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Tonja Krueger

2011-Mar-22 15:05 UTC

[R] Accelerating the calculation of the moving average

Dear List,
I have a data frame with approximately 500000 rows that looks like this:

?Date??? time??? value
?
19.07.1956????????? 12:00:00?????????????? 4.84
19.07.1956????????? 13:00:00?????????????? 4.85
19.07.1956????????? 14:00:00?????????????? 4.89
19.07.1956????????? 15:00:00?????????????? 4.94
19.07.1956????????? 16:00:00?????????????? 4.99
19.07.1956????????? 17:00:00?????????????? 5.01
19.07.1956????????? 18:00:00?????????????? 5.04
19.07.1956????????? 19:00:00?????????????? 5.04
19.07.1956????????? 20:00:00?????????????? 5.04
19.07.1956????????? 21:00:00?????????????? 5.02
19.07.1956????????? 22:00:00?????????????? 5.01
19.07.1956????????? 23:00:00?????????????? 5.00
20.07.1956????????? 00:00:00?????????????? 4.99
20.07.1956????????? 01:00:00?????????????? 4.99
20.07.1956????????? 02:00:00?????????????? 5.00
20.07.1956????????? 03:00:00?????????????? 5.03
20.07.1956????????? 04:00:00?????????????? 5.07
20.07.1956????????? 05:00:00?????????????? 5.10
20.07.1956????????? 06:00:00?????????????? 5.14
20.07.1956????????? 07:00:00?????????????? 5.14
20.07.1956????????? 08:00:00?????????????? 5.11
20.07.1956????????? 09:00:00?????????????? 5.08
20.07.1956????????? 10:00:00?????????????? 5.03
20.07.1956????????? 11:00:00?????????????? 4.98
20.07.1956????????? 12:00:00?????????????? 4.94
20.07.1956????????? 13:00:00?????????????? 4.93
?

I want to calculate
the moving average of the right column.
I tried:

dat$index<-1:length(dat$Zeit)
qs<- 43800
erg<-c()
for (y in min(dat$index):max(dat$index)){
m<- mean(dat[(dat$index>=y)&(dat$index<=y+qs+1),3])
erg<-c(erg,m)
}

It does works, but it takes ages. Is there a faster way to compute the moving
average?

Thank you, 
Tonja Krueger


___________________________________________________________
Handy Internet-Flat ? gratis ? mit WEB.DE FreePhone

Kenn Konstabel

2011-Mar-22 15:10 UTC

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[R] Accelerating the calculation of the moving average

On Tue, Mar 22, 2011 at 3:05 PM, Tonja Krueger <tonja.krueger@web.de>
wrote:
>
> Dear List,
> I have a data frame with approximately 500000 rows that looks like this:
>
>  Date    time    value
> …
> 19.07.1956          12:00:00               4.84
> 19.07.1956          13:00:00               4.85
> 19.07.1956          14:00:00               4.89
> 19.07.1956          15:00:00               4.94
> 19.07.1956          16:00:00               4.99
> 19.07.1956          17:00:00               5.01
> 19.07.1956          18:00:00               5.04
> 19.07.1956          19:00:00               5.04
> /.../

> 20.07.1956          12:00:00               4.94
> 20.07.1956          13:00:00               4.93
> …
>
> I want to calculate
> the moving average of the right column.
> I tried:
>
> dat$index<-1:length(dat$Zeit)
> qs<- 43800
> erg<-c()
> for (y in min(dat$index):max(dat$index)){
> m<- mean(dat[(dat$index>=y)&(dat$index<=y+qs+1),3])
> erg<-c(erg,m)
> }
>
> It does works, but it takes ages. Is there a faster way to compute the
> moving average?
>
see e.g., rollmean in package zoo
>
> Thank you,
> Tonja Krueger
>
>
> ___________________________________________________________
> Handy Internet-Flat ¿ gratis ¿ mit WEB.DE FreePhone
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
	[[alternative HTML version deleted]]

