similar to: strptime and "impossible" dates

Hi, I think that there is something that I am misunderstanding in creating tables using dates that are of class POSIXct. Consider: > x <- data.frame(date = as.POSIXct(strptime(c(rep("2002-10-17", 4), rep("1999-12-08", 2)), format = "%Y-%m-%d"))) > x date 1 2002-10-17 2 2002-10-17 3 2002-10-17 4 2002-10-17 5 1999-12-08 6 1999-12-08 > table(x$date)

I am just starting to play with R. What is the recommended manner for dealing with dates? In particular, should I be using the "chron" or the "date" package or working with some of the facilities in base R like strptime? My needs are very limitted. I have variables that, in S+ 6.0, I treat as timeDate objects. I rarely need to do more than read in the information from text

Hi, In 1.4.1, I was able to create extra "empty" rows in a dataframe as so: > x <- data.frame(a = letters[1:3], b = 1:3) > x a b 1 a 1 2 b 2 3 c 3 > x[4,] a b NA NA NA > rbind(x, x[4,]) a b 1 a 1 2 b 2 3 c 3 NA NA NA > R.version _ platform sparc-sun-solaris2.6 arch sparc os solaris2.6

Almost all of the heavy crunching I do in R is like: > for(i in long.list){ + do.something(i) + } > collect.results() Since all the invocations of do.something are independent of one another, there is no reason that I can't run them in parallel. Since my machine has four processors, a natural way to do this is to divide up long.list into 4 pieces and then start 4 jobs, each of which

Hi This code should explain what I'm trying to do > strptime("30-Jan-08", "%d-%b-%y") [1] "2008-01-30" > > format(strptime("30-Jan-08", "%d-%b-%y") , "%b-%y") [1] "Jan-08" > > strptime(format(strptime("30-Jan-08", "%d-%b-%y") , "%b-%y") , "%b-%y") [1] NA I have a

Hi All In trying to correlate some tide gauge data I need to deal with varying timezones. From the documentation on strptime, it seemed that the tz variable might have some effect on the conversion, but I'm not seeing an effect. > strptime("20061201 1:02 PST",format="%Y%m%d %H:%M",tz="PST")+0 [1] "2006-12-01 01:02:00 EST" >

I'm trying to proess date/time fields from files that were given to me to analyze. Any clues what I'm doing wrong with strptime? This seems to fail the same way under Linux or Windows. For ?strptime would it make sense to explain %OS3 somewhere besides the Examples? > # Why does %OS3 work here? > format(Sys.time(), "%H:%M:%S") [1] "16:45:19" >

Hi, I am having a trouble parsing dates using strptime() that I get in the format of year and week number. The data looks like this "201127" which means year 2011 and week 27. I would like to graph this using ggplot but then I get a gap between 201054 and 201101 so I thought I would just easily convert it. I tried to use strptime and as.Date and the format string of %Y%W but it seems

Hi, I'm reading data from a text file and transforming it in R and my date column seems to be getting corrupted. Can someone point out what's wrong? This code worked fine until I added a new date in 2010. thank you. To load the data I run: work_table = read.table(datafilename,header=TRUE) #read the data file attach(work_table)

In previous versions of R (at least in 1.5.1, I think), my practice was not to include an INDEX file in the package. R CMD check did not complain and an INDEX was created for me when I use R CMD build. At least, this is how I remember it. I thought that this was a good way to behave since it ensured that my INDEX was automatically kept up to date by R, without me having to worry about what

Hi Frederik, On Mon, 2017-01-16 at 18:20 -0800, frederik at ofb.net wrote: > Hi R Devel, > > I wrote some code which depends on 'strptime' being able to parse an > incomplete date, like this: > > > > > base::strptime("2016","%Y") > [1] "2016-01-14 PST" > > The above works - although it's odd that it gives the month

I often use merge with dataframes that contain character vectors which have elements that are sometimes "NA" (meaning the string NA, not the same thing, obviously, as NA in a numeric or factor vector). For example, the stock ticker for Nabisco was "NA". Unfortunately (for me), it seems like merge insists on inserting "NA" for missing values. My question: Is there some

Full_Name: Bill Hutchison Version: 2.2.1 OS: Windows XP Submission from: (NULL) (69.158.121.13) example(strptime) produces the following error: Error in strptime(x, "%d%b%Y") : 2 arguments passed to 'strptime' which requires 3 This error occurs wherever strptime is used. It does not occur in 2.2.0

Converting date strings that range between Mar-14-2010 2:00 and Mar-14-2010 2:59 (inclusive) to date objects (POSIX) returns a NA entity: > strptime("3/14/2010 2:00",format="%m/%d/%Y %H:%M") [1] "2010-03-14 02:00:00" This looks fine, however other functions such as plot see a NA object instead: > is.na(strptime("3/14/2010

Hi everyone, I have bunch of date and time observations in the format %Y-%m-%d %I %M %S %p. I used strptime() to read this format. But the problem is some of the times are in the format of %I %M %p, so for those times, strptime is giving me NA values. For example, strptime(paste("2009-04-08","1:49:47 PM"),format="%Y-%m-%d %I:%M:%S %p") [1] "2009-04-08

On Tue, Jan 10, 2017 at 08:13:21PM -0600, Dirk Eddelbuettel wrote: > > On 10 January 2017 at 17:48, frederik at ofb.net wrote: > | Hi R Devel, > | > | I just ran into a corner case with 'strptime'. Recall that the "%OS" > | conversion accepts fractional seconds: > | > | > strptime("17_35_14.01234.mp3","%H_%M_%OS.mp3")$sec > |

I understand that NA's in character vectors are displayed differently than NA's in factor vectors. > c("x", NA, "y") [1] "x" NA "y" > as.factor(c("x", NA, "y")) [1] x <NA> y Levels: x y That seems sensible enough. But shouldn't I see the same behavior in a dataframe? > test <- data.frame(a =

Is there a way to make as.Date() and strptime() process strings with negative years? It appears that Date objects can contain negative years and you can convert them to strings, but you can't convert them back to Date objects. x <- as.Date(c("0001-01-24", "0500-01-24")) as.character(x) # "0001-01-24" "0500-02-02" as.Date(as.character(x)) #

I think the following examples illustrate the crux of the matter (version and OS info are below). The problem has to do with the transition from standard time to daylight savings time. My timezone, US/Pacific, has two parts: standard time (PST) 8 hours behind GMT and daylight savings time (PDT) 7 hours behind GMT. The transition takes place this year on 7 April at 02:00, when 02:00 is

I'm sure this is just the result of a basic misunderstanding of the syntax of R, but I am stumped. A <- read.table(file="sumByThirtyMinute.csv",sep=",",col.names=c("date","pandl")) A now consists of thousands of rows, but A$date is a string... ... 3183 2006-02-28 12:00:00 548.470 3184 2006-02-28 12:30:00 515.240 3185 2006-02-28 13:00:00