Dear Jeff,
This is great to me!!! Many, many thanks.
I have also clicked the send plain text mode button and I hope this
message will appear in plain text mode.
Thanks again.
Warmest regards.
Ogbos
On Wed, Nov 28, 2018 at 7:06 AM Jeff Newmiller wrote:
>
> Thank you for providing a clarifying
Thank you for providing a clarifying example. I think a useful function
for you to get familiar with is the "ave" function. It is kind of like
aggregate except that it works when the operation you want to apply to the
group of elements will returns the same number of elements as were given
to i
Dear Jim,
I don't think my problem is clear the way I put.
I have been trying to manually apply the formula to some rows.
This is what I have done.
I cut and past some rows from 1-7 and save each with a different file as
shown below:
1 8590 12516
2 8641 98143
3 8705 98916
4 8750 89911
5 8685 10
Dear Jim,
I wish also to use the means calculated and apply a certain formula on the
same data frame. In particular, I would like to subtract the means of each
of these seven days from each of the seven days and and divide the outcome
by the same means. If I represent m1 by the means of each seven
On Wed, Nov 28, 2018 at 4:31 AM Jim Lemon wrote:
> Hi Ogbos,
> If we assume that you have a 3 column data frame named oodf, how about:
>
> Dear Jim,
Thank you so much.
The code just made life very easier for me.
best regards
Ogbos
> oodf[,4]<-floor((cumsum(oodf[,1])-1)/28)
> col2means<-by(o
Hi Ogbos,
If we assume that you have a 3 column data frame named oodf, how about:
oodf[,4]<-floor((cumsum(oodf[,1])-1)/28)
col2means<-by(oodf[,2],oodf[,4],mean)
col3means<-by(oodf[,3],oodf[,4],mean)
Jim
On Wed, Nov 28, 2018 at 2:06 PM Ogbos Okike wrote:
>
> Dear List,
> I have three data-column
Dear List,
I have three data-column data. The data is of the form:
1 8590 12516
2 8641 98143
3 8705 98916
4 8750 89911
5 8685 104835
6 8629 121963
7 8676 77655
1 8577 81081
2 8593 83385
3 8642 112164
4 8708 103684
5 8622 83982
6 8593 75944
7 8600 97036
1 8650 104911
2 8730 114098
3 8731 99421
4 871
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