I'm trying to separate this date/time string in R but have not been successful.
Here is an example of the strings:
"Thu Sep 28 02:11:51 +0000 2017"
"Mon Oct 02 19:22:35 +0000 2017"
What is the best way to make this tidy? I've realized this is far beyond my skills.
Try something like this:
as.POSIXct(gsub("\\+0000", '', "Thu Sep 28 02:11:51 +0000 2017"), format = "%a %b %d %H:%M:%S %Y")
which gives "2017-09-28 02:11:51 EDT"
Related
How can I convert a string like "Fri Jul 26 10:58:25 CEST 2019" correctly to a date. The timezone are not the same every time.
as.Date("Fri Jul 26 10:58:25 CEST 2019", "%a %b %d %H:%M:%S CEST %Y")
What is the correct placeholder for the timezone (CEST, CET, ...)? Or how can I ignore the timezone? It is not important for my use case.
Maybe I'm confused by the question but if time zone isn't important then just omit it?
as.Date("Fri Jul 26 10:58:25 2019", "%a %b %d %H:%M:%S %Y")
Or if you need it clearly specified
as.Date("Fri Jul 26 10:58:25 2019", "%a %b %d %H:%M:%S %Y", tz = "CEST")
To remove the CEST using gsub:
as.Date(gsub("(:[[:digit:]][[:digit:]]) ([[:alpha:]]*)", "\\1", x), "%a %b %d %H:%M:%S %Y")
Currently, my dataset has a time variable (factor) in the following format:
weekday month day hour min seconds +0000 year
I don't know what the "+0000" field is but all observations have this. For example:
"Tues Feb 02 11:05:21 +0000 2018"
"Mon Jun 12 06:21:50 +0000 2017"
"Wed Aug 01 11:24:08 +0000 2018"
I want to convert these values to POSIXlt or POSIXct objects(year-month-day hour:min:sec) and make them numeric. Currently, using as.numeric(as.character(time-variable)) outputs incorrect values.
Thank you for the great responses! I really appreciate a lot.
Not sure how to reproduce the transition from factor to char, but starting from that this code should work:
t <- unlist(strsplit(as.character("Tues Feb 02 11:05:21 +0000 2018")," "))
strptime(paste(t[6],t[2],t[3], t[4]),format='%Y %b %d %H:%M:%S')
PS: More on date formats and conversion: https://www.stat.berkeley.edu/~s133/dates.html
For this problem you can get by without using lubridate. First, to extract individual dates we can use regmatches and gregexpr:
date_char <- 'Tue Feb 02 11:05:21 +0000 2018 Mon Jun 12 06:21:50 +0000 2017'
ptrn <- '([[:alpha:]]{3} [[:alpha:]]{3} [[:digit:]]{2} [[:digit:]]{2}\\:[[:digit:]]{2}\\:[[:digit:]]{2} \\+[[:digit:]]{4} [[:digit:]]{4})'
date_vec <- unlist( regmatches(date_char, gregexpr(ptrn, date_char)))
> date_vec
[1] "Tue Feb 02 11:05:21 +0000 2018" "Mon Jun 12 06:21:50 +0000 2017"
You can learn more about regular expressions here.
In the above example +0000 field is the UTC offset in hours e.g. it would be -0500 for EST timezone. To convert to R date-time object:
> as.POSIXct(date_vec, format = '%a %b %d %H:%M:%S %z %Y', tz = 'UTC')
[1] "2018-02-02 11:05:21 UTC" "2017-06-12 06:21:50 UTC"
which is the desired output. The formats can be found here or you can use lubridate::guess_formats(). If you don't specify the tz, you'll get the output in your system's time zone (e.g. for me that would be EST). Since the offset is specified in the format, R correctly carries out the conversion.
To get numeric values, the following works:
> as.numeric(as.POSIXct(date_vec, format = '%a %b %d %H:%M:%S %z %Y', tz = 'UTC'))
[1] 1517569521 1497248510
Note: this is based on uniform string structure. In the OP there was Tues instead of Tue which wouldn't work. The above example is based on the three-letter abbreviation which is the standard reporting format.
