Dear all R users,
Suppose I have a dataset like that, data =
1 1.957759e-09
2 1.963619e-09
3 1.962807e-09
4 1.973951e-09
5 1.983401e-09
6 1.990894e-09
7 2.000935e-09
8 1.998391e-09
9 1.973322e-09
10 1.983202e-09
I want to see at which row minimum value of the second column occures.
Therefore I made the following loop:
i=1
while (min(data[,2]) != data[i,2])
{
i = i+1
}
> i
[1] 1
Is there any more effective way to do that in terms of time consumption?
Thanks
stat
---------------------------------
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stat stat wrote:> I want to see at which row minimum value of the second column occures. > > Therefore I made the following loop:[snip while-loop]> > Is there any more effective way to do that in terms of time consumption?I don't know about timing, but I understand that loops are somewhat slow. Assuming that x is the first column and y is the second column: D <- data.frame( x = 1:10, y = rnorm(10) ) D$x[ which.min(D$y) ] See the help of which.min for more info. -Jarimatti
?which.min> >Dear all R users, > > Suppose I have a dataset like that, data = > > 1 1.957759e-09 > 2 1.963619e-09 > 3 1.962807e-09 > 4 1.973951e-09 > 5 1.983401e-09 > 6 1.990894e-09 > 7 2.000935e-09 > 8 1.998391e-09 > 9 1.973322e-09 > 10 1.983202e-09 > > I want to see at which row minimum value of the second >column occures. > > Therefore I made the following loop: > > i=1 > while (min(data[,2]) != data[i,2]) > { > i = i+1 > } > > > i >[1] 1 > > Is there any more effective way to do that in terms of time >consumption? > > Thanks > stat > > >--------------------------------- > Here's a new way to find what you're looking for - Yahoo! Answers > [[alternative HTML version deleted]] > >***************************************************************** Confidentiality Note: The information contained in this mess...{{dropped}}