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)
> 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
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