[R studio] Plotting of line chart for each columns at 1 page

Thank you very much sir. Actually, I excluded all the non-trading days.
Therefore, Each year will have 226 observations and total 6154 observations
for each column. The data which I plotted is not rough data. I obtained the
rolling observations of window 500 from my original data. So, the no. of
observations for each resulted column is (6154-500)+1=5655. So, It is not
accurate as per the days of calculations of each year.

Ok, Sir, I will go through your suggestion, obtain the results for each
column of my data and would like to discuss the results with you. After
solving of this problem, I would like to discuss another 2 queries.

Thank you very much Sir for educating a new R learner.

[image: Mailtrack]
<https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=signaturevirality5&> Sender
notified by
Mailtrack
<https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=signaturevirality5&> 12/16/18,
12:20:17 PM

On Sun, Dec 16, 2018 at 8:10 AM Jim Lemon <drjimlemon at gmail.com> wrote:

Hi Subhamitra,
Thanks. Now I can provide some assistance instead of just complaining.
Your first problem is the temporal extent of the data. There are 8613 days
and 6512 weekdays between the two dates you list, but only 5655
observations in your data. Therefore it is unlikely that you have a
complete data series, or perhaps you have the wrong dates. For the moment
I'll assume that there are missing observations. What I am going to do is
to match the 24 years (1994-2017) to their approximate positions in the
time series. This will give you the x-axis labels that you want, close
enough for this illustration. I doubt that you will need anything more
accurate. You have a span of 24.58 years, which means that if your missing
observations are uniformly distributed, you will have almost exactly 226
observations per year. When i tried this, I got too many intervals, so I
increased the increment to 229 and that worked. To get the positions for
the middle of each year in the indices of the data:

year_mids<-seq(182,5655,by=229)

Now I suppress the x-axis by adding xaxt="n" to each call to plot. Then I
add a command to display the years at the positions I have calculated:

axis(1,at=year_mids,labels=1994:2017)

Also note that I have added braces to the "for" loop. Putting it all
together:

year_mids<-seq(182,5655,by=229)
pdf("EMs.pdf",width=20,height=20)
par(mfrow=c(5,4))
# import your first sheet here (16 columns)
EMs1.1<-read.csv("EMs1.1.csv")
ncolumns<-ncol(EMs1.1)
for(i in 1:ncolumns) {
  plot(EMs1.1[,i],type="l",col = "Red", xlab="Time",
       ylab="APEn", main=names(EMs1.1)[i],xaxt="n")
 axis(1,at=year_mids,labels=1994:2017)
}
#import your second sheet here, (1 column)
EMs2.1<-read.csv("EMs2.1.csv")
ncolumns<-ncol(EMs2.1)
for(i in 1:ncolumns) {
  plot(EMs2.1[,i],type="l",col = "Red", xlab="Time",
       ylab="APEn", main=names(EMs2.1)[i],xaxt="n")
 axis(1,at=year_mids,labels=1994:2017)
}
# import your Third sheet here, (1 column)
EMs3.1<-read.csv("EMs3.1.csv")
ncolumns<-ncol(EMs3.1)
for(i in 1:ncolumns) {
  plot(EMs3.1[,i],type="l",col = "Red", xlab="Time",
       ylab="APEn", main=names(EMs3.1)[i],xaxt="n")
 axis(1,at=year_mids,labels=1994:2017)
}
# import your fourth sheet here, (1 column)
EMs4.1<-read.csv("EMs4.1.csv")
ncolumns<-ncol(EMs4.1)
for(i in 1:ncolumns) {
  plot(EMs4.1[,i],type="l",col = "Red", xlab="Time",
       ylab="APEn", main=names(EMs4.1)[i],xaxt="n")
 axis(1,at=year_mids,labels=1994:2017)
}
# finish plotting
dev.off()

With any luck, you are now okay. Remember, this is a hack to deal with
data that are not what you think they are.

Jim

--
*Best Regards,*
*Subhamitra Patra*
*Phd. Research Scholar*
*Department of Humanities and Social Sciences*
*Indian Institute of Technology, Kharagpur*
*INDIA*