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Do you think we are missing an alternative of gohistogram or a related project?
README
gohistogram  Histograms in Go
This package provides Streaming Approximate Histograms for efficient quantile approximations.
The histograms in this package are based on the algorithms found in BenHaim & YomTov's A Streaming Parallel Decision Tree Algorithm (PDF). Histogram bins do not have a preset size. As values stream into the histogram, bins are dynamically added and merged.
Another implementation can be found in the Apache Hive project (see NumericHistogram).
An example:
The accurate method of calculating quantiles (like percentiles) requires data to be sorted. Streaming histograms make it possible to approximate quantiles without sorting (or even individually storing) values.
NumericHistogram is the more basic implementation of a streaming histogram. WeightedHistogram implements bin values as exponentiallyweighted moving averages.
A maximum bin size is passed as an argument to the constructor methods. A larger bin size yields more accurate approximations at the cost of increased memory utilization and performance.
A picture of kittens:
Getting started
Using in your own code
$ go get github.com/VividCortex/gohistogram
import "github.com/VividCortex/gohistogram"
Running tests and making modifications
Get the code into your workspace:
$ cd $GOPATH
$ git clone git@github.com:VividCortex/gohistogram.git ./src/github.com/VividCortex/gohistogram
You can run the tests now:
$ cd src/github.com/VividCortex/gohistogram
$ go test .
API Documentation
Full source documentation can be found here.
Contributing
We only accept pull requests for minor fixes or improvements. This includes:
 Small bug fixes
 Typos
 Documentation or comments
Please open issues to discuss new features. Pull requests for new features will be rejected, so we recommend forking the repository and making changes in your fork for your use case.
License
Copyright (c) 2013 VividCortex
Released under MIT License. Check LICENSE
file for details.
*Note that all licence references and agreements mentioned in the gohistogram README section above
are relevant to that project's source code only.