statistics.rb
A statistics library for Ruby.
Installation
gem install statistics.rb
Or add to your Gemfile:
gem 'statistics.rb'Usage
Histogram
Create a histogram from an array of numeric values:
require 'statistics.rb'
values = [1.2, 3.4, 5.6, 7.8, 2.3, 4.5, 6.7, 8.9, 3.2, 5.4]
h = Statistics::Histogram.new(values)
puts hOutput:
1.20...3.63 | 3 | ****************************************
3.63...6.07 | 3 | ****************************************
6.07...8.50 | 2 | ***************************
8.50...10.93 | 1 | *************
Automatic bin width
By default, bin width is calculated using the square root rule: data_range / sqrt(n).
Manual bin width
h = Statistics::Histogram.new(values, bin_width: 2.0)Manual bin count
h = Statistics::Histogram.new(values, bin_count: 5)Querying the histogram
h.bins # => [#<Bin ...>, #<Bin ...>, ...]
h.boundaries # => [1.2, 3.77, 6.34, ...]
h.bin_count # => 4
h.mode # => #<Bin interval=1.2...3.77 count=3>
h.bins.first.interval # => 1.2...3.77
h.bins.first.count # => 3
h.bins.first.width # => 2.57
h.bins.first.empty? # => falsePercentile
These methods employ linear interpolation. See Hyndman and Fan method 7.
require 'statistics.rb'
values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Statistics::Percentile.of(values, 75) # => 7.75
Statistics::Percentile.q25(values) # => 3.25
Statistics::Percentile.q75(values) # => 7.75Standard Deviation
Statistics::StandardDeviation.of(values) # => population (default)
Statistics::StandardDeviation.of(values, sample: true) # => sample (Bessel's correction)Interquartile Range
Statistics::IQR.of(values) # => 4.5Roadmap
- Optional per-bin value storage
- Additional bin width methods (Freedman-Diaconis, Scott, Sturges, cube root, tuneable root)
- Aligned/neat bin boundaries
License
MIT