I'm trying to calculate the percent change for a time-series variable. Basically the first several observations often look like this, x <- c(100, 0, 0, 150, 130, 0, 0, 200, 0) and then later in the life of the variable they're are generally no more 0's. So when I try to calculate the percent change from one observation to the next, I end up with a lot of NA/Nan/INF, and sometimes 0's which is what I want, in the beginning. I know I can use x <- na.omit(x), and other forms of this, to get rid of some of these errors. But I would rather use some kind of function that would by defult give a 0 while dividing by zero so that I don't lose the observation, which is what happens when I use na.omit. I would imagine this is a common problem. I tried finding something in zoo, but I haven't found what I'm looking for. Any advice would be appreciated. -- View this message in context: http://www.nabble.com/Dividing-by-0-tp18632469p18632469.html Sent from the R help mailing list archive at Nabble.com.
> > I'm trying to calculate the percent change for a time-series variable. > Basically the first several observations often look like this, > > x <- c(100, 0, 0, 150, 130, 0, 0, 200, 0) > > and then later in the life of the variable they're are generally no more > 0's. So when I try to calculate the percent change from one observation > to > the next, I end up with a lot of NA/Nan/INF, and sometimes 0's which is > what > I want, in the beginning. > > I know I can use x <- na.omit(x), and other forms of this, to get rid of > some of these errors. But I would rather use some kind of function that > would by defult give a 0 while dividing by zero so that I don't lose the > observation, which is what happens when I use na.omit. >Well, this is not an error but proper behavior in the world of math that I know. However, to get what you want you could try x=(100-0)/0 if(!is.finite(x))x=0 x
On Thu, 2008-07-24 at 06:57 -0700, nmarti wrote:> I'm trying to calculate the percent change for a time-series variable. > Basically the first several observations often look like this, > > x <- c(100, 0, 0, 150, 130, 0, 0, 200, 0) > > and then later in the life of the variable they're are generally no more > 0's. So when I try to calculate the percent change from one observation to > the next, I end up with a lot of NA/Nan/INF, and sometimes 0's which is what > I want, in the beginning. > > I know I can use x <- na.omit(x), and other forms of this, to get rid of > some of these errors. But I would rather use some kind of function that > would by defult give a 0 while dividing by zero so that I don't lose the > observation, which is what happens when I use na.omit. > > I would imagine this is a common problem. I tried finding something in zoo, > but I haven't found what I'm looking for. >Hi nmarti, If you are looking for percent change, it is probably easiest to write a little function that you can call for each pair of values. I'm assuming that all of your values are >= 0. pctchng<-function(x1,x2) { # don't try to calculate the value if(x1==0) { # if the second value is zero, there is no change if(x1==0) return(0) # otherwise there is infinite change # you may want to return another value here else return(Inf) } # it's okay, calculate the percentage change return(100*(x2-x1)/x1) } Jim
Hi, what about: mydata <- c(1,2,3,NA, Inf, -Inf, NaN, 5, 6, 7) mydata2 <- ifelse(is.na(mydata) | is.infinite(mydata), 0, mydata) mydata mydata2 nmarti wrote:> I know I can use x <- na.omit(x), and other forms of this, to get rid of > some of these errors.I know what you mean, I think, but I would not call it errors. Rather, it is following a standard specification. Check ?is.finite for further information (and the links therein). Hope this helps, Roland
I suspect you should be smoothing the series in a manner that
replaces zeros by some usually small larger number before
you start. Without more details on what you are trying to do, it
is impossible to know what is sensible. You are proposing to
leave all smoothing ("rolling"?) till later; why not do some
smoothing at the start?
John Maindonald email: john.maindonald at anu.edu.au
phone : +61 2 (6125)3473 fax : +61 2(6125)5549
Centre for Mathematics & Its Applications, Room 1194,
John Dedman Mathematical Sciences Building (Building 27)
Australian National University, Canberra ACT 0200.
On 26 Jul 2008, at 8:00 PM, r-help-request at r-project.org wrote:
> From: nmarti <nate318i at yahoo.com>
> Date: 26 July 2008 1:42:09 AM
> To: r-help at r-project.org
> Subject: Re: [R] Dividing by 0
>
>
> I'm well aware these are not errors, I guess I miss-wrote.
> I understand your concern. Thanks for passionately looking out for
> my well
> being, you saved my life.
>
> My variable has about 10,000 elements and sometime for the first 100
> to 500
> elements there is lots of 0's, so I end up with lots of
NA/NaN/Inf's.
> However, when I try to use "Rolling" calculations I recieve error
> messages
> because the "Rolling" functions reject the NA/NaN/Inf's. So,
I need
> 0's in
> place of the NA/NaN/Inf's so I can run the "Rolling"
calculations.
> I can't
> just delete these observations, because it messes up lots of other
> other
> things within these dataframes.
>
> I'm well aware these "Rolling" calculations will be wrong in
the
> beginning
> of the dataframe, so I just throw these out. The rolling window is
> only
> about 50 odservations, so out of 10,000, I still end up with ample
> correct
> data and calculations.
>
> So is this still idiotic?
> Thanks again for your concern. Now that you understand my situation a
> little better, you might be less distracted today and be able to sleep
> better tonight.