SheetJS Community Edition - Spreadsheet Data Toolkit


The SheetJS Community Edition offers battle-tested open-source solutions for extracting useful data from almost any complex spreadsheet and generating new spreadsheets that will work with legacy and modern software alike.

SheetJS Pro offers solutions beyond data processing: Edit complex templates with ease; let out your inner Picasso with styling; make custom sheets with images/graphs/PivotTables; evaluate formula expressions and port calculations to web apps; automate common spreadsheet tasks, and much more! Analytics

Browser Test and Support Matrix

Build Status

Supported File Formats

circo graph of format support

Diagram Legend (click to show)

graph legend

Table of Contents

Expand to show Table of Contents

Getting Started


The complete browser standalone build is saved to dist/xlsx.full.min.js and can be directly added to a page with a script tag:

<script lang="javascript" src="dist/xlsx.full.min.js"></script>

CDN Availability (click to show)


For example, unpkg makes the latest version available at:

<script src=""></script>

Browser builds (click to show)

The complete single-file version is generated at dist/xlsx.full.min.js

A slimmer build is generated at dist/ Compared to full build:

  • codepage library skipped (no support for XLS encodings)
  • XLSX compression option not currently available
  • no support for XLSB / XLS / Lotus 1-2-3 / SpreadsheetML 2003
  • node stream utils removed

Webpack and Browserify builds include optional modules by default. Webpack can be configured to remove support with resolve.alias:

  /* uncomment the lines below to remove support */
  resolve: {
    alias: { "./dist/cpexcel.js": "" } // <-- omit international support

With npm:

$ npm install xlsx

With bower:

$ bower install js-xlsx

dist/xlsx.extendscript.js is an ExtendScript build for Photoshop and InDesign that is included in the npm package. It can be directly referenced with a #include directive:

#include "xlsx.extendscript.js"

Internet Explorer and ECMAScript 3 Compatibility (click to show)

For broad compatibility with JavaScript engines, the library is written using ECMAScript 3 language dialect as well as some ES5 features like Array#forEach. Older browsers require shims to provide missing functions.

To use the shim, add the shim before the script tag that loads xlsx.js:

<!-- add the shim first -->
<script type="text/javascript" src="shim.min.js"></script>
<!-- after the shim is referenced, add the library -->
<script type="text/javascript" src="xlsx.full.min.js"></script>

The script also includes IE_LoadFile and IE_SaveFile for loading and saving files in Internet Explorer versions 6-9. The xlsx.extendscript.js script bundles the shim in a format suitable for Photoshop and other Adobe products.


Most scenarios involving spreadsheets and data can be broken into 5 parts:

Acquire Data: Data may be stored anywhere: local or remote files, databases, HTML TABLE, or even generated programmatically in the web browser.

Extract Data: For spreadsheet files, this involves parsing raw bytes to read the cell data. For general JS data, this involves reshaping the data.

Process Data: From generating summary statistics to cleaning data records, this step is the heart of the problem.

Package Data: This can involve making a new spreadsheet or serializing with JSON.stringify or writing XML or simply flattening data for UI tools.

Release Data: Spreadsheet files can be uploaded to a server or written locally. Data can be presented to users in an HTML TABLE or data grid.

A common problem involves generating a valid spreadsheet export from data stored in an HTML table. In this example, an HTML TABLE on the page will be scraped, a row will be added to the bottom with the date of the report, and a new file will be generated and downloaded locally. XLSX.writeFile takes care of packaging the data and attempting a local download:

// Acquire Data (reference to the HTML table)
var table_elt = document.getElementById("my-table-id");

// Extract Data (create a workbook object from the table)
var workbook = XLSX.utils.table_to_book(table_elt);

// Process Data (add a new row)
var ws = workbook.Sheets["Sheet1"];
XLSX.utils.sheet_add_aoa(ws, [["Created "+new Date().toISOString()]], {origin:-1});

// Package and Release Data (`writeFile` tries to write and save an XLSB file)
XLSX.writeFile(workbook, "Report.xlsb");

This library tries to simplify steps 2 and 4 with functions to extract useful data from spreadsheet files (read / readFile) and generate new spreadsheet files from data (write / writeFile). Additional utility functions like table_to_book work with other common data sources like HTML tables.

This documentation and various demo projects cover a number of common scenarios and approaches for steps 1 and 5.

Utility functions help with step 3.

The Zen of SheetJS

Data processing should fit in any workflow

The library does not impose a separate lifecycle. It fits nicely in websites and apps built using any framework. The plain JS data objects play nice with Web Workers and future APIs.

"Acquiring and Extracting Data" describes solutions for common data import scenarios.

"Writing Workbooks" describes solutions for common data export scenarios involving actual spreadsheet files.

"Utility Functions" details utility functions for translating JSON Arrays and other common JS structures into worksheet objects.

JavaScript is a powerful language for data processing

The "Common Spreadsheet Format" is a simple object representation of the core concepts of a workbook. The various functions in the library provide low-level tools for working with the object.

For friendly JS processing, there are utility functions for converting parts of a worksheet to/from an Array of Arrays. The following example combines powerful JS Array methods with a network request library to download data, select the information we want and create a workbook file:

Get Data from a JSON Endpoint and Generate a Workbook (click to show)

The goal is to generate a XLSB workbook of US President names and birthdays.

Acquire Data

Raw Data has the desired data. For example, John Adams:

  "id": { /* (data omitted) */ },
  "name": {
    "first": "John",          // <-- first name
    "last": "Adams"           // <-- last name
  "bio": {
    "birthday": "1735-10-19", // <-- birthday
    "gender": "M"
  "terms": [
    { "type": "viceprez", /* (other fields omitted) */ },
    { "type": "viceprez", /* (other fields omitted) */ },
    { "type": "prez", /* (other fields omitted) */ } // <-- look for "prez"

Filtering for Presidents

The dataset includes Aaron Burr, a Vice President who was never President!

Array#filter creates a new array with the desired rows. A President served at least one term with type set to "prez". To test if a particular row has at least one "prez" term, Array#some is another native JS function. The complete filter would be:

const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez"));

Lining up the data

For this example, the name will be the first name combined with the last name ( + " " + and the birthday will be the subfield Using Array#map, the dataset can be massaged in one call:

const rows = => ({
  name: + " " +,

The result is an array of "simple" objects with no nesting:

  { name: "George Washington", birthday: "1732-02-22" },
  { name: "John Adams", birthday: "1735-10-19" },
  // ... one row per President

Extract Data

With the cleaned dataset, XLSX.utils.json_to_sheet generates a worksheet:

const worksheet = XLSX.utils.json_to_sheet(rows);

XLSX.utils.book_new creates a new workbook and XLSX.utils.book_append_sheet appends a worksheet to the workbook. The new worksheet will be called "Dates":

const workbook = XLSX.utils.book_new();
XLSX.utils.book_append_sheet(workbook, worksheet, "Dates");

Process Data

Fixing headers

By default, json_to_sheet creates a worksheet with a header row. In this case, the headers come from the JS object keys: "name" and "birthday".

The headers are in cells A1 and B1. XLSX.utils.sheet_add_aoa can write text values to the existing worksheet starting at cell A1:

XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" });

Fixing Column Widths

Some of the names are longer than the default column width. Column widths are set by setting the "!cols" worksheet property.

The following line sets the width of column A to approximately 10 characters:

worksheet["!cols"] = [ { wch: 10 } ]; // set column A width to 10 characters

One Array#reduce call over rows can calculate the maximum width:

const max_width = rows.reduce((w, r) => Math.max(w,, 10);
worksheet["!cols"] = [ { wch: max_width } ];

Note: If the starting point was a file or HTML table, XLSX.utils.sheet_to_json will generate an array of JS objects.

Package and Release Data

XLSX.writeFile creates a spreadsheet file and tries to write it to the system. In the browser, it will try to prompt the user to download the file. In NodeJS, it will write to the local directory.

XLSX.writeFile(workbook, "Presidents.xlsx");

Complete Example

// Uncomment the next line for use in NodeJS:
// const XLSX = require("xlsx"), axios = require("axios");

(async() => {
  /* fetch JSON data and parse */
  const url = "";
  const raw_data = (await axios(url, {responseType: "json"})).data;

  /* filter for the Presidents */
  const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez"));

  /* flatten objects */
  const rows = => ({
    name: + " " +,

  /* generate worksheet and workbook */
  const worksheet = XLSX.utils.json_to_sheet(rows);
  const workbook = XLSX.utils.book_new();
  XLSX.utils.book_append_sheet(workbook, worksheet, "Dates");

  /* fix headers */
  XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" });

  /* calculate column width */
  const max_width = rows.reduce((w, r) => Math.max(w,, 10);
  worksheet["!cols"] = [ { wch: max_width } ];

  /* create an XLSX file and try to save to Presidents.xlsx */
  XLSX.writeFile(workbook, "Presidents.xlsx");

For use in the web browser, assuming the snippet is saved to snippet.js, script tags should be used to include the axios and xlsx standalone builds:

<script src=""></script>
<script src=""></script>
<script src="snippet.js"></script>

File formats are implementation details

The parser covers a wide gamut of common spreadsheet file formats to ensure that "HTML-saved-as-XLS" files work as well as actual XLS or XLSX files.

The writer supports a number of common output formats for broad compatibility with the data ecosystem.

To the greatest extent possible, data processing code should not have to worry about the specific file formats involved.

JS Ecosystem Demos

The demos directory includes sample projects for:

Frameworks and APIs

Bundlers and Tooling

Platforms and Integrations

Other examples are included in the showcase.

Acquiring and Extracting Data

Parsing Workbooks


Extract data from spreadsheet bytes

var workbook =, opts);

The read method can extract data from spreadsheet bytes stored in a JS string, "binary string", NodeJS buffer or typed array (Uint8Array or ArrayBuffer).

Read spreadsheet bytes from a local file and extract data

var workbook = XLSX.readFile(filename, opts);

The readFile method attempts to read a spreadsheet file at the supplied path. Browsers generally do not allow reading files in this way (it is deemed a security risk), and attempts to read files in this way will throw an error.

The second opts argument is optional. "Parsing Options" covers the supported properties and behaviors.


