stats-lite
v2.2.0
Published
A light statistical package that operates on numeric Arrays.
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stats-lite
A fairly light statistical package. Works with numeric arrays, and will automatically filter out non-numeric values and attempt to convert string numeric values.
Install
npm install stats-lite --save
Example
var stats = require("stats-lite")
var dice = require("dice")
var rolls = []
for (var i = 0; i < 3000; i++) {
rolls.push(dice.sum(dice.roll("2d6")))
}
console.log("sum: %s", stats.sum(rolls))
console.log("mean: %s", stats.mean(rolls))
console.log("median: %s", stats.median(rolls))
console.log("mode: %s", stats.mode(rolls))
console.log("variance: %s", stats.variance(rolls))
console.log("standard deviation: %s", stats.stdev(rolls))
console.log("sample standard deviation: %s", stats.sampleStdev(rolls))
console.log("85th percentile: %s", stats.percentile(rolls, 0.85))
console.log("histogram:", stats.histogram(rolls, 10))
/* Your exact numbers may vary, but they should be pretty similar:
sum: 21041
mean: 7.0136666666666665
median: 7
mode: 7
variance: 5.8568132222220415
standard deviation: 2.4200853749861886
sample standard deviation: 2.4204888234135953
85th percentile: 10
histogram { values: [ 94, 163, 212, 357, 925, 406, 330, 264, 164, 85 ],
bins: 10,
binWidth: 1.05,
binLimits: [ 1.75, 12.25 ] }
*/
Compatibility Notice: Version 2.0.0+ of this library use features that require Node.js v4.0.0 and above
API
All of the exported functions take vals
which is an array of numeric values. Non-numeric values will be removed, and string numbers will be converted to Numbers.
NOTE: This will impact some operations, e.g. mean([null, 1, 2, 3])
will be calculated as mean([1, 2, 3])
, (e.g. 6 / 3 = 2
, NOT 6 / 4 = 1.5
)
numbers(vals)
Accepts an array of values and returns an array consisting of only numeric values from the source array. Converts what it can and filters out anything else. e.g.
numbers(["cat", 1, "22.9", 9])
// [1, 22.9, 9]
sum(vals)
Sum the values in the array.
mean(vals)
Calculate the mean average value of vals
.
median(vals)
Calculate the median average value of vals
.
mode(vals)
Calculate the mode average value of vals
.
If vals
is multi-modal (contains multiple modes), mode(vals)
will return a ES6 Set of the modes.
variance(vals)
Calculate the variance from the mean for a population.
stdev(vals)
Calculate the standard deviation of the values from the mean for a population.
sampleVariance(vals)
Calculate the variance from the mean for a sample.
sampleStdev(vals)
Calculate the standard deviation of the values from the mean for a sample.
percentile(vals, ptile)
Calculate the value representing the desired percentile (0 < ptile <= 1)
. Uses the Estimation method to interpolate non-member percentiles.
histogram(vals[, bins])
Build a histogram representing the distribution of the data in the provided number of bins
. If bins
is not set, it will choose one based on Math.sqrt(vals.length)
. Data will look like:
histogram {
values: [ 86, 159, 253, 335, 907, 405, 339, 270, 146, 100 ],
bins: 10,
binWidth: 1.05,
binLimits: [ 1.75, 12.25 ]
}
Where values
are the bins and the counts of the original values falling in that range. The ranges can be calculated from the binWidth
and binLimits
. For example, the first bin values[0]
in this example is from 1.75 < value <= 2.8
. The third bin values[2]
would be 1.75 + (1.05 * 2) < value <= 1.75 + (1.05 * 3)
or 3.85 < value <= 4.9
.
LICENSE
MIT