larry-discuss team mailing list archive

[josef.pktd@xxxxxxxxx]

On Mon, May 3, 2010 at 8:01 PM, Keith Goodman <kwgoodman@xxxxxxxxx> wrote:
> On Mon, May 3, 2010 at 1:13 PM,  <josef.pktd@xxxxxxxxx> wrote:
>> Here is a simple implementation of a reduce option in groupmean,
>> essentially it is two functions in one.
>>
>> see https://blueprints.launchpad.net/larry/+spec/group-method-design
>> as a standalone function it could also be plugged into other larry
>> methods, e.g. larry.mean
>>
>> Only tested on the example in the file.
>>
>> Josef
>
> A reduce option would be very handy. And it's very handy to have your
> implementation to get a feel for how it would work. Thank you.
>
> BTW, what do you think of a weight input to the group-like functions?
> It could be used, for example, to calculated a weighted group mean.
> The weight could be 1d or have the same number of dimensions as the
> input array.

just to clarify
How would you interpret and use the weights?
So, for example, weights are firm sizes, then you want size weighted
averages for each sector.

It would also need a weights option in nanmean.

group_mean and nanmean would be useful with weights, but I don't know
what a weighted group_ranking would mean. group_median: would it be
the 50th percentile (in terms of weights or like a distribution)?

There is also an attachment to a scipy.stats trac ticket that does
describtive statistics with weights and nan-handling.

Josef

Josef