Here are a few common scenarios (click on each subtitle to see the code):

Local file in a NodeJS server (click to show)

readFile uses fs.readFileSync under the hood:

var XLSX = require("xlsx");

var workbook = XLSX.readFile("test.xlsx");

For Node ESM, the readFile helper is not enabled. Instead, fs.readFileSync should be used to read the file data as a Buffer for use with

import { readFileSync } from "fs";
import { read } from "xlsx/xlsx.mjs";

const buf = readFileSync("test.xlsx");
/* buf is a Buffer */
const workbook = read(buf);

User-submitted file in a web page ("Drag-and-Drop") (click to show)

For modern websites targeting Chrome 76+, File#arrayBuffer is recommended:

// XLSX is a global from the standalone script

async function handleDropAsync(e) {
  e.stopPropagation(); e.preventDefault();
  const f = e.dataTransfer.files[0];
  /* f is a File */
  const data = await f.arrayBuffer();
  /* data is an ArrayBuffer */
  const workbook =;

  /* DO SOMETHING WITH workbook HERE */
drop_dom_element.addEventListener("drop", handleDropAsync, false);

For maximal compatibility, the FileReader API should be used:

function handleDrop(e) {
  e.stopPropagation(); e.preventDefault();
  var f = e.dataTransfer.files[0];
  /* f is a File */
  var reader = new FileReader();
  reader.onload = function(e) {
    var data =;
    /* reader.readAsArrayBuffer(file) -> data will be an ArrayBuffer */
    var workbook =;

    /* DO SOMETHING WITH workbook HERE */
drop_dom_element.addEventListener("drop", handleDrop, false); demonstrates the FileReader technique.

User-submitted file with an HTML INPUT element (click to show)

Starting with an HTML INPUT element with type="file":

<input type="file" id="input_dom_element">

For modern websites targeting Chrome 76+, Blob#arrayBuffer is recommended:

// XLSX is a global from the standalone script

async function handleFileAsync(e) {
  const file =[0];
  const data = await file.arrayBuffer();
  /* data is an ArrayBuffer */
  const workbook =;

  /* DO SOMETHING WITH workbook HERE */
input_dom_element.addEventListener("change", handleFileAsync, false);

For broader support (including IE10+), the FileReader approach is recommended:

function handleFile(e) {
  var file =[0];
  var reader = new FileReader();
  reader.onload = function(e) {
    var data =;
    /* reader.readAsArrayBuffer(file) -> data will be an ArrayBuffer */
    var workbook =;

    /* DO SOMETHING WITH workbook HERE */
input_dom_element.addEventListener("change", handleFile, false);

The oldie demo shows an IE-compatible fallback scenario.

Fetching a file in the web browser ("Ajax") (click to show)

For modern websites targeting Chrome 42+, fetch is recommended:

// XLSX is a global from the standalone script

(async() => {
  const url = "";
  const data = await (await fetch(url)).arrayBuffer();
  /* data is an ArrayBuffer */
  const workbook =;

  /* DO SOMETHING WITH workbook HERE */

For broader support, the XMLHttpRequest approach is recommended:

var url = "";

/* set up async GET request */
var req = new XMLHttpRequest();"GET", url, true);
req.responseType = "arraybuffer";

req.onload = function(e) {
  var workbook =;

  /* DO SOMETHING WITH workbook HERE */


The xhr demo includes a longer discussion and more examples. shows fallback approaches for IE6+.

Local file in a PhotoShop or InDesign plugin (click to show)

readFile wraps the File logic in Photoshop and other ExtendScript targets. The specified path should be an absolute path:

#include "xlsx.extendscript.js"

/* Read test.xlsx from the Documents folder */
var workbook = XLSX.readFile(Folder.myDocuments + "/test.xlsx");

The extendscript demo includes a more complex example.

Local file in an Electron app (click to show)

readFile can be used in the renderer process:

/* From the renderer process */
var XLSX = require("xlsx");

var workbook = XLSX.readFile(path);

Electron APIs have changed over time. The electron demo shows a complete example and details the required version-specific settings.

Local file in a mobile app with React Native (click to show)

The react demo includes a sample React Native app.

Since React Native does not provide a way to read files from the filesystem, a third-party library must be used. The following libraries have been tested:

The base64 encoding returns strings compatible with the base64 type:

import XLSX from "xlsx";
import { FileSystem } from "react-native-file-access";

const b64 = await FileSystem.readFile(path, "base64");
/* b64 is a base64 string */
const workbook =, {type: "base64"});

The ascii encoding returns binary strings compatible with the binary type:

import XLSX from "xlsx";
import { readFile } from "react-native-fs";

const bstr = await readFile(path, "ascii");
/* bstr is a binary string */
const workbook =, {type: "binary"});

NodeJS Server File Uploads (click to show)

read can accept a NodeJS buffer. readFile can read files generated by a HTTP POST request body parser like formidable:

const XLSX = require("xlsx");
const http = require("http");
const formidable = require("formidable");

const server = http.createServer((req, res) => {
  const form = new formidable.IncomingForm();
  form.parse(req, (err, fields, files) => {
    /* grab the first file */
    const f = Object.entries(files)[0][1];
    const path = f.filepath;
    const workbook = XLSX.readFile(path);

    /* DO SOMETHING WITH workbook HERE */
}).listen(process.env.PORT || 7262);

The server demo has more advanced examples.

Download files in a NodeJS process (click to show)

Node 17.5 and 18.0 have native support for fetch:

const XLSX = require("xlsx");

const data = await (await fetch(url)).arrayBuffer();
/* data is an ArrayBuffer */
const workbook =;

For broader compatibility, third-party modules are recommended.

request requires a null encoding to yield Buffers:

var XLSX = require("xlsx");
var request = require("request");

request({url: url, encoding: null}, function(err, resp, body) {
  var workbook =;

  /* DO SOMETHING WITH workbook HERE */

axios works the same way in browser and in NodeJS:

const XLSX = require("xlsx");
const axios = require("axios");

(async() => {
  const res = await axios.get(url, {responseType: "arraybuffer"});
  /* is a Buffer */
  const workbook =;

  /* DO SOMETHING WITH workbook HERE */

Download files in an Electron app (click to show)

The net module in the main process can make HTTP/HTTPS requests to external resources. Responses should be manually concatenated using Buffer.concat:

const XLSX = require("xlsx");
const { net } = require("electron");

const req = net.request(url);
req.on("response", (res) => {
  const bufs = []; // this array will collect all of the buffers
  res.on("data", (chunk) => { bufs.push(chunk); });
  res.on("end", () => {
    const workbook =;

    /* DO SOMETHING WITH workbook HERE */

Readable Streams in NodeJS (click to show)

When dealing with Readable Streams, the easiest approach is to buffer the stream and process the whole thing at the end:

var fs = require("fs");
var XLSX = require("xlsx");

function process_RS(stream, cb) {
  var buffers = [];
  stream.on("data", function(data) { buffers.push(data); });
  stream.on("end", function() {
    var buffer = Buffer.concat(buffers);
    var workbook =, {type:"buffer"});


ReadableStream in the browser (click to show)

When dealing with ReadableStream, the easiest approach is to buffer the stream and process the whole thing at the end:

// XLSX is a global from the standalone script

async function process_RS(stream) {
  /* collect data */
  const buffers = [];
  const reader = stream.getReader();
  for(;;) {
    const res = await;
    if(res.value) buffers.push(res.value);
    if(res.done) break;

  /* concat */
  const out = new Uint8Array(buffers.reduce((acc, v) => acc + v.length, 0));

  let off = 0;
  for(const u8 of arr) {
    out.set(u8, off);
    off += u8.length;

  return out;

const data = await process_RS(stream);
/* data is Uint8Array */
const workbook =;

More detailed examples are covered in the included demos

Processing JSON and JS Data

JSON and JS data tend to represent single worksheets. This section will use a few utility functions to generate workbooks:

Create a new Worksheet

var workbook = XLSX.utils.book_new();

The book_new utility function creates an empty workbook with no worksheets.

Append a Worksheet to a Workbook

XLSX.utils.book_append_sheet(workbook, worksheet, sheet_name);

The book_append_sheet utility function appends a worksheet to the workbook. The third argument specifies the desired worksheet name. Multiple worksheets can be added to a workbook by calling the function multiple times.


Create a worksheet from an array of arrays of JS values

var worksheet = XLSX.utils.aoa_to_sheet(aoa, opts);

The aoa_to_sheet utility function walks an "array of arrays" in row-major order, generating a worksheet object. The following snippet generates a sheet with cell A1 set to the string A1, cell B1 set to B2, etc:

var worksheet = XLSX.utils.aoa_to_sheet([
  ["A1", "B1", "C1"],
  ["A2", "B2", "C2"],
  ["A3", "B3", "C3"]

"Array of Arrays Input" describes the function and the optional opts argument in more detail.

Create a worksheet from an array of JS objects

var worksheet = XLSX.utils.json_to_sheet(jsa, opts);

The json_to_sheet utility function walks an array of JS objects in order, generating a worksheet object. By default, it will generate a header row and one row per object in the array. The optional opts argument has settings to control the column order and header output.

"Array of Objects Input" describes the function and the optional opts argument in more detail.


"Zen of SheetJS" contains a detailed example "Get Data from a JSON Endpoint and Generate a Workbook"

The database demo includes examples of working with databases and query results.

Processing HTML Tables


Create a worksheet by scraping an HTML TABLE in the page

var worksheet = XLSX.utils.table_to_sheet(dom_element, opts);

The table_to_sheet utility function takes a DOM TABLE element and iterates through the rows to generate a worksheet. The opts argument is optional. "HTML Table Input" describes the function in more detail.

Create a workbook by scraping an HTML TABLE in the page

var workbook = XLSX.utils.table_to_book(dom_element, opts);

The table_to_book utility function follows the same logic as table_to_sheet. After generating a worksheet, it creates a blank workbook and appends the spreadsheet.

The options argument supports the same options as table_to_sheet, with the addition of a sheet property to control the worksheet name. If the property is missing or no options are specified, the default name Sheet1 is used.


