Re: [R] dates() is a great date function in R
Mr Natural <[EMAIL PROTECTED]> writes: Just save the spreadsheet as a csv file and use tisFromCsv() in the fame package. One of the arguments tisFromCsv() takes is a dateFormat, so you can tell it what format the date column is in. You can also tell it the name of the date column if it isn't some variation of DATE, Date, or date. tisFromCsv() looks at the dates coming in and automatically figures out what frequency the data are (quarterly, monthly, weekly, daily, etc.) and creates a univariate or multivariate (if the spreadsheet has more than one data column) 'tis' (Time Indexed Series) object. Jeff > Proper calendar dates in R are great for plotting and calculating. > However for the non-wonks among us, they can be very frustrating. > I have recently discussed the pains that people in my lab have had > with dates in R. Especially the frustration of bringing date data into R > from Excel, which we have to do a lot. > > Please find below a simple analgesic for R date importation that I > discovered > over the last 1.5 days (Learning new stuff in R is calculated in 1/2 days). > > The functiondates()gives the simplest way to get calendar dates into > R from Excel that I can find. > But straight importation of Excel dates, via a csv or txt file, can be a a > huge pain (I'll give details for anyone who cares to know). > > My pain killer is: > Consider that you have Excel columns in month, day, year format. Note that R > hates date data that does not lead with the year. > > a. Load the chron library by typing library(chron) in the console. > You know that you need this library from information revealed by > performing the query, > ?dates()"in the Console window. This gives the R documentation > help file for this and related time, date functions. In the upper left > of the documentation, one sees "dates(chron)". This tells you that you > need the library chron. > > b. Change the format "dates" in Excel to format "general", which gives > 5 digit Julian dates. Import the csv file (I useread.csv() with the > Julian dates and other data of interest. > > c. Now, change the Julian dates that came in with the csv file into > calendar dates with thedates() function. Below is my code for performing > this activity, concerning an R data file called ss, > > ss holds the Julian dates, illustrated below from the column MPdate, > > >ss$MPdate[1:5] > [1] 34252 34425 34547 34759 34773 > > The dates() function makes calendar dates from Julian dates, > > >dmp<-dates(ss$MPdate,origin=c(month = 1, day = 1, year = 1900)) > > > dmp[1:5] > [1] 10/12/93 04/03/94 08/03/94 03/03/95 03/17/95 > > I would appreciate the comments of more sophisticated programmers who > can suggest streamlining or shortcutting this operation. > > regards, Don > > > > > -- > View this message in context: > http://www.nabble.com/dates%28%29-is-a-great-date-function-in-R-tf4105322.html#a11675205 > Sent from the R help mailing list archive at Nabble.com. > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Jeff __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] dates() is a great date function in R
This is great.
I haven't seen "as.Date" function before, and was using "as.date" from
library(date).
(note the lowercase 'd')
I have an alternative which might or might not be faster...
If the date is formatted "mmdd" (e.g. 20070719)
library(date)
formatted <- gsub("^(\\d{4})(\\d{2})(\\d{2})$", "\\2-\\3-\\1", d$mmdd,
perl=TRUE)
d$dates <- as.date(formatted)
Since as.date only accepts certain type of date formats, I had to use gsub to
reshuffle the date substrings around.
as.Date returns the objects of class "Date", whereas as.date returns the
objects of class "date".
Not sure what the differences are, but a simple test below shows that as.date
conversion is
slightly faster, given a character vector of 1 date entries.
FYI,
I ran a quick performance comparison test on a 64bit linux machine on 2.6.9
kernel.
The test is very rudimentary, but hopefully useful...
I have two scripts:
## as.date_test.R
##
library(date)
d <- read.table("/tmp/dates", as.is = TRUE, col.names = c("mmdd"),
colClasses = c("character"))
formatted <- gsub("^(\\d{4})(\\d{2})(\\d{2})$", "\\2-\\3-\\1", d$mmdd,
perl=TRUE)
d$dates <- as.date(formatted)
print(nrow(d))
print(d$dates[1:3])
##
## as.Date_test.R
##
d <- read.table("/tmp/dates", as.is = TRUE, col.names = c("mmdd"),
colClasses = c("character"))
d$dates <- as.Date(d$mmdd, format = "%Y%m%d")
print(nrow(d))
print(d$dates[1:3])
##
Both scripts read in the same text file containing 1 date strings, and then
convert them into
appropriate date objects.
