@steelbreeze/pivot

pivot

A minimalist pivot table library for TypeScript/JavaScript. While small (just 697 bytes when minified), this library is large in capability, supporting derived and custom dimensions, derived fields for dimensions and calculations, composite dimensions, filtering.

The library also provides a modest set of numerical selectors. Suggestions for additions, or better still contributions, are welcome.

Why create another pivot table library?

There are plenty of pivot table libraries in existence, so why create another one? Well, this is a spin-off from the steelbreeze/landscape project, where instead of aggregating numerical data from the pivot cube, non-numerical data is needed.

Installation

NPM

For installation via the node package manager:

npm i @steelbreeze/pivot

Web

For web via a CDN:

import * as pivot from 'https://cdn.skypack.dev/@steelbreeze/pivot';

Documentation

The documentation can be found here, and more discussion in the Wiki.

Example

The following is the result of pivoting publicly available information about the Fulham Football Club men's squad at the end of the 2020/21 season, calculating the average age of players by position and country.

import * as pivot from '@steelbreeze/pivot';

// create dimensions derived from the squad data
const axes = {
	x: pivot.dimension(pivot.distinct(squad, 'position').sort(), 'position'),
	y: pivot.dimension(pivot.distinct(squad, 'country').sort(), 'country')
};

// create the pivot cube from the squad data using position and country for x and y axes
const cube = pivot.cube(squad, axes);

// find the average age of players by position by country
const result = pivot.map(cube, pivot.average(age));

The selection is the average age of the players grouped by position and country:

        Defend… Forward Goalke… Midfie…
Belgium 32
Camero…                         25
Denmark 24
England 25      23              23.25
France  27              28
Gabon                           27
Jamaica 28      28
Nether… 25
Nigeria 24      22
Portug…         27
Scotla…                         31
Serbia          26
Slovak…                 24
Spain                   33
USA     28

The full example code can be found here.

Alternatively, as can be seen in the web example, non-numerical content can also be queried, mapping the source data to an arbitrary selection:

const result = pivot.map(cube, pivot.select(player => `${player.givenName} ${player.familyName}`));

Resulting in this sort of output:

	Defender	Forward	Goalkeeper	Midfielder
Belgium	Denis Odoi
Cameroon				Andre-Frank Zambo Anguissa
Denmark	Joachim Anderson
England	Tosin Abarabioyo, Joe Bryan	Ademola Lookman		Ruben Loftus-Cheek, Harrison Reed, Josh Onomah, Fabio Carvalho
France	Terence Kongolo		Alphonse Areola
Gabon				Mario Lemina
Jamaica	Michael Hector	Bobby De Cordova-Reid
Netherlands	Kenny Tete
Nigeria	Ola Aina	Josh Maja
Portugal		Ivan Cavaleiro
Scotland				Kevin McDonald, Tom Cairney
Serbia		Aleksander Mitrovic
Slovakia			Marek Rodak
Spain			Fabrico Agosto Ramirez
USA	Tim Ream, Antonee Robinson

Data and calculations correct as of: 2021-05-23.