Here are a few common scenarios (click on each subtitle to see the code):

HTML TABLE element in a webpage (click to show)

<!-- include the standalone script and shim.  this uses the UNPKG CDN -->
<script src=""></script>
<script src=""></script>

<!-- example table with id attribute -->
<table id="tableau">

<!-- this block should appear after the table HTML and the standalone script -->
<script type="text/javascript">
  var workbook = XLSX.utils.table_to_book(document.getElementById("tableau"));

  /* DO SOMETHING WITH workbook HERE */

Multiple tables on a web page can be converted to individual worksheets:

/* create new workbook */
var workbook = XLSX.utils.book_new();

/* convert table "table1" to worksheet named "Sheet1" */
var sheet1 = XLSX.utils.table_to_sheet(document.getElementById("table1"));
XLSX.utils.book_append_sheet(workbook, sheet1, "Sheet1");

/* convert table "table2" to worksheet named "Sheet2" */
var sheet2 = XLSX.utils.table_to_sheet(document.getElementById("table2"));
XLSX.utils.book_append_sheet(workbook, sheet2, "Sheet2");

/* workbook now has 2 worksheets */

Alternatively, the HTML code can be extracted and parsed:

var htmlstr = document.getElementById("tableau").outerHTML;
var workbook =, {type:"string"});

Chrome/Chromium Extension (click to show)

The chrome demo shows a complete example and details the required permissions and other settings.

In an extension, it is recommended to generate the workbook in a content script and pass the object back to the extension:

/* in the worker script */
chrome.runtime.onMessage.addListener(function(msg, sender, cb) {
  /* pass a message like { sheetjs: true } from the extension to scrape */
  if(!msg || !msg.sheetjs) return;
  /* create a new workbook */
  var workbook = XLSX.utils.book_new();
  /* loop through each table element */
  var tables = document.getElementsByTagName("table")
  for(var i = 0; i < tables.length; ++i) {
    var worksheet = XLSX.utils.table_to_sheet(tables[i]);
    XLSX.utils.book_append_sheet(workbook, worksheet, "Table" + i);
  /* pass back to the extension */
  return cb(workbook);

Working with the Workbook

The full object format is described later in this README.

Reading a specific cell (click to show)

This example extracts the value stored in cell A1 from the first worksheet:

var first_sheet_name = workbook.SheetNames[0];
var address_of_cell = 'A1';

/* Get worksheet */
var worksheet = workbook.Sheets[first_sheet_name];

/* Find desired cell */
var desired_cell = worksheet[address_of_cell];

/* Get the value */
var desired_value = (desired_cell ? desired_cell.v : undefined);

Adding a new worksheet to a workbook (click to show)

This example uses XLSX.utils.aoa_to_sheet to make a sheet and XLSX.utils.book_append_sheet to append the sheet to the workbook:

var ws_name = "SheetJS";

/* make worksheet */
var ws_data = [
  [ "S", "h", "e", "e", "t", "J", "S" ],
  [  1 ,  2 ,  3 ,  4 ,  5 ]
var ws = XLSX.utils.aoa_to_sheet(ws_data);

/* Add the worksheet to the workbook */
XLSX.utils.book_append_sheet(wb, ws, ws_name);

Creating a new workbook from scratch (click to show)

The workbook object contains a SheetNames array of names and a Sheets object mapping sheet names to sheet objects. The XLSX.utils.book_new utility function creates a new workbook object:

/* create a new blank workbook */
var wb = XLSX.utils.book_new();

The new workbook is blank and contains no worksheets. The write functions will error if the workbook is empty.

Parsing and Writing Examples read + modify + write files node

The node version installs a command line tool xlsx which can read spreadsheet files and output the contents in various formats. The source is available at xlsx.njs in the bin directory.

Some helper functions in XLSX.utils generate different views of the sheets:

  • XLSX.utils.sheet_to_csv generates CSV
  • XLSX.utils.sheet_to_txt generates UTF16 Formatted Text
  • XLSX.utils.sheet_to_html generates HTML
  • XLSX.utils.sheet_to_json generates an array of objects
  • XLSX.utils.sheet_to_formulae generates a list of formulae

Writing Workbooks

For writing, the first step is to generate output data. The helper functions write and writeFile will produce the data in various formats suitable for dissemination. The second step is to actual share the data with the end point. Assuming workbook is a workbook object:

nodejs write a file (click to show)

XLSX.writeFile uses fs.writeFileSync in server environments:

if(typeof require !== 'undefined') XLSX = require('xlsx');
/* output format determined by filename */
XLSX.writeFile(workbook, 'out.xlsb');
/* at this point, out.xlsb is a file that you can distribute */

Photoshop ExtendScript write a file (click to show)

writeFile wraps the File logic in Photoshop and other ExtendScript targets. The specified path should be an absolute path:

#include "xlsx.extendscript.js"
/* output format determined by filename */
XLSX.writeFile(workbook, 'out.xlsx');
/* at this point, out.xlsx is a file that you can distribute */

The extendscript demo includes a more complex example.

Browser add TABLE element to page (click to show)

The sheet_to_html utility function generates HTML code that can be added to any DOM element.

var worksheet = workbook.Sheets[workbook.SheetNames[0]];
var container = document.getElementById('tableau');
container.innerHTML = XLSX.utils.sheet_to_html(worksheet);

Browser upload file (ajax) (click to show)

A complete example using XHR is included in the XHR demo, along with examples for fetch and wrapper libraries. This example assumes the server can handle Base64-encoded files (see the demo for a basic nodejs server):

/* in this example, send a base64 string to the server */
var wopts = { bookType:'xlsx', bookSST:false, type:'base64' };

var wbout = XLSX.write(workbook,wopts);

var req = new XMLHttpRequest();"POST", "/upload", true);
var formdata = new FormData();
formdata.append('file', 'test.xlsx'); // <-- server expects `file` to hold name
formdata.append('data', wbout); // <-- `data` holds the base64-encoded data

Browser save file (click to show)

XLSX.writeFile wraps a few techniques for triggering a file save:

  • URL browser API creates an object URL for the file, which the library uses by creating a link and forcing a click. It is supported in modern browsers.
  • msSaveBlob is an IE10+ API for triggering a file save.
  • IE_FileSave uses VBScript and ActiveX to write a file in IE6+ for Windows XP and Windows 7. The shim must be included in the containing HTML page.

There is no standard way to determine if the actual file has been downloaded.

/* output format determined by filename */
XLSX.writeFile(workbook, 'out.xlsb');
/* at this point, out.xlsb will have been downloaded */

Browser save file (compatibility) (click to show)

XLSX.writeFile techniques work for most modern browsers as well as older IE. For much older browsers, there are workarounds implemented by wrapper libraries.

FileSaver.js implements saveAs. Note: XLSX.writeFile will automatically call saveAs if available.

/* bookType can be any supported output type */
var wopts = { bookType:'xlsx', bookSST:false, type:'array' };

var wbout = XLSX.write(workbook,wopts);

/* the saveAs call downloads a file on the local machine */
saveAs(new Blob([wbout],{type:"application/octet-stream"}), "test.xlsx");

Downloadify uses a Flash SWF button to generate local files, suitable for environments where ActiveX is unavailable:

    /* other options are required! read the downloadify docs for more info */
    filename: "test.xlsx",
    data: function() { return XLSX.write(wb, {bookType:"xlsx", type:'base64'}); },
    append: false,
    dataType: 'base64'

The oldie demo shows an IE-compatible fallback scenario.

The included demos cover mobile apps and other special deployments.

Writing Examples

Streaming Write

The streaming write functions are available in the object. They take the same arguments as the normal write functions but return a Readable Stream. They are only exposed in NodeJS.

  • is the streaming version of XLSX.utils.sheet_to_csv.
  • is the streaming version of XLSX.utils.sheet_to_html.
  • is the streaming version of XLSX.utils.sheet_to_json.

nodejs convert to CSV and write file (click to show)

var output_file_name = "out.csv";
var stream =;

nodejs write JSON stream to screen (click to show)

/* to_json returns an object-mode stream */
var stream =, {raw:true});

/* the following stream converts JS objects to text via JSON.stringify */
var conv = new Transform({writableObjectMode:true});
conv._transform = function(obj, e, cb){ cb(null, JSON.stringify(obj) + "\n"); };

stream.pipe(conv); conv.pipe(process.stdout); pipes write streams to nodejs response.


XLSX is the exposed variable in the browser and the exported node variable

XLSX.version is the version of the library (added by the build script).

XLSX.SSF is an embedded version of the format library.

Parsing functions, read_opts) attempts to parse data.

XLSX.readFile(filename, read_opts) attempts to read filename and parse.

Parse options are described in the Parsing Options section.

Writing functions

XLSX.write(wb, write_opts) attempts to write the workbook wb

XLSX.writeFile(wb, filename, write_opts) attempts to write wb to filename. In browser-based environments, it will attempt to force a client-side download.

XLSX.writeFileAsync(wb, filename, o, cb) attempts to write wb to filename. If o is omitted, the writer will use the third argument as the callback. contains a set of streaming write functions.

Write options are described in the Writing Options section.


Utilities are available in the XLSX.utils object and are described in the Utility Functions section:


  • book_new creates an empty workbook
  • book_append_sheet adds a worksheet to a workbook


  • aoa_to_sheet converts an array of arrays of JS data to a worksheet.
  • json_to_sheet converts an array of JS objects to a worksheet.
  • table_to_sheet converts a DOM TABLE element to a worksheet.
  • sheet_add_aoa adds an array of arrays of JS data to an existing worksheet.
  • sheet_add_json adds an array of JS objects to an existing worksheet.


  • sheet_to_json converts a worksheet object to an array of JSON objects.
  • sheet_to_csv generates delimiter-separated-values output.
  • sheet_to_txt generates UTF16 formatted text.
  • sheet_to_html generates HTML output.
  • sheet_to_formulae generates a list of the formulae (with value fallbacks).

Cell and cell address manipulation:

  • format_cell generates the text value for a cell (using number formats).
  • encode_row / decode_row converts between 0-indexed rows and 1-indexed rows.
  • encode_col / decode_col converts between 0-indexed columns and column names.
  • encode_cell / decode_cell converts cell addresses.
  • encode_range / decode_range converts cell ranges.