# 1 date records in a flat file
<[EMAIL PROTECTED]>$ wc -l /tmp/dates
1 /tmp/dates
# just to illustrate what the dates look like
<[EMAIL PROTECTED]>$ head -2 /tmp/dates
19900817
19900820
# Running the test script 5 times each
<[EMAIL PROTECTED]>$ for i in 1 2 3 4 5; do time R --vanilla < as.date_test.R >
/dev/null; done
real0m1.29s
user0m1.23s
sys 0m0.05s
real0m1.28s
user0m1.23s
sys 0m0.06s
real0m1.28s
user0m1.22s
sys 0m0.06s
real0m1.29s
user0m1.22s
sys 0m0.06s
real0m1.28s
user0m1.21s
sys 0m0.07s
<[EMAIL PROTECTED]>$ for i in 1 2 3 4 5; do time R --vanilla < as.Date_test.R >
/dev/null; done
real0m1.65s
user0m0.99s
sys 0m0.64s
real0m1.64s
user0m0.98s
sys 0m0.66s
real0m1.63s
user0m0.98s
sys 0m0.65s
real0m1.64s
user0m1.00s
sys 0m0.64s
real0m1.64s
user0m0.98s
sys 0m0.65s
Notice that as.date conversion is silghtly faster than as.Date conversion, on
average...
Just thought it was interesting to share.
(and thanks Mark Leeds for reference)
Regards,
JB
On 07/18/07 16:13:49, Gavin Simpson wrote:
> On Wed, 2007-07-18 at 12:14 -0700, Mr Natural wrote:
> > Proper calendar dates in R are great for plotting and calculating.
> > However for the non-wonks among us, they can be very frustrating.
> > I have recently discussed the pains that people in my lab have had
> > with dates in R. Especially the frustration of bringing date data into R
> > from Excel, which we have to do a lot.
>
> I've always found the following reasonably intuitive:
>
> Given the csv file that I've pasted in below, the following reads the
> csv file in, formats the dates and class Date and then draws a plot.
>
> I have dates in DD/MM/ format so year is not first - thus attesting
> to R not hating dates in this format ;-)
>
> ## read in csv data
> ## as.is = TRUE stops characters being converted to factors
> ## thus saving us an extra step to convert them back
> dat <- read.csv("date_data.csv", as.is = TRUE)
>
> ## we convert to class Date
> ## format tells R how the dates are formatted in our character strings
> ## see ?strftime for the meaning and available codes
> dat$Date <- as.Date(dat$Date, format = "%d/%m/%Y")
>
> ## check this worked ok
> str(dat$Date)
> dat$Date
>
> ## see nicely formatted dates and not a drop of R-related hatred
> ## but just about the most boring graph I could come up with
> plot(Data ~ Date, dat, type = "l")
>
> And you can keep your Excel file formatted as dates as well - bonus!
>
> Oh, and before you get "Martin'd", it is the chron *package*!
>
> HTH
>
> G
>
> CSV file I used, generated in OpenOffice.org, but I presume it stores
> Dates in the same way as Excel?:
>
> "Data","Date"
> 1,01/01/2007
> 2,02/01/2007
> 3,03/01/2007
> 4,04/01/2007
> 5,05/01/2007
> 6,06/01/2007
> 7,07/01/2007
> 8,08/01/2007
> 9,09/01/2007
> 10,10/01/2007
> 11,11/01/2007
> 10,12/01/2007
> 9,13/01/2007
> 8,14/01/2007
> 7,15/01/2007
> 6,16/01/2007
> 5,17/01/2007
> 4,18/01/
Re: [R] dates() is a great date function in R
...just a follow up to reading time series data from CSV files. If you've
got data like Gavin's (only with the dates in the first column)
Date,Data
01/01/2007,1
02/01/2007,2
03/01/2007,3
04/01/2007,4
...
then you can use read.zoo() in package "zoo":
x <- read.zoo("mydata.csv", sep = ",", format = "%d/%m/%Y", header = TRUE)
plot(x)
which produces the time-series plot.
