als-statistics/lib/table/table-data/index.js

Modular JS statistics toolkit for Node.js and the browser: descriptive stats, correlations (Pearson/Spearman/Kendall), t-tests & ANOVA (Student/Welch), reliability (Cronbach’s alpha), regression (linear/logistic), clustering (DBSCAN/HDBSCAN), and table/co

import Column from '../../column/index.js'
export class TableData {
   static Column = Column
   #colValues = []; #columns = {}; #colNames = []; #n = 0;
   constructor(data, options={}) {
      this.options = options
      if(data) this.#init(data)
   }

   #init(data) {
      if (data instanceof TableData) data = data.columns
      const entries = Array.isArray(data) && data.every(v => typeof v === 'string')
         ? data.map(name => ([name, []])) : Object.entries(data)
      if(entries.length === 0) return
      entries.forEach(([n, v]) => this.#addData(v, n))
      const allExcludes = Array.from(new Set(this.#colValues.map(({ invalid }) => invalid).flat()))
      this.#colValues.forEach(col => {
         const indecesToRemove = allExcludes.filter(i => !col.invalid.includes(i))
         col.values = col.values.filter((v, i) => !indecesToRemove.includes(i))
      })
      this.alignColumns()
   }

   get n() { return this.#n }
   get k() { return this.#colValues.length }
   get colValues() { return this.#colValues }
   get columns() { return this.#columns }
   get colNames() { return this.#colNames }

   alignColumns() {
      if(this.options.alignColumns === false) return
      this.#n = Math.min(...this.#colValues.map(({ n }) => n))
      this.#colValues.forEach(column => {
         if (column.n !== this.#n) column.values = column.values.slice(0, this.#n)
      })
   }

   #addData(values, name, labels) {
      const column = new Column(values, name, labels)
      const colName = name || column.name
      this.#columns[colName] = column
      this.#colValues.push(this.#columns[colName])
      this.#colNames.push(colName)
   }

   #fixRow(row) {
      const colValues = Array.isArray(row) ? row : this.colNames.map(n => row[n])
      .filter(v => typeof v === 'number' && !isNaN(v) && isFinite(v))
      if(colValues.length < this.k) throw new Error(`One of values is not acceptable`)
      return colValues
   }
   addRow(row,index) {
      const colValues = this.#fixRow(row)
      this.colValues.forEach((col,i) => col.insertAt(index,colValues[i]))
      this.#n++
      return this
   }
   addRows(rows,index) { // TODO this method not tested
      const columns = this.colNames.map(v => ([]))
      rows.forEach(row => { this.#fixRow(row).forEach((v,i) => columns[i].push(v)) }); 
      columns.forEach((col,i) => {
         this.colValues[i].insertAt(index,...col)
         this.#n++
      })
      return this 
   }
   deleteRow(index) {
      if(index > this.n-1) throw new Error(`index not exists`)
      this.colValues.forEach(col => col.deleteValue(index))
      this.#n--
   }

   addColumn(name, data, labels) {
      this.#addData(data, name, labels);
      this.alignColumns();
      return this.#columns[name]
   }

   deleteColumn(name) {
      if (!this.#columns[name]) return this
      delete this.#columns[name];
      this.#colNames = this.#colNames.filter(k => k !== name)
      this.#colValues = this.#colValues.filter((s) => s.name !== name)
      return this;
   }
}