Common Spreadsheet Format

SheetJS conforms to the Common Spreadsheet Format (CSF):

General Structures

Cell address objects are stored as {c:C, r:R} where C and R are 0-indexed column and row numbers, respectively. For example, the cell address B5 is represented by the object {c:1, r:4}.

Cell range objects are stored as {s:S, e:E} where S is the first cell and E is the last cell in the range. The ranges are inclusive. For example, the range A3:B7 is represented by the object {s:{c:0, r:2}, e:{c:1, r:6}}. Utility functions perform a row-major order walk traversal of a sheet range:

for(var R = range.s.r; R <= range.e.r; ++R) {
  for(var C = range.s.c; C <= range.e.c; ++C) {
    var cell_address = {c:C, r:R};
    /* if an A1-style address is needed, encode the address */
    var cell_ref = XLSX.utils.encode_cell(cell_address);

Cell Object

Cell objects are plain JS objects with keys and values following the convention:

vraw value (see Data Types section for more info)
wformatted text (if applicable)
ttype: b Boolean, e Error, n Number, d Date, s Text, z Stub
fcell formula encoded as an A1-style string (if applicable)
Frange of enclosing array if formula is array formula (if applicable)
rrich text encoding (if applicable)
hHTML rendering of the rich text (if applicable)
ccomments associated with the cell
znumber format string associated with the cell (if requested)
lcell hyperlink object (.Target holds link, .Tooltip is tooltip)
sthe style/theme of the cell (if applicable)

Built-in export utilities (such as the CSV exporter) will use the w text if it is available. To change a value, be sure to delete cell.w (or set it to undefined) before attempting to export. The utilities will regenerate the w text from the number format (cell.z) and the raw value if possible.

The actual array formula is stored in the f field of the first cell in the array range. Other cells in the range will omit the f field.

Data Types

The raw value is stored in the v value property, interpreted based on the t type property. This separation allows for representation of numbers as well as numeric text. There are 6 valid cell types:

bBoolean: value interpreted as JS boolean
eError: value is a numeric code and w property stores common name **
nNumber: value is a JS number **
dDate: value is a JS Date object or string to be parsed as Date **
sText: value interpreted as JS string and written as text **
zStub: blank stub cell that is ignored by data processing utilities **

Error values and interpretation (click to show)

ValueError Meaning

Type n is the Number type. This includes all forms of data that Excel stores as numbers, such as dates/times and Boolean fields. Excel exclusively uses data that can be fit in an IEEE754 floating point number, just like JS Number, so the v field holds the raw number. The w field holds formatted text. Dates are stored as numbers by default and converted with XLSX.SSF.parse_date_code.

Type d is the Date type, generated only when the option cellDates is passed. Since JSON does not have a natural Date type, parsers are generally expected to store ISO 8601 Date strings like you would get from date.toISOString(). On the other hand, writers and exporters should be able to handle date strings and JS Date objects. Note that Excel disregards timezone modifiers and treats all dates in the local timezone. The library does not correct for this error.

Type s is the String type. Values are explicitly stored as text. Excel will interpret these cells as "number stored as text". Generated Excel files automatically suppress that class of error, but other formats may elicit errors.

Type z represents blank stub cells. They are generated in cases where cells have no assigned value but hold comments or other metadata. They are ignored by the core library data processing utility functions. By default these cells are not generated; the parser sheetStubs option must be set to true.


Excel Date Code details (click to show)

By default, Excel stores dates as numbers with a format code that specifies date processing. For example, the date 19-Feb-17 is stored as the number 42785 with a number format of d-mmm-yy. The SSF module understands number formats and performs the appropriate conversion.

XLSX also supports a special date type d where the data is an ISO 8601 date string. The formatter converts the date back to a number.

The default behavior for all parsers is to generate number cells. Setting cellDates to true will force the generators to store dates.

Time Zones and Dates (click to show)

Excel has no native concept of universal time. All times are specified in the local time zone. Excel limitations prevent specifying true absolute dates.

Following Excel, this library treats all dates as relative to local time zone.

Epochs: 1900 and 1904 (click to show)

Excel supports two epochs (January 1 1900 and January 1 1904). The workbook's epoch can be determined by examining the workbook's wb.Workbook.WBProps.date1904 property:


Sheet Objects

Each key that does not start with ! maps to a cell (using A-1 notation)

sheet[address] returns the cell object for the specified address.

Special sheet keys (accessible as sheet[key], each starting with !):

sheet['!ref']: A-1 based range representing the sheet range. Functions that work with sheets should use this parameter to determine the range. Cells that are assigned outside of the range are not processed. In particular, when writing a sheet by hand, cells outside of the range are not included

Functions that handle sheets should test for the presence of !ref field. If the !ref is omitted or is not a valid range, functions are free to treat the sheet as empty or attempt to guess the range. The standard utilities that ship with this library treat sheets as empty (for example, the CSV output is empty string).

When reading a worksheet with the sheetRows property set, the ref parameter will use the restricted range. The original range is set at ws['!fullref']

sheet['!margins']: Object representing the page margins. The default values follow Excel's "normal" preset. Excel also has a "wide" and a "narrow" preset but they are stored as raw measurements. The main properties are listed below:

Page margin details (click to show)

leftleft margin (inches)
rightright margin (inches)
toptop margin (inches)0.751.00.75
bottombottom margin (inches)0.751.00.75
headerheader margin (inches)
footerfooter margin (inches)
/* Set worksheet sheet to "normal" */
ws["!margins"]={left:0.7, right:0.7, top:0.75,bottom:0.75,header:0.3,footer:0.3}
/* Set worksheet sheet to "wide" */
ws["!margins"]={left:1.0, right:1.0, top:1.0, bottom:1.0, header:0.5,footer:0.5}
/* Set worksheet sheet to "narrow" */

Worksheet Object

In addition to the base sheet keys, worksheets also add:

ws['!cols']: array of column properties objects. Column widths are actually stored in files in a normalized manner, measured in terms of the "Maximum Digit Width" (the largest width of the rendered digits 0-9, in pixels). When parsed, the column objects store the pixel width in the wpx field, character width in the wch field, and the maximum digit width in the MDW field.

ws['!rows']: array of row properties objects as explained later in the docs. Each row object encodes properties including row height and visibility.

ws['!merges']: array of range objects corresponding to the merged cells in the worksheet. Plain text formats do not support merge cells. CSV export will write all cells in the merge range if they exist, so be sure that only the first cell (upper-left) in the range is set.

ws['!outline']: configure how outlines should behave. Options default to the default settings in Excel 2019:

keyExcel featuredefault
aboveUncheck "Summary rows below detail"false
leftUncheck "Summary rows to the right of detail"false
  • ws['!protect']: object of write sheet protection properties. The password key specifies the password for formats that support password-protected sheets (XLSX/XLSB/XLS). The writer uses the XOR obfuscation method. The following keys control the sheet protection -- set to false to enable a feature when sheet is locked or set to true to disable a feature:

Worksheet Protection Details (click to show)

keyfeature (true=disabled / false=enabled)default
selectLockedCellsSelect locked cellsenabled
selectUnlockedCellsSelect unlocked cellsenabled
formatCellsFormat cellsdisabled
formatColumnsFormat columnsdisabled
formatRowsFormat rowsdisabled
insertColumnsInsert columnsdisabled
insertRowsInsert rowsdisabled
insertHyperlinksInsert hyperlinksdisabled
deleteColumnsDelete columnsdisabled
deleteRowsDelete rowsdisabled
pivotTablesUse PivotTable reportsdisabled
objectsEdit objectsenabled
scenariosEdit scenariosenabled
  • ws['!autofilter']: AutoFilter object following the schema:
type AutoFilter = {
  ref:string; // A-1 based range representing the AutoFilter table range

Chartsheet Object

Chartsheets are represented as standard sheets. They are distinguished with the !type property set to "chart".

The underlying data and !ref refer to the cached data in the chartsheet. The first row of the chartsheet is the underlying header.

Macrosheet Object

Macrosheets are represented as standard sheets. They are distinguished with the !type property set to "macro".

Dialogsheet Object

Dialogsheets are represented as standard sheets. They are distinguished with the !type property set to "dialog".

Workbook Object

workbook.SheetNames is an ordered list of the sheets in the workbook

wb.Sheets[sheetname] returns an object representing the worksheet.

wb.Props is an object storing the standard properties. wb.Custprops stores custom properties. Since the XLS standard properties deviate from the XLSX standard, XLS parsing stores core properties in both places.

wb.Workbook stores workbook-level attributes.

Workbook File Properties

The various file formats use different internal names for file properties. The workbook Props object normalizes the names:

File Properties (click to show)

JS NameExcel Description
TitleSummary tab "Title"
SubjectSummary tab "Subject"
AuthorSummary tab "Author"
ManagerSummary tab "Manager"
CompanySummary tab "Company"
CategorySummary tab "Category"
KeywordsSummary tab "Keywords"
CommentsSummary tab "Comments"
LastAuthorStatistics tab "Last saved by"
CreatedDateStatistics tab "Created"

For example, to set the workbook title property:

if(!wb.Props) wb.Props = {};
wb.Props.Title = "Insert Title Here";

Custom properties are added in the workbook Custprops object:

if(!wb.Custprops) wb.Custprops = {};
wb.Custprops["Custom Property"] = "Custom Value";

Writers will process the Props key of the options object:

/* force the Author to be "SheetJS" */
XLSX.write(wb, {Props:{Author:"SheetJS"}});

Workbook-Level Attributes

wb.Workbook stores workbook-level attributes.

Defined Names

wb.Workbook.Names is an array of defined name objects which have the keys:

Defined Name Properties (click to show)

SheetName scope. Sheet Index (0 = first sheet) or null (Workbook)
NameCase-sensitive name. Standard rules apply **
RefA1-style Reference ("Sheet1!$A$1:$D$20")
CommentComment (only applicable for XLS/XLSX/XLSB)

Excel allows two sheet-scoped defined names to share the same name. However, a sheet-scoped name cannot collide with a workbook-scope name. Workbook writers may not enforce this constraint.