If however, your data is a mix of different formats, you'd have to extract individual time strings (customized regexes, of course), then use lubridate::guess_formats() to get the formats and then use those to carry out the conversion.
Hope this is helpful!!
I tried ISOdatetime() but it's not working.
error: argument "min" is missing, with no default
for example: Tue Jan 31 17:38:10 +0000 2017 -> 31/01/2017 or 31-01-2017
We can use strptime
format(strptime(str1, format = "%a %b %d %H:%M:%OS%z %Y"), "%d/%m/%Y")
#[1] "31/01/2017"
In a data.frame, I have a date time stamp in the form:
head(x$time)
[1] "Thu Oct 11 22:18:02 2012" "Thu Oct 11 22:50:15 2012" "Thu Oct 11 22:54:17 2012"
[4] "Thu Oct 11 22:43:13 2012" "Thu Oct 11 22:41:18 2012" "Thu Oct 11 22:15:19 2012"
Everytime I try to convert it with as.Date, lubridate, or zoo I get NAs or Errors.
What is the way to convert this time to a readable form?
I've tried:
Time<-strptime(x$time,format="&m/%d/%Y %H:$M")
x$minute<-parse_date_time(x$time)
x$minute<-mdy(x$time)
x$minute<-as.Date(x$time,"%m/%d/%Y %H:%M:%S")
x$minute<-as.time(x$time)
x$minute<-as.POSIXct(x$time,format="%H:%M")
x$minute<-minute(x$time)
What you really want is strptime(). Try something like:
strptime(x$time, "%a %b %d %H:%M:%S %Y")
As an example of the interesting things you can do with strptime(), consider the following:
thedate <- "I came to your house at 11:45 on January 21, 2012."
strptime(thedate, "I came to your house at %H:%M on %B %d, %Y.")
# [1] "2012-01-21 11:45:00"
Another option is to use lubridate::parse_date_time():
library(lubridate)
parse_date_time(x$time, "%a %b %d %H:%M:%S %Y")
Or more simply:
parse_date_time(x$time, "abdHMSY")
From the docs:
It differs from base::strptime() in two respects. First, it allows specification of the order in which the formats occur without the need to include separators and % prefix. Such a formating argument is refered to as "order". Second, it allows the user to specify several format-orders to handle heterogeneous date-time character representations.
The docs contain all the formats (the "abdHMSY" etc.) recognized by lubridate.
I have a spreadsheet full of data with dates that look like this:
Mon Jul 16 15:20:22 +0000 2012
Is there a way to convert these to R dates (preferably PST) without using regular expression or is there no other way? I'd appreciate ideas on doing this conversion efficiently.
Sure, just use strptime() to parse time from strings:
R> strptime("Mon Jul 16 15:20:22 +0000 2012",
+ format="%a %b %d %H:%M:%S %z %Y")
[1] "2012-07-16 10:20:22 CDT"
R>
which uses my local timezone (CDT). If yours is Pacific, you can set it explicitly as in
R> strptime("Mon Jul 16 15:20:22 +0000 2012",
+ format="%a %b %d %H:%M:%S %z %Y", tz="America/Los_Angeles")
[1] "2012-07-16 08:20:22 PDT"
R>
which looks right with a 7 hour delta to UTC.
There's nearly a verbatim example of how to do this in the Examples section of ?strptime:
# ?strptime example:
## An RFC 822 header (Eastern Canada, during DST)
strptime("Tue, 23 Mar 2010 14:36:38 -0400", "%a, %d %b %Y %H:%M:%S %z")
# your data...
strptime("Mon Jul 16 15:20:22 +0000 2012", "%a %b %d %H:%M:%S %z %Y")
This can also be done with lubridate package in tidyverse
library(lubridate)
parse_date_time("Mon Jul 16 15:20:22 +0000 2012", orders = "amdHMSzY")
which is what I prefer.