This uses the "Date" class contained in base R rather than "dates" from
chron. Concerning the different time/date classes, see the R News article
Gabor already mentioned. For some more examples of using zoo/read.zoo see
vignette("zoo-quickref", package = "zoo")
hth,
Z
On Wed, 18 Jul 2007, Gavin Simpson wrote:
> On Wed, 2007-07-18 at 12:14 -0700, Mr Natural wrote:
> > Proper calendar dates in R are great for plotting and calculating.
> > However for the non-wonks among us, they can be very frustrating.
> > I have recently discussed the pains that people in my lab have had
> > with dates in R. Especially the frustration of bringing date data into R
> > from Excel, which we have to do a lot.
>
> I've always found the following reasonably intuitive:
>
> Given the csv file that I've pasted in below, the following reads the
> csv file in, formats the dates and class Date and then draws a plot.
>
> I have dates in DD/MM/ format so year is not first - thus attesting
> to R not hating dates in this format ;-)
>
> ## read in csv data
> ## as.is = TRUE stops characters being converted to factors
> ## thus saving us an extra step to convert them back
> dat <- read.csv("date_data.csv", as.is = TRUE)
>
> ## we convert to class Date
> ## format tells R how the dates are formatted in our character strings
> ## see ?strftime for the meaning and available codes
> dat$Date <- as.Date(dat$Date, format = "%d/%m/%Y")
>
> ## check this worked ok
> str(dat$Date)
> dat$Date
>
> ## see nicely formatted dates and not a drop of R-related hatred
> ## but just about the most boring graph I could come up with
> plot(Data ~ Date, dat, type = "l")
>
> And you can keep your Excel file formatted as dates as well - bonus!
>
> Oh, and before you get "Martin'd", it is the chron *package*!
>
> HTH
>
> G
>
> CSV file I used, generated in OpenOffice.org, but I presume it stores
> Dates in the same way as Excel?:
>
> "Data","Date"
> 1,01/01/2007
> 2,02/01/2007
> 3,03/01/2007
> 4,04/01/2007
> 5,05/01/2007
> 6,06/01/2007
> 7,07/01/2007
> 8,08/01/2007
> 9,09/01/2007
> 10,10/01/2007
> 11,11/01/2007
> 10,12/01/2007
> 9,13/01/2007
> 8,14/01/2007
> 7,15/01/2007
> 6,16/01/2007
> 5,17/01/2007
> 4,18/01/2007
> 3,19/01/2007
> 2,20/01/2007
> 1,21/01/2007
> 1,22/01/2007
> 2,23/01/2007
> 3,24/01/2007
>
> > Please find below a simple analgesic for R date importation that I
> > discovered
> > over the last 1.5 days (Learning new stuff in R is calculated in 1/2 days).
> >
> > The functiondates()gives the simplest way to get calendar dates into
> > R from Excel that I can find.
> > But straight importation of Excel dates, via a csv or txt file, can be a a
> > huge pain (I'll give details for anyone who cares to know).
> >
> > My pain killer is:
> > Consider that you have Excel columns in month, day, year format. Note that R
> > hates date data that does not lead with the year.
> >
> > a. Load the chron library by typing library(chron) in the console.
> > You know that you need this library from information revealed by
> > performing the query,
> > ?dates()"in the Console window. This gives the R documentation
> > help file for this and related time, date functions. In the upper left
> > of the documentation, one sees "dates(chron)". This tells you that you
> > need the library chron.
> >
> > b. Change the format "dates" in Excel to format "general", which gives
> > 5 digit Julian dates. Import the csv file (I useread.csv() with the
> > Julian dates and other data of interest.
> >
> > c. Now, change the Julian dates that came in with the csv file into
> > calendar dates with thedates() function. Below is my code for performing
> > this activity, concerning an R data file called ss,
> >
> > ss holds the Julian dates, illustrated below from the column MPdate,
> >
> > >ss$MPdate[1:5]
> > [1] 34252 34425 34547 34759 34773
> >
> > The dates() function makes calendar dates from Julian dates,
> >
> > >dmp<-dates(ss$MPdate,origin=c(month = 1, day = 1, year = 1900))
> >
> > > dmp[1:5]
> > [1] 10/12/93 04/03/94 08/03/94 03/03/95 03/17/95
> >
> > I would appreciate the comments of more sophisticated programmers who
> > can suggest streamlining or shortcutting this operation.