Workbook Views

wb.Workbook.Views is an array of workbook view objects which have the keys:

RTLIf true, display right-to-left

Miscellaneous Workbook Properties

wb.Workbook.WBProps holds other workbook properties:

CodeNameVBA Project Workbook Code Name
date1904epoch: 0/false for 1900 system, 1/true for 1904
filterPrivacyWarn or strip personally identifying info on save

Document Features

Even for basic features like date storage, the official Excel formats store the same content in different ways. The parsers are expected to convert from the underlying file format representation to the Common Spreadsheet Format. Writers are expected to convert from CSF back to the underlying file format.


The A1-style formula string is stored in the f field. Even though different file formats store the formulae in different ways, the formats are translated. Even though some formats store formulae with a leading equal sign, CSF formulae do not start with =.

Representation of A1=1, A2=2, A3=A1+A2 (click to show)

  "!ref": "A1:A3",
  A1: { t:'n', v:1 },
  A2: { t:'n', v:2 },
  A3: { t:'n', v:3, f:'A1+A2' }

Shared formulae are decompressed and each cell has the formula corresponding to its cell. Writers generally do not attempt to generate shared formulae.

Cells with formula entries but no value will be serialized in a way that Excel and other spreadsheet tools will recognize. This library will not automatically compute formula results! For example, to compute BESSELJ in a worksheet:

Formula without known value (click to show)

  "!ref": "A1:A3",
  A1: { t:'n', v:3.14159 },
  A2: { t:'n', v:2 },
  A3: { t:'n', f:'BESSELJ(A1,A2)' }

Array Formulae

Array formulae are stored in the top-left cell of the array block. All cells of an array formula have a F field corresponding to the range. A single-cell formula can be distinguished from a plain formula by the presence of F field.

Array Formula examples (click to show)

For example, setting the cell C1 to the array formula {=SUM(A1:A3*B1:B3)}:

worksheet['C1'] = { t:'n', f: "SUM(A1:A3*B1:B3)", F:"C1:C1" };

For a multi-cell array formula, every cell has the same array range but only the first cell specifies the formula. Consider D1:D3=A1:A3*B1:B3:

worksheet['D1'] = { t:'n', F:"D1:D3", f:"A1:A3*B1:B3" };
worksheet['D2'] = { t:'n', F:"D1:D3" };
worksheet['D3'] = { t:'n', F:"D1:D3" };

Utilities and writers are expected to check for the presence of a F field and ignore any possible formula element f in cells other than the starting cell. They are not expected to perform validation of the formulae!

Formula Output Utility Function (click to show)

The sheet_to_formulae method generates one line per formula or array formula. Array formulae are rendered in the form range=formula while plain cells are rendered in the form cell=formula or value. Note that string literals are prefixed with an apostrophe ', consistent with Excel's formula bar display.

Formulae File Format Details (click to show)

Storage RepresentationFormatsReadWrite
A1-style stringsXLSX
RC-style stringsXLML and plain text
BIFF Parsed formulaeXLSB and all XLS formats 
OpenFormula formulaeODS/FODS/UOS
Lotus Parsed formulaeAll Lotus WK_ formats 

Since Excel prohibits named cells from colliding with names of A1 or RC style cell references, a (not-so-simple) regex conversion is possible. BIFF Parsed formulae and Lotus Parsed formulae have to be explicitly unwound. OpenFormula formulae can be converted with regular expressions.

Row and Column Properties

Format Support (click to show)


Column Properties: XLSX/M, XLSB, BIFF8 XLS, XLML, SYLK, DOM

Row and Column properties are not extracted by default when reading from a file and are not persisted by default when writing to a file. The option cellStyles: true must be passed to the relevant read or write function.

Column Properties

The !cols array in each worksheet, if present, is a collection of ColInfo objects which have the following properties:

type ColInfo = {
  /* visibility */
  hidden?: boolean; // if true, the column is hidden

  /* column width is specified in one of the following ways: */
  wpx?:    number;  // width in screen pixels
  width?:  number;  // width in Excel's "Max Digit Width", width*256 is integral
  wch?:    number;  // width in characters

  /* other fields for preserving features from files */
  level?:  number;  // 0-indexed outline / group level
  MDW?:    number;  // Excel's "Max Digit Width" unit, always integral

Row Properties

The !rows array in each worksheet, if present, is a collection of RowInfo objects which have the following properties:

type RowInfo = {
  /* visibility */
  hidden?: boolean; // if true, the row is hidden

  /* row height is specified in one of the following ways: */
  hpx?:    number;  // height in screen pixels
  hpt?:    number;  // height in points

  level?:  number;  // 0-indexed outline / group level

Outline / Group Levels Convention

The Excel UI displays the base outline level as 1 and the max level as 8. Following JS conventions, SheetJS uses 0-indexed outline levels wherein the base outline level is 0 and the max level is 7.

Why are there three width types? (click to show)

There are three different width types corresponding to the three different ways spreadsheets store column widths:

SYLK and other plain text formats use raw character count. Contemporaneous tools like Visicalc and Multiplan were character based. Since the characters had the same width, it sufficed to store a count. This tradition was continued into the BIFF formats.

SpreadsheetML (2003) tried to align with HTML by standardizing on screen pixel count throughout the file. Column widths, row heights, and other measures use pixels. When the pixel and character counts do not align, Excel rounds values.

XLSX internally stores column widths in a nebulous "Max Digit Width" form. The Max Digit Width is the width of the largest digit when rendered (generally the "0" character is the widest). The internal width must be an integer multiple of the the width divided by 256. ECMA-376 describes a formula for converting between pixels and the internal width. This represents a hybrid approach.

Read functions attempt to populate all three properties. Write functions will try to cycle specified values to the desired type. In order to avoid potential conflicts, manipulation should delete the other properties first. For example, when changing the pixel width, delete the wch and width properties.

Implementation details (click to show)

Row Heights

Excel internally stores row heights in points. The default resolution is 72 DPI or 96 PPI, so the pixel and point size should agree. For different resolutions they may not agree, so the library separates the concepts.

Even though all of the information is made available, writers are expected to follow the priority order:

  1. use hpx pixel height if available
  2. use hpt point height if available

Column Widths

Given the constraints, it is possible to determine the MDW without actually inspecting the font! The parsers guess the pixel width by converting from width to pixels and back, repeating for all possible MDW and selecting the MDW that minimizes the error. XLML actually stores the pixel width, so the guess works in the opposite direction.

Even though all of the information is made available, writers are expected to follow the priority order:

  1. use width field if available
  2. use wpx pixel width if available
  3. use wch character count if available

Number Formats

The cell.w formatted text for each cell is produced from cell.v and cell.z format. If the format is not specified, the Excel General format is used. The format can either be specified as a string or as an index into the format table. Parsers are expected to populate workbook.SSF with the number format table. Writers are expected to serialize the table.

Custom tools should ensure that the local table has each used format string somewhere in the table. Excel convention mandates that the custom formats start at index 164. The following example creates a custom format from scratch:

New worksheet with custom format (click to show)

var wb = {
  SheetNames: ["Sheet1"],
  Sheets: {
    Sheet1: {
      A1: { t:"n", v:10000 },                    // <-- General format
      B1: { t:"n", v:10000, z: "0%" },           // <-- Builtin format
      C1: { t:"n", v:10000, z: "\"T\"\ #0.00" }  // <-- Custom format

The rules are slightly different from how Excel displays custom number formats. In particular, literal characters must be wrapped in double quotes or preceded by a backslash. For more info, see the Excel documentation article Create or delete a custom number format or ECMA-376 18.8.31 (Number Formats)

Default Number Formats (click to show)

The default formats are listed in ECMA-376 18.8.30:

12# ?/?
13# ??/??
14m/d/yy (see below)
18h:mm AM/PM
19h:mm:ss AM/PM
22m/d/yy h:mm
37#,##0 ;(#,##0)
38#,##0 ;[Red](#,##0)

Format 14 (m/d/yy) is localized by Excel: even though the file specifies that number format, it will be drawn differently based on system settings. It makes sense when the producer and consumer of files are in the same locale, but that is not always the case over the Internet. To get around this ambiguity, parse functions accept the dateNF option to override the interpretation of that specific format string.


Format Support (click to show)

Cell Hyperlinks: XLSX/M, XLSB, BIFF8 XLS, XLML, ODS


Hyperlinks are stored in the l key of cell objects. The Target field of the hyperlink object is the target of the link, including the URI fragment. Tooltips are stored in the Tooltip field and are displayed when you move your mouse over the text.

For example, the following snippet creates a link from cell A3 to with the tip "Find us @!":

ws['A1'].l = { Target:"", Tooltip:"Find us @!" };

Note that Excel does not automatically style hyperlinks -- they will generally be displayed as normal text.

Remote Links

HTTP / HTTPS links can be used directly:

ws['A2'].l = { Target:"" };
ws['A3'].l = { Target:"http://localhost:7262/yes_localhost_works" };

Excel also supports mailto email links with subject line:

ws['A4'].l = { Target:"mailto:ignored@dev.null" };
ws['A5'].l = { Target:"mailto:ignored@dev.null?subject=Test Subject" };

Local Links

Links to absolute paths should use the file:// URI scheme:

ws['B1'].l = { Target:"file:///SheetJS/t.xlsx" }; /* Link to /SheetJS/t.xlsx */
ws['B2'].l = { Target:"file:///c:/SheetJS.xlsx" }; /* Link to c:\SheetJS.xlsx */

Links to relative paths can be specified without a scheme:

ws['B3'].l = { Target:"SheetJS.xlsb" }; /* Link to SheetJS.xlsb */
ws['B4'].l = { Target:"../SheetJS.xlsm" }; /* Link to ../SheetJS.xlsm */

Relative Paths have undefined behavior in the SpreadsheetML 2003 format. Excel 2019 will treat a ..\ parent mark as two levels up.

Internal Links

Links where the target is a cell or range or defined name in the same workbook ("Internal Links") are marked with a leading hash character:

ws['C1'].l = { Target:"#E2" }; /* Link to cell E2 */
ws['C2'].l = { Target:"#Sheet2!E2" }; /* Link to cell E2 in sheet Sheet2 */
ws['C3'].l = { Target:"#SomeDefinedName" }; /* Link to Defined Name */

Cell Comments

Cell comments are objects stored in the c array of cell objects. The actual contents of the comment are split into blocks based on the comment author. The a field of each comment object is the author of the comment and the t field is the plain text representation.

