als-statistics/lib/column/index.js

A powerful and lightweight JavaScript library for descriptive statistics, regression, clustering, outlier detection, and noise analysis using a flexible table/column architecture.

const BaseColumn = require('./base');
class Column extends BaseColumn {
   constructor(values, columnFilter) {
      super(values, columnFilter)
   }

   clone(filtered=true,table) { return new this.constructor(filtered ? this.values : this._values,table) }
   get frequencies() { // Absolute frequencies for each unique value
      return this.cached('absoluteFrequencies', () => {
         const freq = new Map();
         for (const v of this.values) { freq.set(v, (freq.get(v) || 0) + 1) }
         return Object.fromEntries(freq);
      });
   }

   get relativeFrequencies() { // Relative frequencies (the proportion of each value relative to the total)
      return this.cached('relativeFrequencies', () => {
         const { frequencies, n } = this, relFreq = {};
         for (const key in frequencies) { relFreq[key] = frequencies[key] / n }
         return relFreq;
      });
   }

   get sorted() {
      return this.cached('sorted', () => {
         const valuesCopy = this.values.slice();
         if (valuesCopy.length === 0) return valuesCopy;
         if (this.type === Number) return valuesCopy.sort((a, b) => a - b);
         return valuesCopy.sort((a, b) => String(a).localeCompare(String(b)));
      });
   }

   percentile(p) {
      const { sorted, n } = this
      if (p < 0 || p > 100) throw new Error("Percentile must be between 0 and 100");
      if (p === 0) return sorted[0];
      if (p === 100) return sorted[n - 1];

      const index = Math.floor((p / 100) * (n - 1)); // Берем нижний индекс
      return sorted[index]; // Возвращаем число без усреднения
   }
   get median() { return this.cached('median', () => this.percentile(50)) }
   get q1() { return this.cached('q1', () => this.percentile(25)) }
   get q3() { return this.cached('q3', () => this.percentile(75)) }
}

module.exports = Column