> >
> > regards, Don
> >
> >
> >
> >
> --
> %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> Gavin Simpson [t] +44 (0)20 7679 0522
> ECRC, UCL Geography, [f] +44 (0)20 7679 0565
> Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/
> UK. WC1E 6BT.
Re: [R] dates() is a great date function in R
On Wed, 2007-07-18 at 12:14 -0700, Mr Natural wrote:
> Proper calendar dates in R are great for plotting and calculating.
> However for the non-wonks among us, they can be very frustrating.
> I have recently discussed the pains that people in my lab have had
> with dates in R. Especially the frustration of bringing date data into R
> from Excel, which we have to do a lot.
I've always found the following reasonably intuitive:
Given the csv file that I've pasted in below, the following reads the
csv file in, formats the dates and class Date and then draws a plot.
I have dates in DD/MM/ format so year is not first - thus attesting
to R not hating dates in this format ;-)
## read in csv data
## as.is = TRUE stops characters being converted to factors
## thus saving us an extra step to convert them back
dat <- read.csv("date_data.csv", as.is = TRUE)
## we convert to class Date
## format tells R how the dates are formatted in our character strings
## see ?strftime for the meaning and available codes
dat$Date <- as.Date(dat$Date, format = "%d/%m/%Y")
## check this worked ok
str(dat$Date)
dat$Date
## see nicely formatted dates and not a drop of R-related hatred
## but just about the most boring graph I could come up with
plot(Data ~ Date, dat, type = "l")
And you can keep your Excel file formatted as dates as well - bonus!
Oh, and before you get "Martin'd", it is the chron *package*!
HTH
G
CSV file I used, generated in OpenOffice.org, but I presume it stores
Dates in the same way as Excel?:
"Data","Date"
1,01/01/2007
2,02/01/2007
3,03/01/2007
4,04/01/2007
5,05/01/2007
6,06/01/2007
7,07/01/2007
8,08/01/2007
9,09/01/2007
10,10/01/2007
11,11/01/2007
10,12/01/2007
9,13/01/2007
8,14/01/2007
7,15/01/2007
6,16/01/2007
5,17/01/2007
4,18/01/2007
3,19/01/2007
2,20/01/2007
1,21/01/2007
1,22/01/2007
2,23/01/2007
3,24/01/2007
> Please find below a simple analgesic for R date importation that I
> discovered
> over the last 1.5 days (Learning new stuff in R is calculated in 1/2 days).
>
> The functiondates()gives the simplest way to get calendar dates into
> R from Excel that I can find.
> But straight importation of Excel dates, via a csv or txt file, can be a a
> huge pain (I'll give details for anyone who cares to know).
>
> My pain killer is:
> Consider that you have Excel columns in month, day, year format. Note that R
> hates date data that does not lead with the year.
>
> a. Load the chron library by typing library(chron) in the console.
> You know that you need this library from information revealed by
> performing the query,
> ?dates()"in the Console window. This gives the R documentation
> help file for this and related time, date functions. In the upper left
> of the documentation, one sees "dates(chron)". This tells you that you
> need the library chron.
>
> b. Change the format "dates" in Excel to format "general", which gives
> 5 digit Julian dates. Import the csv file (I useread.csv() with the
> Julian dates and other data of interest.
>
> c. Now, change the Julian dates that came in with the csv file into
> calendar dates with thedates() function. Below is my code for performing
> this activity, concerning an R data file called ss,
>
> ss holds the Julian dates, illustrated below from the column MPdate,
>
> >ss$MPdate[1:5]
> [1] 34252 34425 34547 34759 34773
>
> The dates() function makes calendar dates from Julian dates,
>
> >dmp<-dates(ss$MPdate,origin=c(month = 1, day = 1, year = 1900))
>
> > dmp[1:5]
> [1] 10/12/93 04/03/94 08/03/94 03/03/95 03/17/95
>
> I would appreciate the comments of more sophisticated programmers who
> can suggest streamlining or shortcutting this operation.