For example, the following snippet appends a cell comment into cell A1:

if(!ws.A1.c) ws.A1.c = [];
ws.A1.c.push({a:"SheetJS", t:"I'm a little comment, short and stout!"});

Note: XLSB enforces a 54 character limit on the Author name. Names longer than 54 characters may cause issues with other formats.

To mark a comment as normally hidden, set the hidden property:

if(!ws.A1.c) ws.A1.c = [];
ws.A1.c.push({a:"SheetJS", t:"This comment is visible"});

if(!ws.A2.c) ws.A2.c = [];
ws.A2.c.hidden = true;
ws.A2.c.push({a:"SheetJS", t:"This comment will be hidden"});

Sheet Visibility

Excel enables hiding sheets in the lower tab bar. The sheet data is stored in the file but the UI does not readily make it available. Standard hidden sheets are revealed in the "Unhide" menu. Excel also has "very hidden" sheets which cannot be revealed in the menu. It is only accessible in the VB Editor!

The visibility setting is stored in the Hidden property of sheet props array.

More details (click to show)

2Very Hidden


> { return [, x.Hidden] })
[ [ 'Visible', 0 ], [ 'Hidden', 1 ], [ 'VeryHidden', 2 ] ]

Non-Excel formats do not support the Very Hidden state. The best way to test if a sheet is visible is to check if the Hidden property is logical truth:

> { return [, !x.Hidden] })
[ [ 'Visible', true ], [ 'Hidden', false ], [ 'VeryHidden', false ] ]

VBA and Macros

VBA Macros are stored in a special data blob that is exposed in the vbaraw property of the workbook object when the bookVBA option is true. They are supported in XLSM, XLSB, and BIFF8 XLS formats. The supported format writers automatically insert the data blobs if it is present in the workbook and associate with the worksheet names.

Custom Code Names (click to show)

The workbook code name is stored in wb.Workbook.WBProps.CodeName. By default, Excel will write ThisWorkbook or a translated phrase like DieseArbeitsmappe. Worksheet and Chartsheet code names are in the worksheet properties object at wb.Workbook.Sheets[i].CodeName. Macrosheets and Dialogsheets are ignored.

The readers and writers preserve the code names, but they have to be manually set when adding a VBA blob to a different workbook.

Macrosheets (click to show)

Older versions of Excel also supported a non-VBA "macrosheet" sheet type that stored automation commands. These are exposed in objects with the !type property set to "macro".

Detecting macros in workbooks (click to show)

The vbaraw field will only be set if macros are present, so testing is simple:

function wb_has_macro(wb/*:workbook*/)/*:boolean*/ {
    if(!!wb.vbaraw) return true;
    const sheets = => wb.Sheets[n]);
    return sheets.some((ws) => !!ws && ws['!type']=='macro');

Parsing Options

The exported read and readFile functions accept an options argument:

Option NameDefaultDescription
type Input data encoding (see Input Type below)
rawfalseIf true, plain text parsing will not parse values **
codepage If specified, use code page when appropriate **
cellFormulatrueSave formulae to the .f field
cellHTMLtrueParse rich text and save HTML to the .h field
cellNFfalseSave number format string to the .z field
cellStylesfalseSave style/theme info to the .s field
cellTexttrueGenerated formatted text to the .w field
cellDatesfalseStore dates as type d (default is n)
dateNF If specified, use the string for date code 14 **
sheetStubsfalseCreate cell objects of type z for stub cells
sheetRows0If >0, read the first sheetRows rows **
bookDepsfalseIf true, parse calculation chains
bookFilesfalseIf true, add raw files to book object **
bookPropsfalseIf true, only parse enough to get book metadata **
bookSheetsfalseIf true, only parse enough to get the sheet names
bookVBAfalseIf true, copy VBA blob to vbaraw field **
password""If defined and file is encrypted, use password **
WTFfalseIf true, throw errors on unexpected file features **
sheets If specified, only parse specified sheets **
PRNfalseIf true, allow parsing of PRN files **
xlfnfalseIf true, preserve _xlfn. prefixes in formulae **
FS DSV Field Separator override
  • Even if cellNF is false, formatted text will be generated and saved to .w
  • In some cases, sheets may be parsed even if bookSheets is false.
  • Excel aggressively tries to interpret values from CSV and other plain text. This leads to surprising behavior! The raw option suppresses value parsing.
  • bookSheets and bookProps combine to give both sets of information
  • Deps will be an empty object if bookDeps is false
  • bookFiles behavior depends on file type:
    • keys array (paths in the ZIP) for ZIP-based formats
    • files hash (mapping paths to objects representing the files) for ZIP
    • cfb object for formats using CFB containers
  • sheetRows-1 rows will be generated when looking at the JSON object output (since the header row is counted as a row when parsing the data)
  • By default all worksheets are parsed. sheets restricts based on input type:
    • number: zero-based index of worksheet to parse (0 is first worksheet)
    • string: name of worksheet to parse (case insensitive)
    • array of numbers and strings to select multiple worksheets.
  • bookVBA merely exposes the raw VBA CFB object. It does not parse the data. XLSM and XLSB store the VBA CFB object in xl/vbaProject.bin. BIFF8 XLS mixes the VBA entries alongside the core Workbook entry, so the library generates a new XLSB-compatible blob from the XLS CFB container.
  • codepage is applied to BIFF2 - BIFF5 files without CodePage records and to CSV files without BOM in type:"binary". BIFF8 XLS always defaults to 1200.
  • PRN affects parsing of text files without a common delimiter character.
  • Currently only XOR encryption is supported. Unsupported error will be thrown for files employing other encryption methods.
  • Newer Excel functions are serialized with the _xlfn. prefix, hidden from the user. SheetJS will strip _xlfn. normally. The xlfn option preserves them.
  • WTF is mainly for development. By default, the parser will suppress read errors on single worksheets, allowing you to read from the worksheets that do parse properly. Setting WTF:true forces those errors to be thrown.

Input Type

Strings can be interpreted in multiple ways. The type parameter for read tells the library how to parse the data argument:

typeexpected input
"base64"string: Base64 encoding of the file
"binary"string: binary string (byte n is data.charCodeAt(n))
"string"string: JS string (characters interpreted as UTF8)
"buffer"nodejs Buffer
"array"array: array of 8-bit unsigned int (byte n is data[n])
"file"string: path of file that will be read (nodejs only)

Guessing File Type

Implementation Details (click to show)

Excel and other spreadsheet tools read the first few bytes and apply other heuristics to determine a file type. This enables file type punning: renaming files with the .xls extension will tell your computer to use Excel to open the file but Excel will know how to handle it. This library applies similar logic:

Byte 0Raw File TypeSpreadsheet Types
0xD0CFB ContainerBIFF 5/8 or protected XLSX/XLSB or WQ3/QPW or XLR
0x09BIFF StreamBIFF 2/3/4/5
0x3CXML/HTMLSpreadsheetML / Flat ODS / UOS1 / HTML / plain text
0x50ZIP ArchiveXLSB or XLSX/M or ODS or UOS2 or NUMBERS or text
0x49Plain TextSYLK or plain text
0x54Plain TextDIF or plain text
0xEFUTF8 EncodedSpreadsheetML / Flat ODS / UOS1 / HTML / plain text
0xFFUTF16 EncodedSpreadsheetML / Flat ODS / UOS1 / HTML / plain text
0x00Record StreamLotus WK* or Quattro Pro or plain text
0x7BPlain textRTF or plain text
0x0APlain textSpreadsheetML / Flat ODS / UOS1 / HTML / plain text
0x0DPlain textSpreadsheetML / Flat ODS / UOS1 / HTML / plain text
0x20Plain textSpreadsheetML / Flat ODS / UOS1 / HTML / plain text

DBF files are detected based on the first byte as well as the third and fourth bytes (corresponding to month and day of the file date)

Works for Windows files are detected based on the BOF record with type 0xFF

Plain text format guessing follows the priority order:

XML<?xml appears in the first 1024 characters
HTMLstarts with < and HTML tags appear in the first 1024 characters *
XMLstarts with < and the first tag is valid
RTFstarts with {\rt
DSVstarts with /sep=.$/, separator is the specified character
DSVmore unquoted `
DSVmore unquoted ; chars than \t or , in the first 1024
TSVmore unquoted \t chars than , chars in the first 1024
CSVone of the first 1024 characters is a comma ","
ETHstarts with socialcalc:version:
PRNPRN option is set to true
  • HTML tags include: html, table, head, meta, script, style, div

Why are random text files valid? (click to show)

Excel is extremely aggressive in reading files. Adding an XLS extension to any display text file (where the only characters are ANSI display chars) tricks Excel into thinking that the file is potentially a CSV or TSV file, even if it is only one column! This library attempts to replicate that behavior.

The best approach is to validate the desired worksheet and ensure it has the expected number of rows or columns. Extracting the range is extremely simple:

var range = XLSX.utils.decode_range(worksheet['!ref']);
var ncols = range.e.c - range.s.c + 1, nrows = range.e.r - range.s.r + 1;

Writing Options

The exported write and writeFile functions accept an options argument:

Option NameDefaultDescription
type Output data encoding (see Output Type below)
cellDatesfalseStore dates as type d (default is n)
bookSSTfalseGenerate Shared String Table **
bookType"xlsx"Type of Workbook (see below for supported formats)
sheet""Name of Worksheet for single-sheet formats **
compressionfalseUse ZIP compression for ZIP-based formats **
Props Override workbook properties when writing **
themeXLSX Override theme XML when writing XLSX/XLSB/XLSM **
ignoreECtrueSuppress "number as text" errors **
  • bookSST is slower and more memory intensive, but has better compatibility with older versions of iOS Numbers
  • The raw data is the only thing guaranteed to be saved. Features not described in this README may not be serialized.
  • cellDates only applies to XLSX output and is not guaranteed to work with third-party readers. Excel itself does not usually write cells with type d so non-Excel tools may ignore the data or error in the presence of dates.
  • Props is an object mirroring the workbook Props field. See the table from the Workbook File Properties section.
  • if specified, the string from themeXLSX will be saved as the primary theme for XLSX/XLSB/XLSM files (to xl/theme/theme1.xml in the ZIP)
  • Due to a bug in the program, some features like "Text to Columns" will crash Excel on worksheets where error conditions are ignored. The writer will mark files to ignore the error by default. Set ignoreEC to false to suppress.

Supported Output Formats

For broad compatibility with third-party tools, this library supports many output formats. The specific file type is controlled with bookType option:

bookTypefile extcontainersheetsDescription
xlsx.xlsxZIPmultiExcel 2007+ XML Format
xlsm.xlsmZIPmultiExcel 2007+ Macro XML Format
xlsb.xlsbZIPmultiExcel 2007+ Binary Format
biff8.xlsCFBmultiExcel 97-2004 Workbook Format
biff5.xlsCFBmultiExcel 5.0/95 Workbook Format
biff4.xlsnonesingleExcel 4.0 Worksheet Format
biff3.xlsnonesingleExcel 3.0 Worksheet Format
biff2.xlsnonesingleExcel 2.0 Worksheet Format
xlml.xlsnonemultiExcel 2003-2004 (SpreadsheetML)
ods.odsZIPmultiOpenDocument Spreadsheet
fods.fodsnonemultiFlat OpenDocument Spreadsheet
wk3.wk3nonesingleLotus Workbook (WK3)
csv.csvnonesingleComma Separated Values
txt.txtnonesingleUTF-16 Unicode Text (TXT)
sylk.sylknonesingleSymbolic Link (SYLK)
html.htmlnonesingleHTML Document
dif.difnonesingleData Interchange Format (DIF)
dbf.dbfnonesingledBASE II + VFP Extensions (DBF)
wk1.wk1nonesingleLotus Worksheet (WK1)
rtf.rtfnonesingleRich Text Format (RTF)
prn.prnnonesingleLotus Formatted Text
eth.ethnonesingleEthercalc Record Format (ETH)
  • compression only applies to formats with ZIP containers.
  • Formats that only support a single sheet require a sheet option specifying the worksheet. If the string is empty, the first worksheet is used.
  • writeFile will automatically guess the output file format based on the file extension if bookType is not specified. It will choose the first format in the aforementioned table that matches the extension.

Output Type

The type argument for write mirrors the type argument for read:

"base64"string: Base64 encoding of the file
"binary"string: binary string (byte n is data.charCodeAt(n))
"string"string: JS string (characters interpreted as UTF8)
"buffer"nodejs Buffer
"array"ArrayBuffer, fallback array of 8-bit unsigned int
"file"string: path of file that will be created (nodejs only)

Utility Functions

The sheet_to_* functions accept a worksheet and an optional options object.

The *_to_sheet functions accept a data object and an optional options object.

The examples are based on the following worksheet:

XXX| A | B | C | D | E | F | G |
 1 | S | h | e | e | t | J | S |
 2 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
 3 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |

Array of Arrays Input

XLSX.utils.aoa_to_sheet takes an array of arrays of JS values and returns a worksheet resembling the input data. Numbers, Booleans and Strings are stored as the corresponding styles. Dates are stored as date or numbers. Array holes and explicit undefined values are skipped. null values may be stubbed. All other values are stored as strings. The function takes an options argument:

Option NameDefaultDescription
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
sheetStubsfalseCreate cell objects of type z for null values
nullErrorfalseIf true, emit #NULL! error cells for null values

Examples (click to show)

To generate the example sheet:

var ws = XLSX.utils.aoa_to_sheet([

XLSX.utils.sheet_add_aoa takes an array of arrays of JS values and updates an existing worksheet object. It follows the same process as aoa_to_sheet and accepts an options argument:

Option NameDefaultDescription
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
sheetStubsfalseCreate cell objects of type z for null values
nullErrorfalseIf true, emit #NULL! error cells for null values
origin Use specified cell as starting point (see below)

origin is expected to be one of:

(cell object)Use specified cell (cell object)
(string)Use specified cell (A1-style cell)
(number >= 0)Start from the first column at specified row (0-indexed)
-1Append to bottom of worksheet starting on first column
(default)Start from cell A1

Examples (click to show)

Consider the worksheet:

XXX| A | B | C | D | E | F | G |
 1 | S | h | e | e | t | J | S |
 2 | 1 | 2 |   |   | 5 | 6 | 7 |
 3 | 2 | 3 |   |   | 6 | 7 | 8 |
 4 | 3 | 4 |   |   | 7 | 8 | 9 |
 5 | 4 | 5 | 6 | 7 | 8 | 9 | 0 |

This worksheet can be built up in the order A1:G1, A2:B4, E2:G4, A5:G5:

/* Initial row */
var ws = XLSX.utils.aoa_to_sheet([ "SheetJS".split("") ]);

/* Write data starting at A2 */
XLSX.utils.sheet_add_aoa(ws, [[1,2], [2,3], [3,4]], {origin: "A2"});

/* Write data starting at E2 */
XLSX.utils.sheet_add_aoa(ws, [[5,6,7], [6,7,8], [7,8,9]], {origin:{r:1, c:4}});

/* Append row */
XLSX.utils.sheet_add_aoa(ws, [[4,5,6,7,8,9,0]], {origin: -1});

Array of Objects Input

XLSX.utils.json_to_sheet takes an array of objects and returns a worksheet with automatically-generated "headers" based on the keys of the objects. The default column order is determined by the first appearance of the field using Object.keys. The function accepts an options argument:

Option NameDefaultDescription
header Use specified field order (default Object.keys) **
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
skipHeaderfalseIf true, do not include header row in output
nullErrorfalseIf true, emit #NULL! error cells for null values
  • All fields from each row will be written. If header is an array and it does not contain a particular field, the key will be appended to the array.
  • Cell types are deduced from the type of each value. For example, a Date object will generate a Date cell, while a string will generate a Text cell.
  • Null values will be skipped by default. If nullError is true, an error cell corresponding to #NULL! will be written to the worksheet.

Examples (click to show)

The original sheet cannot be reproduced using plain objects since JS object keys must be unique. After replacing the second e and S with e_1 and S_1:

var ws = XLSX.utils.json_to_sheet([
  { S:1, h:2, e:3, e_1:4, t:5, J:6, S_1:7 },
  { S:2, h:3, e:4, e_1:5, t:6, J:7, S_1:8 }
], {header:["S","h","e","e_1","t","J","S_1"]});

Alternatively, the header row can be skipped:

var ws = XLSX.utils.json_to_sheet([
  { A:"S", B:"h", C:"e", D:"e", E:"t", F:"J", G:"S" },
  { A: 1,  B: 2,  C: 3,  D: 4,  E: 5,  F: 6,  G: 7  },
  { A: 2,  B: 3,  C: 4,  D: 5,  E: 6,  F: 7,  G: 8  }
], {header:["A","B","C","D","E","F","G"], skipHeader:true});

XLSX.utils.sheet_add_json takes an array of objects and updates an existing worksheet object. It follows the same process as json_to_sheet and accepts an options argument:

Option NameDefaultDescription
header Use specified column order (default Object.keys)
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
skipHeaderfalseIf true, do not include header row in output
nullErrorfalseIf true, emit #NULL! error cells for null values
origin Use specified cell as starting point (see below)

origin is expected to be one of:

(cell object)Use specified cell (cell object)
(string)Use specified cell (A1-style cell)
(number >= 0)Start from the first column at specified row (0-indexed)
-1Append to bottom of worksheet starting on first column
(default)Start from cell A1

Examples (click to show)

Consider the worksheet:

XXX| A | B | C | D | E | F | G |
 1 | S | h | e | e | t | J | S |
 2 | 1 | 2 |   |   | 5 | 6 | 7 |
 3 | 2 | 3 |   |   | 6 | 7 | 8 |
 4 | 3 | 4 |   |   | 7 | 8 | 9 |
 5 | 4 | 5 | 6 | 7 | 8 | 9 | 0 |

This worksheet can be built up in the order A1:G1, A2:B4, E2:G4, A5:G5:

/* Initial row */
var ws = XLSX.utils.json_to_sheet([
  { A: "S", B: "h", C: "e", D: "e", E: "t", F: "J", G: "S" }
], {header: ["A", "B", "C", "D", "E", "F", "G"], skipHeader: true});

/* Write data starting at A2 */
XLSX.utils.sheet_add_json(ws, [
  { A: 1, B: 2 }, { A: 2, B: 3 }, { A: 3, B: 4 }
], {skipHeader: true, origin: "A2"});

/* Write data starting at E2 */
XLSX.utils.sheet_add_json(ws, [
  { A: 5, B: 6, C: 7 }, { A: 6, B: 7, C: 8 }, { A: 7, B: 8, C: 9 }
], {skipHeader: true, origin: { r: 1, c: 4 }, header: [ "A", "B", "C" ]});

/* Append row */
XLSX.utils.sheet_add_json(ws, [
  { A: 4, B: 5, C: 6, D: 7, E: 8, F: 9, G: 0 }
], {header: ["A", "B", "C", "D", "E", "F", "G"], skipHeader: true, origin: -1});

HTML Table Input

XLSX.utils.table_to_sheet takes a table DOM element and returns a worksheet resembling the input table. Numbers are parsed. All other data will be stored as strings.

XLSX.utils.table_to_book produces a minimal workbook based on the worksheet.

Both functions accept options arguments:

Option NameDefaultDescription
raw If true, every cell will hold raw strings
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
sheetRows0If >0, read the first sheetRows rows of the table
displayfalseIf true, hidden rows and cells will not be parsed

Examples (click to show)

To generate the example sheet, start with the HTML table:

<table id="sheetjs">

To process the table:

var tbl = document.getElementById('sheetjs');
var wb = XLSX.utils.table_to_book(tbl);

Note: can handle HTML represented as strings.

