Julia equivalent of scipy binned_statistic_dd

[sethaxen]

@jpmorr

But looking at it now, it still seems to be different as it’s binning multiple vecotrs against a single set of bins, whereas what I want to do is bin based on a single set of data against 3D bins, like:

h = fit(Histogram, (rand(1000,3)), nbins=(40, 5, 9))

In this case I have 1000 coordiantes in x,y, znd and it want to bin that 3D data into a 3D grid with specified numbers of bins in each direction. I don’t think Histogram will do that, at least from what I can see in the documentation anyway.

I think if you get returned counts and indices like in scipy or numpy it would be easy enough to work out the statistics after the fact, but I’m not sure the counts and IDs for each bin are retunred by Histogram .

This should do what you want:

x = rand(1000,3)
h = fit(Histogram, Tuple(eachcol(x)); nbins=(40, 5, 9))
bin_ids = map(xi -> StatsBase.binindex(h, Tuple(xi)), eachrow(x))