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Asked: 2026-05-25T11:03:00+00:00

Suppose I have: R> str(data) ‘data.frame’: 4 obs. of 2 variables: $ datetime: Factor

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Suppose I have:

R> str(data)
'data.frame':   4 obs. of  2 variables:
 $ datetime: Factor w/ 4 levels "2011-01-05 09:30:00.001",..: 1 2 3 4
 $ price   : num  18.3 18.3 18.3 18.3

R> data
                 datetime price
1 2011-01-05 09:30:00.001 18.31
2 2011-01-05 09:30:00.321 18.33
3 2011-01-05 09:30:01.511 18.33
4 2011-01-05 09:30:02.192 18.34

When I try to load this into an xts object the timestamps are subtly altered:

R> x <- xts(data[-1], as.POSIXct(strptime(data$datetime, '%Y-%m-%d %H:%M:%OS')))
R> str(x)
An ‘xts’ object from 2011-01-05 09:30:00.000 to 2011-01-05 09:30:02.191 containing:
  Data: num [1:4, 1] 18.3 18.3 18.3 18.3
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr "price"
  Indexed by objects of class: [POSIXct,POSIXt] TZ: 
  xts Attributes:  
 NULL

 R> x
                         price
 2011-01-05 09:30:00.000 18.31
 2011-01-05 09:30:00.321 18.33
 2011-01-05 09:30:01.510 18.33
 2011-01-05 09:30:02.191 18.34

You’ll notice that the timestamps have been altered. The first entry now occurs at 09:30:00.000 instead of what the original data said, 09:30:00.001. The third and fourth rows are also incorrect.

What’s causing this? Am I doing something fundamentally wrong? I’ve tried various incantations to get the data into an xts object and they all seem to exhibit this behavior.

EDIT: Add sessionInfo()

R> sessionInfo()
R version 2.13.1 (2011-07-08)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=C               LC_MONETARY=C              LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] xts_0.8-2 zoo_1.7-4

loaded via a namespace (and not attached):
[1] grid_2.13.1     lattice_0.19-30 tools_2.13.1

EDIT 2: If I modify my source data to be microsecond precision as follows:

datetime,price
2011-01-05 09:30:00.001000,18.31
2011-01-05 09:30:00.321000,18.33
2011-01-05 09:30:01.511000,18.33
2011-01-05 09:30:02.192000,18.34

And then load it so I have:

R> test
                    datetime price
1 2011-01-05 09:30:00.001000 18.31
2 2011-01-05 09:30:00.321000 18.33
3 2011-01-05 09:30:01.511000 18.33
4 2011-01-05 09:30:02.192000 18.34

And then, finally, convert it into an xts object and set the index format:

R> x <- xts(test[,-1], as.POSIXct(strptime(test$datetime, '%Y-%m-%d %H:%M:%OS')))
R> indexFormat(x) <- '%Y-%m-%d %H:%M:%OS6'
R> x
                            [,1]
2011-01-05 09:30:00.000999 18.31
2011-01-05 09:30:00.321000 18.33
2011-01-05 09:30:01.510999 18.33
2011-01-05 09:30:02.191999 18.34

You can see the effect as well. I was hoping that adding the extra precision would help, but unfortunately it does not.

EDIT 3: Please see @DWin’s answer for an end-to-end test case that reproduces this behavior.

EDIT 4: The behavior does not appear to be millisecond oriented. The following shows the same altered result of a microsecond resolution timestamp. If I change my input data to:

R> data
                    datetime price
1 2011-01-05 09:30:00.001001 18.31
2 2011-01-05 09:30:00.321001 18.33
3 2011-01-05 09:30:01.511001 18.33
4 2011-01-05 09:30:02.192005 18.34

And then create an xts object:

R> x <- xts(data[-1], 
            as.POSIXct(strptime(as.character(data$datetime), '%Y-%m-%d %H:%M:%OS')))
R> indexFormat(x) <- '%Y-%m-%d %H:%M:%OS6'
R> x
                           price
2011-01-05 09:30:00.001000 18.31
2011-01-05 09:30:00.321001 18.33
2011-01-05 09:30:01.511001 18.33
2011-01-05 09:30:02.192004 18.34

EDIT 5: It would appear to be a floating point precision issue. Observe:

R> t <- as.POSIXct("2011-01-05 09:30:00.001001")
R> t
[1] "2011-01-05 09:30:00.001 CST"
R> as.numeric(t)
[1] 1294241400.0010008812

This exhibits the error behavior, and is consistent with the example in EDIT 4. However, using an example that didn’t show the error:

R> t <- as.POSIXct("2011-01-05 09:30:01.511001")
R> t
[1] "2011-01-05 09:30:01.511001 CST"
R> as.numeric(t)
[1] 1294241401.5110011101

It seems as if xts or some underlying component is rounding down rather than to the nearest?

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1 Answer

  1. Editorial Team

    It seems the problem is only in printing. Using the OP’s original data:

    ind <- as.POSIXct(strptime(data$datetime, '%Y-%m-%d %H:%M:%OS'))
as.numeric(ind)*1e6  # as expected
# [1] 1294241400001000 1294241400321000 1294241401511000 1294241402192000
ind  # wrong
# [1] "2011-01-05 09:30:00.000 CST" "2011-01-05 09:30:00.321 CST"
# [3] "2011-01-05 09:30:01.510 CST" "2011-01-05 09:30:02.191 CST"
x <- xts(data[-1], ind)
x  # wrong
#                         price
# 2011-01-05 09:30:00.000 18.31
# 2011-01-05 09:30:00.321 18.33
# 2011-01-05 09:30:01.510 18.33
# 2011-01-05 09:30:02.191 18.34
as.numeric(index(x))*1e6  # but the underlying index values are as expected
# [1] 1294241400001000 1294241400321000 1294241401511000 1294241402192000
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