Hi
I have a daily level time series data. What I need to do is a time series
analysis and forecasting and stuff.
But the thing I am stuck at is - I cant get a decent time series plot of the
data I have
http://r.789695.n4.nabble.com/file/n3021952/test.jpg
This is a plot of daily level data from July 09 to Oct 10. what I am
interested is in - like instead of just 2010 time stamp on x axis, if I
could have monthly tags it would be great.
Here is what I have done -
MY DATA IS OF THIS FORMAT
Date X Y Z A B C
D E F G
7/1/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/2/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/3/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/4/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/5/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/6/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/7/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/8/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/9/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/10/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/11/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/12/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/13/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/14/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/15/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/16/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/17/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/18/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/19/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/20/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/21/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/22/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/23/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/24/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/25/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/26/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/27/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/28/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/29/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/30/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/31/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/1/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/2/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/3/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/4/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/5/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/6/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/7/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/8/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/9/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/10/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/11/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/12/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/13/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/14/2009 294 52.40% 29 5.20% 108 19.30% 1 0.20% 10 1.80%
8/15/2009 217 49.90% 13 3.00% 49 11.30% 52 12.00% 19 4.40%
8/16/2009 481 59.10% 76 9.30% 94 11.50% 4 0.50% 15 1.80%
8/17/2009 568 65.00% 58 6.60% 119 13.60% 4 0.50% 29 3.30%
8/18/2009 416 62.80% 25 3.80% 86 13.00% 7 1.10% 23 3.50%
8/19/2009 529 58.10% 47 5.20% 105 11.50% 34 3.70% 49 5.40%
...
..
.
WHAT I DID .
file<-read.csv("filename.csv",header=TRUE)
miedata<-as.POSIXct(strptime(as.character(file[,1]),format="%m/%d/%Y"))
zoom<-zoo(file[,2],miedata)
plot(zoom)
Any help of any sort will be greatly appreciated. Its been very hard to get
a grip of Irregular Time Series in R
Thanks
--
View this message in context:
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Hi
I have a daily level time series data. What I need to do is a time series
analysis and forecasting and stuff.
But the thing I am stuck at is - I cant get a decent time series plot of the
data I have
http://r.789695.n4.nabble.com/file/n3021984/test.jpg
This is a plot of daily level data from July 09 to Oct 10. what I am
interested is in - like instead of just 2010 time stamp on x axis, if I
could have monthly tags it would be great.
Here is what I have done -
MY DATA IS OF THIS FORMAT
Date X Y Z A B C
D E F G
7/1/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/2/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/3/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/4/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/5/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/6/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/7/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/8/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/9/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/10/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/11/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/12/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/13/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/14/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/15/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/16/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/17/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/18/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/19/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/20/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/21/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/22/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/23/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/24/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/25/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/26/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/27/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/28/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/29/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/30/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
7/31/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/1/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/2/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/3/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/4/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/5/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/6/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/7/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/8/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/9/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/10/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/11/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/12/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/13/2009 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00%
8/14/2009 294 52.40% 29 5.20% 108 19.30% 1 0.20% 10 1.80%
8/15/2009 217 49.90% 13 3.00% 49 11.30% 52 12.00% 19 4.40%
8/16/2009 481 59.10% 76 9.30% 94 11.50% 4 0.50% 15 1.80%
8/17/2009 568 65.00% 58 6.60% 119 13.60% 4 0.50% 29 3.30%
8/18/2009 416 62.80% 25 3.80% 86 13.00% 7 1.10% 23 3.50%
8/19/2009 529 58.10% 47 5.20% 105 11.50% 34 3.70% 49 5.40%
...
..
.
WHAT I DID .
file<-read.csv("filename.csv",header=TRUE)
miedata<-as.POSIXct(strptime(as.character(file[,1]),format="%m/%d/%Y"))
zoom<-zoo(file[,2],miedata)
plot(zoom)
Any help of any sort will be greatly appreciated. Its been very hard to get
a grip of Irregular Time Series in R
Thanks
--
View this message in context:
http://r.789695.n4.nabble.com/Irregular-Time-Series-tp3021984p3021984.html
Sent from the R help mailing list archive at Nabble.com.
On Mon, Nov 1, 2010 at 6:59 AM, mysterio66 <tarun.baloch at iprospect.com> wrote:> > Hi > > I have a daily level time series data. What I need to do is a time series > analysis and forecasting and stuff. > > But the thing I am stuck at is - I cant get a decent time series plot of the > data I have > http://r.789695.n4.nabble.com/file/n3021984/test.jpg > > This is a plot of daily level data from July 09 to Oct 10. what I am > interested is in - like instead of just 2010 time stamp on x axis, if I > could have monthly tags it would be great.There is an example in example(plot.zoo) -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com