1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
|
# Enumerable::Statistics
[](https://travis-ci.org/mrkn/enumerable-statistics)
Enumerable::Statistics provides some methods to calculate statistical summary in arrays and enumerables.
## Installation
Add this line to your application's Gemfile:
```ruby
gem 'enumerable-statistics'
```
And then execute:
$ bundle
Or install it yourself as:
$ gem install enumerable-statistics
## Usage
You should load this library by the following line in your script at first.
```ruby
require 'enumerable/statistics'
```
The following methods are supplied by this library:
- `Array#mean`, `Enumerable#mean`
- Calculates a mean of values in an array or an enumerable
- `Array#variance`, `Enumerable#variance`
- Calculates a variance of values in an array or an enumerable
- `Array#stdev`, `Enumerable#stdev`
- Calculates a standard deviation of values in an array or an enumerable
- `Array#mean_variance`, `Enumerable#mean_variance`
- Calculates a mean and a variance simultaneously
- `Array#mean_stdev`, `Enumerable#mean_stdev`
- Calculates a mean and a standard deviation simultaneously
- `Array#median`
- Calculates a median of values in an array
- `Array#percentile(q)`
- Calculates a percentile or percentiles of values in an array
- `Array#value_counts`, `Enumerable#value_counts`, and `Hash#value_counts`
- Count how many items for each value in the container
- `Array#histogram`
- Calculate histogram of the values in the array
Moreover, for Ruby < 2.4, `Array#sum` and `Enumerable#sum` are provided.
All methods scan a collection once to calculate statistics and preserve precision as possible.
## Performance
```
$ bundle exec rake bench
# sum
Warming up --------------------------------------
inject 1.545k i/100ms
while 2.342k i/100ms
sum 11.009k i/100ms
Calculating -------------------------------------
inject 15.016k (± 9.6%) i/s - 75.705k in 5.098723s
while 22.238k (±16.2%) i/s - 107.732k in 5.068156s
sum 112.992k (± 6.9%) i/s - 572.468k in 5.091868s
# mean
Warming up --------------------------------------
inject 1.578k i/100ms
while 2.057k i/100ms
mean 9.855k i/100ms
Calculating -------------------------------------
inject 15.347k (± 8.6%) i/s - 77.322k in 5.076009s
while 21.669k (±14.5%) i/s - 106.964k in 5.074312s
mean 108.861k (± 8.9%) i/s - 542.025k in 5.021786s
# variance
Warming up --------------------------------------
inject 586.000 i/100ms
while 826.000 i/100ms
variance 8.475k i/100ms
Calculating -------------------------------------
inject 6.187k (± 6.7%) i/s - 31.058k in 5.043418s
while 8.597k (± 7.4%) i/s - 42.952k in 5.024587s
variance 84.702k (± 8.5%) i/s - 423.750k in 5.039936s
```
## Development
After checking out the repo, run `bin/setup` to install dependencies. You can also run `bin/console` for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run `bundle exec rake install`. To release a new version, update the version number in `version.rb`, and then run `bundle exec rake release`, which will create a git tag for the version, push git commits and tags, and push the `.gem` file to [rubygems.org](https://rubygems.org).
## Contributing
Bug reports and pull requests are welcome on GitHub at https://github.com/mrkn/enumerable-statistics.
|
