Thanks to everybody for trying to help me with this, I think there are
a few workable options here. However, I think the most efficient
option that I've found was to avoid the join/aggregate in R
altogether. I've joined them at the database level to accomplish the
same thing. This may not be a h
Oh, you didn't say the intervals could overlap!
If Bill D's suggestions don't suffice, try the following:
(again assuming all dates are in a form that allow comparison
operations, e.g. via as.POSIX**)
Assume you have g intervals with start dates "starts" and end dates
"ends" and that you have d
You could try pulling some of the repeated subscripting operations,
especially the insertions, out of the loop. E.g.,
values <- observations[,"values"];
date <- observations[,"date"] ;
groups$average <- vapply(seq_len(NROW(groups)), function(i)
mean(values[date >= groups[i, "start"] &
Thanks David, Bert,
>From what I'm reading on ?findInterval, It may not be workable because
of overlapping date ranges. findInterval seems to take a series of
bin breakpoints as its argument. I'm currently exploring data.table
documentation and will keep thinking about this.
Just on David's poin
A strategy:
1. Convert your dates and intervals to numerics that give the days
since a time origin. See as.POSIXlt (or ** ct for details and an
example that does this). Should be fast...
2. Use the findInterval() function to get the interval into which each
date falls. This **is** "vectorized" a
> On Feb 10, 2016, at 12:18 PM, Peter Lomas wrote:
>
> Hello, I have a dataframe with a date range, and another dataframe
> with observations by date. For each date range, I'd like to average
> the values within that range from the other dataframe. I've provided
> code below doing what I would
Hello, I have a dataframe with a date range, and another dataframe
with observations by date. For each date range, I'd like to average
the values within that range from the other dataframe. I've provided
code below doing what I would like, but using a for loop is too
inefficient for my actual cas
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