Lets say I have a log file from a web server with response times per request:
_1st_request 1334
_2nd_request 345
_3rd_request 244
_4th_request 648
......... etc
Is there an easy way with bash scripting to find the top decile (10-quantile)? In other words to answer the question: How slow was the slowest request if I exclude the slowest...
My code is based on the methods described here and here.
def fraction?(number)
number - number.truncate
end
def percentile(param_array, percentage)
another_array = param_array.to_a.sort
r = percentage.to_f * (param_array.size.to_f - 1) + 1
if r <= 1 then return another_array[0]
elsif r >= another_array.size then return anothe...
I have a dataframe that looks like this:
str(Data)
'data.frame': 11520 obs. of 29 variables:
$ groupname : Factor w/ 8 levels "Control","Treatment1",..: 1 1 1 1 1 1 1 1 1 1 ...
$ fCycle : Factor w/ 2 levels "Dark","Light": 2 2 2 2 2 2 2 2 2 2 ...
$ totdist : num 0 67.5 89.8 109.1 58.3 ...
#etc.
I can do a single plot o...
The real goal here is to find the quantile means (or sums, or median, etc.) in Python. Since I'm not a power user of Python but have used R for a while, my chosen route is via Rpy. However, I ran into the problem that the returned list of means are not correspondent to the order of the quantiles. In particular, I have the followings in R...
Hi all,
i´d like to assign factors representing quantiles. Thus I need them to be numeric.
That´s why I wrote the following function, which is basically the answer to my problem:
qdum <- function(v,q){
qd = quantile(v,1:(q)/q)
v = as.data.frame(v)
v$b = 0
names(v) <- c("a","b")
i=1
for (i in 1:q){
if(i == 1)
v$b[ v$a < ...