Gabor Grothendieck

2011-Mar-22 15:19 UTC

head link

[R] Accelerating the calculation of the moving average

On Tue, Mar 22, 2011 at 11:05 AM, Tonja Krueger <tonja.krueger at web.de>
wrote:>
> Dear List,
> I have a data frame with approximately 500000 rows that looks like this:
>
> ?Date??? time??? value
> ?
> 19.07.1956????????? 12:00:00?????????????? 4.84
> 19.07.1956????????? 13:00:00?????????????? 4.85
> 19.07.1956????????? 14:00:00?????????????? 4.89
> 19.07.1956????????? 15:00:00?????????????? 4.94
> 19.07.1956????????? 16:00:00?????????????? 4.99
> 19.07.1956????????? 17:00:00?????????????? 5.01
> 19.07.1956????????? 18:00:00?????????????? 5.04
> 19.07.1956????????? 19:00:00?????????????? 5.04
> 19.07.1956????????? 20:00:00?????????????? 5.04
> 19.07.1956????????? 21:00:00?????????????? 5.02
> 19.07.1956????????? 22:00:00?????????????? 5.01
> 19.07.1956????????? 23:00:00?????????????? 5.00
> 20.07.1956????????? 00:00:00?????????????? 4.99
> 20.07.1956????????? 01:00:00?????????????? 4.99
> 20.07.1956????????? 02:00:00?????????????? 5.00
> 20.07.1956????????? 03:00:00?????????????? 5.03
> 20.07.1956????????? 04:00:00?????????????? 5.07
> 20.07.1956????????? 05:00:00?????????????? 5.10
> 20.07.1956????????? 06:00:00?????????????? 5.14
> 20.07.1956????????? 07:00:00?????????????? 5.14
> 20.07.1956????????? 08:00:00?????????????? 5.11
> 20.07.1956????????? 09:00:00?????????????? 5.08
> 20.07.1956????????? 10:00:00?????????????? 5.03
> 20.07.1956????????? 11:00:00?????????????? 4.98
> 20.07.1956????????? 12:00:00?????????????? 4.94
> 20.07.1956????????? 13:00:00?????????????? 4.93
> ?
>
> I want to calculate
> the moving average of the right column.
> I tried:
>
> dat$index<-1:length(dat$Zeit)
> qs<- 43800
> erg<-c()
> for (y in min(dat$index):max(dat$index)){
> m<- mean(dat[(dat$index>=y)&(dat$index<=y+qs+1),3])
> erg<-c(erg,m)
> }
>
> It does works, but it takes ages. Is there a faster way to compute the
moving average?
>
> Thank you,
> Tonja Krueger
There are rolling mean or sum functions written in C in the caTools,
xts and TTR packages (and possibly other packages as well).

There are also faster ways to do it even in pure R such as the
rollmean function in zoo (although that would not be expected to be as
fast as the C implementations).

-- 
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com

William Dunlap

2011-Mar-22 16:25 UTC

head link

[R] Accelerating the calculation of the moving average

filter(), in the stats package, can do moving
averages (with any weights).

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com  
> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Tonja Krueger
> Sent: Tuesday, March 22, 2011 8:06 AM
> To: r-help at r-project.org
> Subject: [R] Accelerating the calculation of the moving average
> 
> 
> Dear List,
> I have a data frame with approximately 500000 rows that looks 
> like this:
> 
> ?Date??? time??? value
> ...
> 19.07.1956????????? 12:00:00?????????????? 4.84
> 19.07.1956????????? 13:00:00?????????????? 4.85
> 19.07.1956????????? 14:00:00?????????????? 4.89
> 19.07.1956????????? 15:00:00?????????????? 4.94
> 19.07.1956????????? 16:00:00?????????????? 4.99
> 19.07.1956????????? 17:00:00?????????????? 5.01
> 19.07.1956????????? 18:00:00?????????????? 5.04
> 19.07.1956????????? 19:00:00?????????????? 5.04
> 19.07.1956????????? 20:00:00?????????????? 5.04
> 19.07.1956????????? 21:00:00?????????????? 5.02
> 19.07.1956????????? 22:00:00?????????????? 5.01
> 19.07.1956????????? 23:00:00?????????????? 5.00
> 20.07.1956????????? 00:00:00?????????????? 4.99
> 20.07.1956????????? 01:00:00?????????????? 4.99
> 20.07.1956????????? 02:00:00?????????????? 5.00
> 20.07.1956????????? 03:00:00?????????????? 5.03
> 20.07.1956????????? 04:00:00?????????????? 5.07
> 20.07.1956????????? 05:00:00?????????????? 5.10
> 20.07.1956????????? 06:00:00?????????????? 5.14
> 20.07.1956????????? 07:00:00?????????????? 5.14
> 20.07.1956????????? 08:00:00?????????????? 5.11
> 20.07.1956????????? 09:00:00?????????????? 5.08
> 20.07.1956????????? 10:00:00?????????????? 5.03
> 20.07.1956????????? 11:00:00?????????????? 4.98
> 20.07.1956????????? 12:00:00?????????????? 4.94
> 20.07.1956????????? 13:00:00?????????????? 4.93
> ...
> 
> I want to calculate
> the moving average of the right column.
> I tried:
> 
> dat$index<-1:length(dat$Zeit)
> qs<- 43800
> erg<-c()
> for (y in min(dat$index):max(dat$index)){
> m<- mean(dat[(dat$index>=y)&(dat$index<=y+qs+1),3])
> erg<-c(erg,m)
> }
> 
> It does works, but it takes ages. Is there a faster way to 
> compute the moving average? 
> 
> Thank you, 
> Tonja Krueger
> 
> 
> ___________________________________________________________
> Handy Internet-Flat ? gratis ? mit WEB.DE FreePhone
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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