posixct

I have a very big dataset with a DateTime Column containing POSIXct-Values. I need to determine the season (Winter - Summer) based on the DateTime column. I've created a function which works fine on a small dataset, but crashes when I use it on the large one. Can anybody see my mistake? I've created 4 functions: 3 subfunctions so that I can do logical comparisons and selection using *apply functions 1 function to determine the season Here are thefunctions: require(lubridate) # function for logical comparison (to be used in *apply) greaterOrEqual <- function(x,y){ ifelse(x >= y,T,F) } #

This question already has answers here : Read csv with dates and numbers (3 answers) I am working on "Localization Data for Person Activity Data Set" dataset from UCI and in this data set there is a column of date and time(both in one column) with following format: 27.05.2009 14:03:25:777 27.05.2009 14:03:25:183 27.05.2009 14:03:25:210 27.05.2009 14:03:25:237 ... I am wondering if there is anyway to convert this column to timestamp using R. Waldir Leoncio First of all, we need to substitute the colon separating the milliseconds from the seconds to a dot, otherwise the final step won't work

I'm trying to pull data from a PostgreSQL database and the results for a timestamp field are inconsistent. I'm not sure if I'm handling POSIXct results properly. Otherwise, I think I found a bug in the RPostgreSQL package. Here is the way to replicate the issue: Suppose there is a table in a postgres database with one field (run this in PostgreSQL): CREATE DATABASE mydb; CREATE TABLE test_table ( "DateTime" timestamp without time zone NOT NULL, CONSTRAINT "pk_test_table" PRIMARY KEY ("DateTime") ) WITH ( OIDS=FALSE ); ALTER TABLE test_table OWNER TO postgres; And let’s say there are a few

I am trying to expand the amount of factors shown in one custom Posixct field where the normal way ( str(DF, list.len=ncol(DF), vec.len=20) ) does not work. I request here 20 but it shows all the time two ( "2017-01-01 08:40:00" "2017-01-01 08:50:00" ... ) regardless the length of the list (here 3 ). Data data.csv "AAA", "BBB" 1, 01012017-0940+0100 2, 01012017-0950+0100 3, 01012017-0838+0100 Code library('methods') # setClass # https://unix.stackexchange.com/a/363290/16920 setClass('iso8601') # https://stackoverflow.com/questions/5788117/only-read-limited-number-of-columns setAs("character",

I am using the fasttime package for its fastPOSIXct function that can read character datetimes very efficiently. My problem is that it can only read character datetimes THAT ARE EXPRESSED IN GMT. R) fastPOSIXct("2010-03-15 12:37:17.223",tz="GMT") #very fast [1] "2010-03-15 12:31:16.223 GMT" R) as.POSIXct("2010-03-15 12:37:17.223",tz="GMT") #very slow [1] "2010-03-15 12:31:16.223 GMT" Now, say I have a file with datetimes expressed in "America/Montral" timezone, the plan is to load them (implicitely pretending they are in GMT) and modifying subsequently the timezone attribute without changing

I have a POSIXct object and would like to change it's tz attribute WITHOUT R to interpret it (interpret it would mean to change how the datetime is displayed on the screen). Some background: I am using the fasttime package from S.Urbanek, which take strings and cast it to POSIXct very quickly. Problem is that the string should represent a datetime in "GMT" and it's not the case of my data. I end up with a POSIXct object with tz=GMT , in reality it is tz=GMT+1 , if I change the timezone with attr(datetime, "tzone") <- "Europe/Paris"; datetime <- .POSIXct(datetime,tz="Europe/Paris"); then it

This question already has an answer here: Date conversion from POSIXct to Date in R 3 answers How can I get the correct date from the first column in my code? test <- data.frame(posixdate = c("2013-05-01 00:59:00", "2013-05-01 01:59:00", "2013-05-01 02:59:00", "2013-05-01 03:59:00")) test$posixdate <- as.POSIXct(test$posixdate, format="%Y-%m-%d %H:%M:%S" ) test$date <- as.Date(test$posixdate) The above code results in: posixdate date 1 2013-05-01 00:59:00 2013-04-30 2 2013-05-01 01:59:00 2013-04-30 3 2013-05-01 02:59:00 2013-05-01 4 2013-05-01 03:59:00 2013-05-01 The first two dates are not