>
> regards, Don
>
>
>
>
--
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
Gavin Simpson [t] +44 (0)20 7679 0522
ECRC, UCL Geography, [f] +44 (0)20 7679 0565
Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/
UK. WC1E 6BT. [w] http://www.freshwaters.org.uk
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] dates() is a great date function in R
See the Other Applications section of the R News 4/1 help desk article on dates. On 7/18/07, Mr Natural <[EMAIL PROTECTED]> wrote: > > Proper calendar dates in R are great for plotting and calculating. > However for the non-wonks among us, they can be very frustrating. > I have recently discussed the pains that people in my lab have had > with dates in R. Especially the frustration of bringing date data into R > from Excel, which we have to do a lot. > > Please find below a simple analgesic for R date importation that I > discovered > over the last 1.5 days (Learning new stuff in R is calculated in 1/2 days). > > The functiondates()gives the simplest way to get calendar dates into > R from Excel that I can find. > But straight importation of Excel dates, via a csv or txt file, can be a a > huge pain (I'll give details for anyone who cares to know). > > My pain killer is: > Consider that you have Excel columns in month, day, year format. Note that R > hates date data that does not lead with the year. > > a. Load the chron library by typing library(chron) in the console. > You know that you need this library from information revealed by > performing the query, > ?dates()"in the Console window. This gives the R documentation > help file for this and related time, date functions. In the upper left > of the documentation, one sees "dates(chron)". This tells you that you > need the library chron. > > b. Change the format "dates" in Excel to format "general", which gives > 5 digit Julian dates. Import the csv file (I useread.csv() with the > Julian dates and other data of interest. > > c. Now, change the Julian dates that came in with the csv file into > calendar dates with thedates() function. Below is my code for performing > this activity, concerning an R data file called ss, > > ss holds the Julian dates, illustrated below from the column MPdate, > > >ss$MPdate[1:5] > [1] 34252 34425 34547 34759 34773 > > The dates() function makes calendar dates from Julian dates, > > >dmp<-dates(ss$MPdate,origin=c(month = 1, day = 1, year = 1900)) > > > dmp[1:5] > [1] 10/12/93 04/03/94 08/03/94 03/03/95 03/17/95 > > I would appreciate the comments of more sophisticated programmers who > can suggest streamlining or shortcutting this operation. > > regards, Don > > > > > -- > View this message in context: > http://www.nabble.com/dates%28%29-is-a-great-date-function-in-R-tf4105322.html#a11675205 > Sent from the R help mailing list archive at Nabble.com. > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] dates() is a great date function in R
Proper calendar dates in R are great for plotting and calculating. However for the non-wonks among us, they can be very frustrating. I have recently discussed the pains that people in my lab have had with dates in R. Especially the frustration of bringing date data into R from Excel, which we have to do a lot. Please find below a simple analgesic for R date importation that I discovered over the last 1.5 days (Learning new stuff in R is calculated in 1/2 days). The functiondates()gives the simplest way to get calendar dates into R from Excel that I can find. But straight importation of Excel dates, via a csv or txt file, can be a a huge pain (I'll give details for anyone who cares to know). My pain killer is: Consider that you have Excel columns in month, day, year format. Note that R hates date data that does not lead with the year. a. Load the chron library by typing library(chron) in the console. You know that you need this library from information revealed by performing the query, ?dates()"in the Console window. This gives the R documentation help file for this and related time, date functions. In the upper left of the documentation, one sees "dates(chron)". This tells you that you need the library chron. b. Change the format "dates" in Excel to format "general", which gives 5 digit Julian dates. Import the csv file (I useread.csv() with the Julian dates and other data of interest. c. Now, change the Julian dates that came in with the csv file into calendar dates with thedates() function. Below is my code for performing this activity, concerning an R data file called ss, ss holds the Julian dates, illustrated below from the column MPdate, >ss$MPdate[1:5] [1] 34252 34425 34547 34759 34773 The dates() function makes calendar dates from Julian dates, >dmp<-dates(ss$MPdate,origin=c(month = 1, day = 1, year = 1900)) > dmp[1:5] [1] 10/12/93 04/03/94 08/03/94 03/03/95 03/17/95 I would appreciate the comments of more sophisticated programmers who can suggest streamlining or shortcutting this operation. regards, Don -- View this message in context: http://www.nabble.com/dates%28%29-is-a-great-date-function-in-R-tf4105322.html#a11675205 Sent from the R help mailing list archive at Nabble.com. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
