Zoo Time-series - extend x-axis in plot

Question

I created a time-series with zoo (following suggestions in another question that ts() is not good for daily time-series). I would like to extend the x-axis beyond the dates from my zoo object (in order to overlay a second time-series - neither "add=T" nor points() seem to work for zoo plots). I need to overlay (par(new=T)) the second time-series because the two have different scales. However, if I try to adjust xlim, it plots the axes, but not the actual data.

2017.ts<-read.zoo(2017.day, format = "%Y-%m-%d")

2017.ts
            norm_mean
2017-01-27    7.500000
2017-01-31    13.666667
2017-02-08    12.833333
2017-02-15    14.000000
2017-02-17    18.200000
2017-02-23    10.833333
2017-03-03    11.000000
2017-03-06    13.333333
2017-03-07    14.833333
2017-03-08    18.000000
2017-03-09    10.600000
2017-03-10    5.666667
2017-03-16    17.000000
2017-03-20    10.500000
2017-03-29    5.000000
2017-03-30    2.000000
2017-03-31    2.166667
2017-04-04    2.666667
2017-04-11    3.750000

plot(2017.ts, type="h", lwd=5, lend=1, col="grey", xlab="Date")
plot(2017.ts, type="h", lwd=5, lend=1, col="grey", xlab="Date",xlim=as.Date(c("01-01-2017", "01-05-2017")) )

Edit to include data for the second ts.

z2

        v2 
2017-01-04 108.65521 
2017-01-05 109.13615 
2017-01-06 108.78080 
2017-01-07 108.27312 
2017-01-08 109.09156 
2017-01-09 108.13882 
2017-01-10 108.79868 
2017-01-11 109.08090 
2017-01-12 110.09045 
2017-01-13 108.89611 
2017-01-14 111.21378 
2017-01-15 111.70625 
2017-01-16 113.30840 
2017-01-17 112.95767 
2017-01-18 110.57698 
2017-01-19 111.67750 
2017-01-20 112.11809 
2017-01-21 112.36285 
2017-01-22 111.72885 
2017-01-23 111.56948 
2017-01-24 113.18226 
2017-01-25 114.50997 
2017-01-26 112.59635 
2017-01-27 112.89517
2017-01-28 113.85590 
2017-01-29 113.66267 
2017-01-30 113.27187
2017-01-31 114.49236 
2017-02-01 113.46934 
2017-02-02 116.58854 
2017-02-03 114.50764 
2017-02-04 115.47986 
2017-02-05 115.34931 
2017-02-06 115.43250 
2017-02-07 114.70101 
2017-02-08 113.19042 
2017-02-09 115.53726 
2017-02-10 115.05983 
2017-02-11 115.34476 
2017-02-12 115.49007 
2017-02-13 114.96326 
2017-02-14 115.37941 
2017-02-15 115.40066 
2017-02-16 116.49903
2017-02-17 115.05514 
2017-02-18 115.72139 
2017-02-19 116.44944 
2017-02-20 116.38858 
2017-02-21 116.52819 
2017-02-22 116.13941 
2017-02-23 114.54677 
2017-02-24 115.84712 
2017-02-25 116.91059 
2017-02-26 115.72712 
2017-02-27 116.68500 
2017-02-28 117.56170 
2017-03-01 117.17802 
2017-03-02 115.96913 
2017-03-03 116.71031 
2017-03-04 116.30385 
2017-03-05 115.48656 
2017-03-06 115.64056 
2017-03-07 116.25858 
2017-03-08 115.88340 
2017-03-09 114.34972 
2017-03-10 114.59559 
2017-03-11 115.07535 
2017-03-12 115.34625 
2017-03-13 114.80948 
2017-03-14 115.02052  
2017-03-15 114.85764 

xlim<-range(c(time(2017.ts), time(z2)))
plot(2017.ts, type = "h", lwd = 1, col = "blue", xlim = xlim)

However,

points(z2,col="red")

does nothing.

Answer 1

Normally one does this by merging the two series together and plotting them all at once. Using the data in the Note at the end we have the following code. (screens = 1 will use a single panel rather than plotting each in a separate panel.)

z <- merge(z1, z2)
plot(z, type = "h", col = c("blue", adjustcolor("red", .4)), screens = 1)

giving (continued after figure):

Although not recommended due to the unnecessary extra code, if you really want to do it in two steps then:

xlim <- range(c(time(z1), time(z2)))
ylim <- range(c(coredata(z1), coredata(z2)))
plot(z1, type = "h", col = "blue", xlim = xlim, ylim = ylim)
points(z2, type = "h", col = adjustcolor("red", .4))

giving (continued after figure):

Note

Lines <- "
2017-01-27    7.500000
2017-01-31    13.666667
2017-02-08    12.833333
2017-02-15    14.000000
2017-02-17    18.200000
2017-02-23    10.833333
2017-03-03    11.000000
2017-03-06    13.333333
2017-03-07    14.833333
2017-03-08    18.000000
2017-03-09    10.600000
2017-03-10    5.666667
2017-03-16    17.000000
2017-03-20    10.500000
2017-03-29    5.000000
2017-03-30    2.000000
2017-03-31    2.166667
2017-04-04    2.666667
2017-04-11    3.750000"

Lines2 <- "
2017-01-04 108.65521 
2017-01-05 109.13615 
2017-01-06 108.78080 
2017-01-07 108.27312 
2017-01-08 109.09156 
2017-01-09 108.13882 
2017-01-10 108.79868 
2017-01-11 109.08090 
2017-01-12 110.09045 
2017-01-13 108.89611 
2017-01-14 111.21378 
2017-01-15 111.70625 
2017-01-16 113.30840 
2017-01-17 112.95767 
2017-01-18 110.57698 
2017-01-19 111.67750 
2017-01-20 112.11809 
2017-01-21 112.36285 
2017-01-22 111.72885 
2017-01-23 111.56948 
2017-01-24 113.18226 
2017-01-25 114.50997 
2017-01-26 112.59635 
2017-01-27 112.89517
2017-01-28 113.85590 
2017-01-29 113.66267 
2017-01-30 113.27187
2017-01-31 114.49236 
2017-02-01 113.46934 
2017-02-02 116.58854 
2017-02-03 114.50764 
2017-02-04 115.47986 
2017-02-05 115.34931 
2017-02-06 115.43250 
2017-02-07 114.70101 
2017-02-08 113.19042 
2017-02-09 115.53726 
2017-02-10 115.05983 
2017-02-11 115.34476 
2017-02-12 115.49007 
2017-02-13 114.96326 
2017-02-14 115.37941 
2017-02-15 115.40066 
2017-02-16 116.49903
2017-02-17 115.05514 
2017-02-18 115.72139 
2017-02-19 116.44944 
2017-02-20 116.38858 
2017-02-21 116.52819 
2017-02-22 116.13941 
2017-02-23 114.54677 
2017-02-24 115.84712 
2017-02-25 116.91059 
2017-02-26 115.72712 
2017-02-27 116.68500 
2017-02-28 117.56170 
2017-03-01 117.17802 
2017-03-02 115.96913 
2017-03-03 116.71031 
2017-03-04 116.30385 
2017-03-05 115.48656 
2017-03-06 115.64056 
2017-03-07 116.25858 
2017-03-08 115.88340 
2017-03-09 114.34972 
2017-03-10 114.59559 
2017-03-11 115.07535 
2017-03-12 115.34625 
2017-03-13 114.80948 
2017-03-14 115.02052  
2017-03-15 114.85764"

library(zoo)
z1 <- read.zoo(text = Lines)
z2 <- read.zoo(text = Lines2)