Donald Braman wrote:
Thanks, for the response!
Unfortunately, I was unclear; my problem is not that I need to know what the
percentile ranges are, but that I need to assign an appropriate percentile
range to each of the records in my dataframe. My dataframe contains
somewhere between 1000 and 9000 rows/records in my dataframe (depending on
context), not a hundred rows. That is, I'd like to assign a corresponding
quantile value to each row that corresponds to the quantile() result for
each record in my 1000-9000 row data frame.
Thanks again for any help!
You can use
cnt <- cut(x, quantile(x, seq(0,1,0.01)), include=TRUE)
names(cnt) <- 1:100 # if you want to get rid of ugly interval labels
With Harrells Hmisc packages, there's also
cnt <- cut2(x, g=100)
Or you can take a more basic approach and do
N <-sum(!is.na(x))
cnt <- ceiling(rank(x)/N*100)
On Sat, Sep 27, 2008 at 8:54 AM, Henrique Dallazuanna <[EMAIL PROTECTED]>wrote:
Try this:
my.df$my.newvar <- quantile(my.df$my.var, probs = seq(0.01,1, 0.01))
On Sat, Sep 27, 2008 at 3:50 AM, Donald Braman <[EMAIL PROTECTED]>
wrote:
I'm wondering if there is a simple way to assign a quantile to a vector
in a
data frame, much like one could in Stata using centile. Let's say I want
100
slices in my assignation. I can easily see what the limits of each slice
by
using quantile:
quantile(my.df$my.var, probs=seq(0, 1, 0.01))
But how do I assign the appropriate value to each row/record in my data
frame? Clearly the following won't work, but what will?
my.df$my.new.var <- quantile(my.df$my.var, probs=seq(0, 1, 0.01))
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