similar to: Truncating dates (and other date-time manipulations)

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 =

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 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,

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, 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

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

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

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 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'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,

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

I have a problem with duplicated date_time stamps that I do not see as duplicated. I read a file with observations taken every 30 minutes: > aur2009=read.csv(paste(datadir,"AUR_ECPP_2009.csv",sep="/"),sep=";",stringsAsFactors=F) > aur2009[1:3,1:5] Date.Time E_filled E_filled_flag LE_filled LE_filled_flag 1 1/1/2009 0:00 0 NaN 5.86

nuqneH, I've tried using TIS authsrv authentication via bsd auth and found it quite limited. The most important restriction it does not log ip and fqdn of the remote peer, nor the application name, to the authentication server. It does not matter much for TIS authsrv, but since other applications do provide such information, our authsrv version uses it for extra authentication restrictions.

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 =

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

I have an S3 class called "tis" (Time Indexed Series) which may or may not have multiple columns. I have a function "[<-.tis" that I've reproduced below. My question is this: inside of "[<-.tis", how can I distinguish between calls of the form x[i] <- someValue and x[i,] <- someValue ? In either case, nargs() is 3, and looking at the values

I have an S3 class called "tis" (Time Indexed Series) which may or may not have multiple columns. I have a function "[<-.tis" that I've reproduced below. My question is this: inside of "[<-.tis", how can I distinguish between calls of the form x[i] <- someValue and x[i,] <- someValue ? In either case, nargs() is 3, and looking at the values

List, I am using the 'tisPlot' function in Jeff Hallman's excellent tis package and was hoping that someone could spare me from having to dig into the code of his 'tisPlot' function. So far as I can tell, the preferred method of controlling the plotting of the x-axis is using the 'xTickFreq' and 'xTickSkip' options. Unfortunately, the where the data ends

Hi All: I''m writing my 1st Rails app and I can''t seem to find the answer on the web or in the book. I''m making a table, and I want to be able to expand a filename. The code is basically as as follows below. In the last <td> entry, I want to call an action and pass in the test_results_path, which I will go and read a file and munge the data for a separate

Hello All, Okay i think I''m finally getting all of what i want out of ferret working, thanks mostly to reading this forum and also getting ALOT of questions answered, thanks alot everyone. Anyway my last ferret task is too get the results sorted by a field called date_registered and have this working with pagination. here is what i''m doing at the moment: