Hi Michael,
This is my problem. Could you find out how I can find the column name of
the zoo object "xzoo"? I am expecting "EUR".
Thanks,
Miao
> x<-read.csv("A_FX_EUR_Q.csv", header=TRUE)> x[1:4,] TIME EUR
1 198001 1.41112
2 198002 1.39108
3 198003 1.42323
4 198004 1.34205> xzoo<-zoo(x[,2:NCOL(x)],
seq(as.yearqtr(1980+(1-1)/4), as.yearqtr(2012+(2-1)/4), 1/4))>
xzoo[1:4,]1980 Q1 1980 Q2 1980 Q3 1980 Q4
1.41112 1.39108 1.42323 1.34205 > NCOL(xzoo)[1] 1> colnames(xzoo)NULL
2012/8/10 R. Michael Weylandt <michael.weyla...@gmail.com> <
michael.weyla...@gmail.com>
>
>
> On Aug 9, 2012, at 8:32 PM, jpm miao <miao...@gmail.com> wrote:
>
> > Hi everyone and Achim,
> >
> > Achim, I appreciate your help about the function "NCOL". When I use
> > "NCOL" instead of "ncol", I can find out the number of columns (number of
> > time series) in the presence of only one time series (one variable, one
> > column).
> >
> > Now I want to know how I can find out the column names of the zoo
> > objects? In case of more than one time series, the function "colnames"
> > works, but not for the univariate time series.
> >
>
> That's not true. zoo allows (but does not require) the data to have a dim
> attribute, as with any other vector. If (and I believe only if) an object
> has a dim attribute and hence can have colnames. For example, see xts which
> is a subclass of zoo requiring dim and for which colnames and names are
> equivalent.
>
> Michael
>
>
> > Thanks,
> >
> > Miao
> >
> > 2012/8/9 Achim Zeileis <achim.zeil...@uibk.ac.at>
> >
> >> On Thu, 9 Aug 2012, jpm miao wrote:
> >>
> >> Hi,
> >>>
> >>> Part of my program is to calculate the number of time series in a zoo
> >>> object. It works well if it has more than one time series, but it
> fails if
> >>> it has only one. How can I access the number of column (i.e. the
> number of
> >>> time series) when I have only one column? Why is the number of an
> object
> >>> of
> >>> only one object "NULL"? It should be one, shouldn't it? (The following
> >>> example does not involve the creation of a zoo object; in reality,
> similar
> >>> problems are encountered when I create a zoo object)
> >>>
> >>
> >> Univariate zoo series are by default vectors, i.e., have no "dim"
> >> attribute. You can either choose to store a matrix instead of a vector
> in
> >> the zoo series - or you can use NCOL() instead of ncol() to extract the
> >> number of columns. See the corresponding manual pages for more details.
> An
> >> illustration is included below:
> >>
> >> ## univariate series
> >>
> >> R> x <- sin(1:4)
> >> R> z <- zoo(x)
> >> R> z
> >> 1 2 3 4
> >> 0.8414710 0.9092974 0.1411200 -0.7568025
> >> R> dim(z)
> >> NULL
> >> R> ncol(z)
> >> NULL
> >> R> NCOL(z)
> >> [1] 1
> >>
> >> ## alternatives to create a 1-column matrix instead of a vector
> >>
> >> R> z1 <- zoo(matrix(x, ncol = 1))
> >> R> z1
> >>
> >> 1 0.8414710
> >> 2 0.9092974
> >> 3 0.1411200
> >> 4 -0.7568025
> >> R> dim(z1)
> >> [1] 4 1
> >>
> >> R> dim(z) <- c(NROW(z), NCOL(z))
> >> R> z
> >>
> >> 1 0.8414710
> >> 2 0.9092974
> >> 3 0.1411200
> >> 4 -0.7568025
> >> R> dim(z)
> >> [1] 4 1
> >>
> >>
> >> temp5<-read.csv("A_**Consumption.csv", header=TRUE)> temp5[1:3,] TIME
> >>>> C C_D C_ND
> >>>>
> >>> 1 196101 70345 1051 69294
> >>> 2 196102 61738 905 60833
> >>> 3 196103 63838 860 62978> temp6<-temp5[,2:ncol(temp5)]> temp6[1:3,]
> >>> C C_D C_ND
> >>> 1 70345 1051 69294
> >>> 2 61738 905 60833
> >>> 3 63838 860 62978> colnames(temp6)[1] "C" "C_D" "C_ND">
> >>> temp7<-read.csv("A_FX_EUR_Q.**csv", header=TRUE)> temp7[1:3,] TIME
> >>> EUR
> >>> 1 198001 1.41112
> >>> 2 198002 1.39108
> >>> 3 198003 1.42323> temp8<-temp7[,2:ncol(temp7)]> temp8[1:3,]Error in
> >>> temp8[1:3, ] : incorrect number of dimensions
> >>>
> >>> ncol(temp6)[1] 3> ncol(temp8) # Why isn't it 1?NULL
> >>>>
> >>>
> >>> temp8 [1] 1.411120 1.391080 1.423230 1.342050 1.232870
> >>>>
> >>> [6] 1.115090 1.032930 1.089250 1.036320 1.001850
> >>> [11] 0.950641 0.933593 0.947940 0.911204 0.860682
> >>> [16] 0.843864 0.831666 0.824776 0.768626 0.732064
> >>> [21] 0.684473 0.726018 0.784729 0.852911 0.922885
> >>> [26] 0.958778 1.012740 1.038160 1.124550 1.149780
> >>> [31] 1.128450 1.214120 1.233530 1.216270 1.113620
> >>> [36] 1.170250 1.126230 1.074330 1.078480 1.127870
> >>> [41] 1.205540 1.222740 1.296500 1.366550 1.341280
> >>> [46] 1.187600 1.176790 1.254490 1.262610 1.271820
> >>> [51] 1.385930 1.268130 1.190480 1.206840 1.150270
> >>> [56] 1.140010 1.125200 1.163450 1.226830 1.240210
> >>> [61] 1.273300 1.331010 1.312420 1.317350 1.287330
> >>> [66] 1.254500 1.274210 1.261930 1.178970 1.143500
> >>> [71] 1.093320 1.123400 1.086770 1.100380 1.117670
> >>> [76] 1.176960 1.121600 1.056900 1.048600 1.038000
> >>> [81] 0.986500 0.933200 0.905200 0.868300 0.923200
> >>> [86] 0.872500 0.890300 0.895900 0.876600 0.918800
> >>> [91] 0.983800 0.999400 1.073100 1.137200 1.124800
> >>> [96] 1.189000 1.249700 1.204600 1.222000 1.297700
> >>> [101] 1.311300 1.259400 1.219900 1.188400 1.202300
> >>> [106] 1.258200 1.274300 1.288700 1.310600 1.348100
> >>> [111] 1.373800 1.448600 1.497600 1.562200 1.505000
> >>> [116] 1.318000 1.302900 1.363200 1.430300 1.477900
> >>> [121] 1.382900 1.270800 1.291000 1.358300 1.368000
> >>> [126] 1.439100 1.412700 1.348200 1.310800 1.281400
> >>>
> >>> [[alternative HTML version deleted]]
> >>>
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