lpstats

Go package for simple statistics

The package lpstats provides a simple interface for statistics. It provides functions for the calculation of mean and variance.

• Simple: Without configuration, just function calls
• Easy to use: Most functions take integer and float values as arguments
• Tested: Unit tests with high code coverage
• Dependencies: Only depends on the Go Standard Library and tserr

Usage

The package is installed with

go get github.com/thorstenrie/lpstats

In the Go app, the package is imported with

import "github.com/thorstenrie/lpstats"

External functions can be used with arguments of type integer or float. Type constraints are defined in constraints.go.

• Number: number types, for example, func Square[T Number](x T) float64
• Signed: signed number types, for example, func Sign[T Signed](a T) T
• Sinteger: signed integer types, for example func EqualS[T Sinteger](x, y T) error
• Uinteger: unsigned integer types, for example, func VarianceN[T Uinteger](n T) float64

Functions

The package provides mathematical and statistical functions

• Absolute value
• Arithmetic mean of a discrete value array
• Equal for slices of signed integers
• Expected value for a uniform distribution
• Max (Depcrecated and will be removed in one of the next releases)
• Min (Depcrecated and will be removed in one of the next releases)
• Near equal
• Sign
• Square
• Sum
• Variance of a discrete value array
• Variance of a uniform distribution

Example

package main

import (
	"fmt"

	"github.com/thorstenrie/lpstats"
)

func main() {
	var (
		i []int     = []int{1, 2, 3, 4, 5, 6}
		x []float64 = []float64{1.1, 2.1, 3.1, 4.1, 5.1, 6.1}
		n uint      = 6
	)

	im, _ := lpstats.ArithmeticMean(i)
	xm, _ := lpstats.ArithmeticMean(x)

	iv, _ := lpstats.Variance(i)
	xv, _ := lpstats.Variance(x)

	fmt.Printf("Mean(i) = %f, Variance(i) = %f\n", im, iv)
	fmt.Printf("Mean(f) = %f, Variance(x) = %f\n", xm, xv)

	fmt.Printf("Variance of a %d-sided die: %.2f\n", n, lpstats.VarianceN(n))
}

Known Limitations

• Most calculations are based on floating point arithmetic. It is not suitable for arbitrary precision fixed-point decimal arithmetic.

Links

Godoc

Go Report Card

Open Source Insights