I have 2 Date variables in a .csv file with formats of "07-JUL-16 06.05.54.000000 AM". I want to use these in a regression model. Should I be reading these into a data frame as factors or characters? How can I take a difference of the 2 dates in each case?
Read them in as characters (e.g. stringsAsFactors=FALSE or tidyverse functions), then use as.POSIXct, e.g.
as.POSIXct("07-JUL-16 06.05.54.000000 AM",format="%d-%b-%y %I.%M.%OS %p")
## [1] "2016-07-07 06:05:54 EDT"
(I'm assuming that you are intending a day-month-year format rather than a month-day-year format -- but actually I don't have any evidence to support that thought!)
Once you've done this, subtracting the values should just work (give you an object of difftime) -- but be careful with units when converting to numeric!
For what it's worth, lubridate::ymd_hms thinks it can guess the format, but guesses wrong (?? assuming I guessed right above: with a two-digit year, and without any year values greater than 31, there's really nothing to distinguish years and days ...)
Related
Newbie here, first post (please be gentle). I have been trying to resolve this for several hours, so finally decided time to ask advice.
I have a large spreadsheet which I am importing with readxl. It contains one column with date (format dd/mm/yyyy) and several time columns in format hh:mm as can be seen: excel
Essentially I want to be able to import both time and date columns and combine them, so that I can then do some other calculations, like time elapsed.
If I import letting R guess the col-types, it converts the times to POSIXct, but these then have a date on 1899 attached to them: R_POSIXct
If I force readxl to assign the time column to numeric, I get a decimal (e.g. 0.315972222 for 07:35), which then tried converting using similar syntax to
format(as.POSIXct(Sys.Date() + 0.315972222), "%Y-%m-%d %H:%M:%S", tz="UTC")
i.e.
df$datetime <- format(as.POSIXct(df$date + df$time), "%Y-%m-%d %H:%M", tz="UTC")
which results in the correct date, but with a time of 00:00, not the time it is passed.
I have tried searching here and found posts to be not quite the same question (e.g. Combining date and time columns into dd/mm/yyyy hh:mm), and have read widely, including about about lubridate, but as I'm only 6 months into R, am finding some explanations a bit cryptic.
Suggestions or ignposting appreciated (if there are solutions I haven't found)
If you subtract the number of days between 1899-01-01 and 1970-01-01 and then multiply that (shifted) Excel numeric value by 3600 you should come close to the number of seconds since start of 1970. You could then convert to POSIXct with as.POSIXct( x, origin="1970-01-01"). That does seem to be "the hard way", however
It would be far easier and probably more accurate to convert the date-times to YYYY-MM-DD H:M:S format and then export as csv to be imported into R as text. There is a "POSIXct" colClasses argument to read.csv, although it doesn't handle separate columns of date and time. For that you would be advised to import as character values and then paste the dates and times. Then watch you format strings for as.POSIXct. The dd/mm/yyyy "format" would be specified by "%d/%m/%Y".
I have a data set in R that contains a column of dates in the format yyyy/mm/dd. I am trying to use as.Date to convert these dates to date objects in R. However, I cannot seem to find the correct argument for origin to input into as.Date. The following code is an example of what I have been trying. I am using a CSV file from Excel, so I used origin="1899/12/30 based on other sites I have looked at.
> as.Date(2001/04/26, origin="1899/12/30")
[1] "1900-01-18"
However, this is not working since the input date 2001/04/26 is returned as "1900-01-18". I need to convert the dates into date objects so I can then convert the dates into julian dates.
