I follow up with the equivalent of Tukey's HSD to determine who the (indistinguishly) top salesmen are? If I add another factor, say "region" to the