Dear all,
I am pretty new to R only having an introduction course, so please bare with
me. I am doing my PhD at The Max Planck Institute of Immunobiology where I
am analyzing some calorimetry data from some mice.
I have a spreadsheet consisting of measurements of the respiratory exchange
rate
It would be something like this (might have to change the syntax a bit)
bin_ave=0;
while (i lenth(time)){
bin_ave[k]=mean(time(i:i+6));
k=k+1;
i=i+6;
}
if your data is in a table format replace time with mytable$time.
hope this helps,
Sachin
p.s. sorry about corporate
try this:
# create times 9 minutes apart
time - seq(as.POSIXct('2010-11-25 00:00'), by = '9 min', length = 480)
mySamp - data.frame(time = time, value = sample(1:100, length(time), TRUE))
# add column to split by hour
mySamp$hour - format(mySamp$time, '%Y-%m-%d %H:30')
# compute the mean
Hi Kevin
Here is one way:
yourData - c(0.730, 0.732, 0.743, 0.757,0.781, 0.731,
0.830, 0.832, 0.843, 0.857, 0.881, 0.831)
nrGroups - 2
lengthGroups - 6
tapply(yourData, factor(rep(c(1,nrGroups), each = lengthGroups)), mean)
and you will have to adjust the number of groups and if necessary
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