You can either is as.Date with a numeric value, or with a character value. When you type just 2001/04/26 into R, that's doing division and getting 19.24 (a numeric value). And numeric values require an origin and the number you supply is the offset from that origin. So you're getting 19 days away from your origin, ie "1900-01-18". A date like Apr 26 2001 would be
as.Date(40659, origin="1899-12-30")
# [1] "2011-04-26"
If your dates from Excel "look like" dates chances are they are character values (or factors). To convert a character value to a Date with as.Date() you want so specify a format. Here
as.Date("2001/04/26", format="%Y/%m/%d")
# [1] "2001-04-26"
see ?strptime for details on the special % variables. Now if you're read your data into a data.frame with read.table or something, there's a chance your variable may be a factor. If that's the case, you'll want do convert to character with'
as.Date(as.character(mydf$datecol), format="%Y/%m/%d")
The r code that I am working on is supposed to use the data collected in every five minute intervals.
The data is saved in csv format. However, due to inconsistency in the data collected, the time column in the data sometimes represent timestamp instead of just time.(dd/mm/yyyy HH:MM, instead of HH:MM)
This causes an error to my system as the system reads the data as having multiple different values for the same time value. Therefore, I would like to omit the date format from the timestamp such that the code would only read the time value.
My failed attempt was:
as.Date(data[[1]],"%H:%M")
which gave me all NA values for the time column.
I have searched for similar questions in SO, but I did not manage to find a clear answer to my question. Can anyone suggest me some possible functions to use?
I appreciate your help.
You could just strip the date portion of the text and then use as.POSIXct to convert them all to a %H:%M timestamp, e.g.:
x <- c("10:25","01/01/2014 10:30")
x <- gsub("^.+(\\d{2}:\\d{2})$","\\1",x)
as.POSIXct(x,format="%H:%M",tz="UTC")
#[1] "2014-06-02 10:25:00 UTC" "2014-06-02 10:30:00 UTC"
I am using the new version of data.table and especially the AWESOME fread function. My files contain dates that are loaded as strings (cause I don't know to do it otherwise) looking like 01APR2008:09:00:00.
I need to sort the data.table on those datetimes and then for the sort to be efficient to cast then in the IDateTime format (or anything alse I would not know yet).
> strptime("01APR2008:09:00:00","%d%b%Y:%H:%M:%S")
[1] "2008-04-01 09:00:00"
> IDateTime(strptime("01APR2008:09:00:00","%d%b%Y:%H:%M:%S"))
idate itime
1: 2008-04-01 09:00:00
> IDateTime("01APR2008:09:00:00","%d%b%Y:%H:%M:%S")
Error in charToDate(x) :
character string is not in a standard unambiguous format
It looks like I cannot do DT[ , newType := IDateTime(strptime(oldType, "%d%b%Y:%H:%M:%S"))].
My questions are then:
Is there a way to cast directly to IDateTime from fread, such that I can sort afterward efficiently?
If not, what is the most efficient way to go knowing that I would like to be able to sort DT by this datetime column
Unfortunately (for efficiency) strptime produces a POSIXlt type, which is unsupported by data.table and always will be due its size (40 bytes per date!) and structure. Although strftime produces the much better POSIXct, it still does it via POSIXlt. More info here :
http://stackoverflow.com/a/12788992/403310
Looking to base functions such as as.Date, it uses strptime too, creating an integer offset from epoch (oddly) stored as double. The IDate (and friends) class in data.table aims to achieve integer epoch offsets stored as, um, integer. Suitable for fast sorting by base::sort.list(method = "radix") (which is really a counting sort). IDate doesn't really aim to be fast at (usually one off) conversion.
So to convert string dates/times, rightly or wrongly, I tend to roll my own helper function.
If the string date is "2012-12-24" I'd lean towards: as.integer(gsub("-", "", col)) and proceed with YYYYMMDD integer dates. Similarly times can be HHMMDD as an integer. Two columns: date and time separately can be useful if you generally want to roll = TRUE within a day, but not to the previous day. Grouping by month is simple and fast: by = date %/% 100L. Adding and subtracting days is troublesome, but it is anyway because rarely do you want to add calendar days, rather weekdays or business days. So that's a lookup to your business day vector anyway.
In your case the character month would need a conversion to 1:12. There isn't a separator in your dates "01APR2008", so a substring would be one way followed by a match or fmatch on the month name. Are you in control of the file format? If so, numbers are better in an unambiguous format that sorts naturally such as %Y-%m-%d, or %Y%m%d.
I haven't yet got to how best do this in fread, so date/times are left as character currently because I'm not yet sure how to detect the date format or which type to output. It does need to output either integer or double dates though, rather than inefficient character. I suspect that my use of YYYYMMDD integers are seen as unconventional, so I'm a little hesitant to make that the default. They have their place, and there are pros and cons of epoch based dates too. Dates don't have to be always epoch based is all I'm suggesting.
What do you think? Btw, thanks for encouragement on fread; was nice to see.
I d'ont know how your file is structured, but from your comment you want to use the date field as a key. Why not to read it as a time series and format it when in reading?
Here I use zoo to do it.(Here I suppose that the date column is the first one,otherwise see index.colum argument)
ff <- function(x) as.POSIXct(strptime(x,"%d%b%Y:%H:%M:%S"))
h <- read.zoo(text = "03avril2008:09:00:00 125
02avril2008:09:30:00 126
05avril2008:09:10:00 127
04avril2008:09:20:00 128
01avril2008:09:00:00 128"
,FUN=ff)
You get your dates sorted in the right format and sorted.
The conversion is natural from POSIXct to IDateTime
IDateTime(index(h))
idate itime
1: 2008-04-01 09:00:00
2: 2008-04-02 09:30:00
3: 2008-04-03 09:00:00
4: 2008-04-04 09:20:00
5: 2008-04-05 09:10:00
Here sure you still do 2 conversions, But you do it when reading data, and the second you do it without dealing with any format problem.
In most cases, we convert numeric time to POSIXct format using R. However, if we want to compare two time points, then we would prefer the numeric time format. For example, I have a date format like "2001-03-13 10:31:00",
begin <- "2001-03-13 10:31:00"
Using R, I want to covert this into a numeric (e.g., the Julian time), perhaps something like the passing seconds between 1970-01-01 00:00:00 and 2001-03-13 10:31:00.
Do you have any suggestions?
The Julian calendar began in 45 BC (709 AUC) as a reform of the Roman calendar by Julius Caesar. It was chosen after consultation with the astronomer Sosigenes of Alexandria and was probably designed to approximate the tropical year (known at least since Hipparchus). see http://en.wikipedia.org/wiki/Julian_calendar
If you just want to remove ":" , " ", and "-" from a character vector then this will suffice:
end <- gsub("[: -]", "" , begin, perl=TRUE)
#> end
#[1] "20010313103100"
You should read the section about 1/4 of the way down in ?regex about character classes. Since the "-" is special in that context as a range operator, it needs to be placed first or last.
After your edit then the answer is clearly what #joran wrote, except that you would need first to convert to a DateTime class:
as.numeric(as.POSIXct(begin))
#[1] 984497460
The other point to make is that comparison operators do work for Date and DateTime classed variables, so the conversion may not be necessary at all. This compares 'begin' to a time one second later and correctly reports that begin is earlier:
as.POSIXct(begin) < as.POSIXct(begin) +1
#[1] TRUE
Based on the revised question this should do what you want:
begin <- "2001-03-13 10:31:00"
as.numeric(as.POSIXct(begin))
The result is a unix timestamp, the number of seconds since epoch, assuming the timestamp is in the local time zone.
Maybe this could also work:
library(lubridate)
...
df <- '24:00:00'
as.numeric(hms(df))
hms() will convert your data from one time format into another, this will let you convert it into seconds. See full documentation.
I tried this because i had trouble with data which was in that format but over 24 hours.
The example from ?as.POSIX help gives
as.POSIXct(strptime(begin, "%Y-%m-%d %H:%M:%S"))
so for you it would be
as.numeric(as.POSIXct(strptime(begin, "%Y-%m-%d %H:%M:%S")))