XLSX.utils.sheet_add_dom takes a table DOM element and updates an existing worksheet object. It follows the same process as table_to_sheet and accepts an options argument:

Option NameDefaultDescription
raw If true, every cell will hold raw strings
dateNFFMT 14Use specified date format in string output
cellDatesfalseStore dates as type d (default is n)
sheetRows0If >0, read the first sheetRows rows of the table
displayfalseIf true, hidden rows and cells will not be parsed

origin is expected to be one of:

(cell object)Use specified cell (cell object)
(string)Use specified cell (A1-style cell)
(number >= 0)Start from the first column at specified row (0-indexed)
-1Append to bottom of worksheet starting on first column
(default)Start from cell A1

Examples (click to show)

A small helper function can create gap rows between tables:

function create_gap_rows(ws, nrows) {
  var ref = XLSX.utils.decode_range(ws["!ref"]);       // get original range
  ref.e.r += nrows;                                    // add to ending row
  ws["!ref"] = XLSX.utils.encode_range(ref);           // reassign row

/* first table */
var ws = XLSX.utils.table_to_sheet(document.getElementById('table1'));
create_gap_rows(ws, 1); // one row gap after first table

/* second table */
XLSX.utils.sheet_add_dom(ws, document.getElementById('table2'), {origin: -1});
create_gap_rows(ws, 3); // three rows gap after second table

/* third table */
XLSX.utils.sheet_add_dom(ws, document.getElementById('table3'), {origin: -1});

Formulae Output

XLSX.utils.sheet_to_formulae generates an array of commands that represent how a person would enter data into an application. Each entry is of the form A1-cell-address=formula-or-value. String literals are prefixed with a ' in accordance with Excel.

Examples (click to show)

For the example sheet:

> var o = XLSX.utils.sheet_to_formulae(ws);
> [o[0], o[5], o[10], o[15], o[20]];
[ 'A1=\'S', 'F1=\'J', 'D2=4', 'B3=3', 'G3=8' ]

Delimiter-Separated Output

As an alternative to the writeFile CSV type, XLSX.utils.sheet_to_csv also produces CSV output. The function takes an options argument:

Option NameDefaultDescription
FS",""Field Separator" delimiter between fields
RS"\n""Record Separator" delimiter between rows
dateNFFMT 14Use specified date format in string output
stripfalseRemove trailing field separators in each record **
blankrowstrueInclude blank lines in the CSV output
skipHiddenfalseSkips hidden rows/columns in the CSV output
forceQuotesfalseForce quotes around fields
  • strip will remove trailing commas from each line under default FS/RS
  • blankrows must be set to false to skip blank lines.
  • Fields containing the record or field separator will automatically be wrapped in double quotes; forceQuotes forces all cells to be wrapped in quotes.

Examples (click to show)

For the example sheet:

> console.log(XLSX.utils.sheet_to_csv(ws));
> console.log(XLSX.utils.sheet_to_csv(ws, {FS:"\t"}));
S    h    e    e    t    J    S
1    2    3    4    5    6    7
2    3    4    5    6    7    8
> console.log(XLSX.utils.sheet_to_csv(ws,{FS:":",RS:"|"}));

UTF-16 Unicode Text

The txt output type uses the tab character as the field separator. If the codepage library is available (included in full distribution but not core), the output will be encoded in CP1200 and the BOM will be prepended.

XLSX.utils.sheet_to_txt takes the same arguments as sheet_to_csv.

HTML Output

As an alternative to the writeFile HTML type, XLSX.utils.sheet_to_html also produces HTML output. The function takes an options argument:

Option NameDefaultDescription
id Specify the id attribute for the TABLE element
editablefalseIf true, set contenteditable="true" for every TD
header Override header (default html body)
footer Override footer (default /body /html)

Examples (click to show)

For the example sheet:

> console.log(XLSX.utils.sheet_to_html(ws));
// ...


XLSX.utils.sheet_to_json generates different types of JS objects. The function takes an options argument:

Option NameDefaultDescription
rawtrueUse raw values (true) or formatted strings (false)
rangefrom WSOverride Range (see table below)
header Control output format (see table below)
dateNFFMT 14Use specified date format in string output
defval Use specified value in place of null or undefined
blankrows**Include blank lines in the output **
  • raw only affects cells which have a format code (.z) field or a formatted text (.w) field.
  • If header is specified, the first row is considered a data row; if header is not specified, the first row is the header row and not considered data.
  • When header is not specified, the conversion will automatically disambiguate header entries by affixing _ and a count starting at 1. For example, if three columns have header foo the output fields are foo, foo_1, foo_2
  • null values are returned when raw is true but are skipped when false.
  • If defval is not specified, null and undefined values are skipped normally. If specified, all null and undefined points will be filled with defval
  • When header is 1, the default is to generate blank rows. blankrows must be set to false to skip blank rows.
  • When header is not 1, the default is to skip blank rows. blankrows must be true to generate blank rows

range is expected to be one of:

(number)Use worksheet range but set starting row to the value
(string)Use specified range (A1-style bounded range string)
(default)Use worksheet range (ws['!ref'])

header is expected to be one of:

1Generate an array of arrays ("2D Array")
"A"Row object keys are literal column labels
array of stringsUse specified strings as keys in row objects
(default)Read and disambiguate first row as keys

If header is not 1, the row object will contain the non-enumerable property __rowNum__ that represents the row of the sheet corresponding to the entry.

Examples (click to show)

For the example sheet:

> XLSX.utils.sheet_to_json(ws);
[ { S: 1, h: 2, e: 3, e_1: 4, t: 5, J: 6, S_1: 7 },
  { S: 2, h: 3, e: 4, e_1: 5, t: 6, J: 7, S_1: 8 } ]

> XLSX.utils.sheet_to_json(ws, {header:"A"});
[ { A: 'S', B: 'h', C: 'e', D: 'e', E: 't', F: 'J', G: 'S' },
  { A: '1', B: '2', C: '3', D: '4', E: '5', F: '6', G: '7' },
  { A: '2', B: '3', C: '4', D: '5', E: '6', F: '7', G: '8' } ]

> XLSX.utils.sheet_to_json(ws, {header:["A","E","I","O","U","6","9"]});
[ { '6': 'J', '9': 'S', A: 'S', E: 'h', I: 'e', O: 'e', U: 't' },
  { '6': '6', '9': '7', A: '1', E: '2', I: '3', O: '4', U: '5' },
  { '6': '7', '9': '8', A: '2', E: '3', I: '4', O: '5', U: '6' } ]

> XLSX.utils.sheet_to_json(ws, {header:1});
[ [ 'S', 'h', 'e', 'e', 't', 'J', 'S' ],
  [ '1', '2', '3', '4', '5', '6', '7' ],
  [ '2', '3', '4', '5', '6', '7', '8' ] ]

Example showing the effect of raw:

> ws['A2'].w = "3";                          // set A2 formatted string value

> XLSX.utils.sheet_to_json(ws, {header:1, raw:false});
[ [ 'S', 'h', 'e', 'e', 't', 'J', 'S' ],
  [ '3', '2', '3', '4', '5', '6', '7' ],     // <-- A2 uses the formatted string
  [ '2', '3', '4', '5', '6', '7', '8' ] ]

> XLSX.utils.sheet_to_json(ws, {header:1});
[ [ 'S', 'h', 'e', 'e', 't', 'J', 'S' ],
  [ 1, 2, 3, 4, 5, 6, 7 ],                   // <-- A2 uses the raw value
  [ 2, 3, 4, 5, 6, 7, 8 ] ]

File Formats

Despite the library name xlsx, it supports numerous spreadsheet file formats:

Excel Worksheet/Workbook Formats:-----::-----:
Excel 2007+ XML Formats (XLSX/XLSM)
Excel 2007+ Binary Format (XLSB BIFF12)
Excel 2003-2004 XML Format (XML "SpreadsheetML")
Excel 97-2004 (XLS BIFF8)
Excel 5.0/95 (XLS BIFF5)
Excel 4.0 (XLS/XLW BIFF4)
Excel 3.0 (XLS BIFF3)
Excel 2.0/2.1 (XLS BIFF2)
Excel Supported Text Formats:-----::-----:
Delimiter-Separated Values (CSV/TXT)
Data Interchange Format (DIF)
Symbolic Link (SYLK/SLK)
Lotus Formatted Text (PRN)
UTF-16 Unicode Text (TXT)
Other Workbook/Worksheet Formats:-----::-----:
Numbers 3.0+ / iWork 2013+ Spreadsheet (NUMBERS) 
OpenDocument Spreadsheet (ODS)
Flat XML ODF Spreadsheet (FODS)
Uniform Office Format Spreadsheet (标文通 UOS1/UOS2) 
dBASE II/III/IV / Visual FoxPro (DBF)
Lotus 1-2-3 (WK1/WK3)
Lotus 1-2-3 (WKS/WK2/WK4/123) 
Quattro Pro Spreadsheet (WQ1/WQ2/WB1/WB2/WB3/QPW) 
Works 1.x-3.x DOS / 2.x-5.x Windows Spreadsheet (WKS) 
Works 6.x-9.x Spreadsheet (XLR) 
Other Common Spreadsheet Output Formats:-----::-----:
HTML Tables
Rich Text Format tables (RTF) 
Ethercalc Record Format (ETH)

Features not supported by a given file format will not be written. Formats with range limits will be silently truncated:

FormatLast CellMax ColsMax Rows
Excel 2007+ XML Formats (XLSX/XLSM)XFD1048576163841048576
Excel 2007+ Binary Format (XLSB BIFF12)XFD1048576163841048576
Excel 97-2004 (XLS BIFF8)IV6553625665536
Excel 5.0/95 (XLS BIFF5)IV1638425616384
Excel 4.0 (XLS BIFF4)IV1638425616384
Excel 3.0 (XLS BIFF3)IV1638425616384
Excel 2.0/2.1 (XLS BIFF2)IV1638425616384
Lotus 1-2-3 R2 - R5 (WK1/WK3/WK4)IV81922568192
Lotus 1-2-3 R1 (WKS)IV20482562048

Excel 2003 SpreadsheetML range limits are governed by the version of Excel and are not enforced by the writer.

File Format Details (click to show)

Core Spreadsheet Formats

  • Excel 2007+ XML (XLSX/XLSM)

XLSX and XLSM files are ZIP containers containing a series of XML files in accordance with the Open Packaging Conventions (OPC). The XLSM format, almost identical to XLSX, is used for files containing macros.

The format is standardized in ECMA-376 and later in ISO/IEC 29500. Excel does not follow the specification, and there are additional documents discussing how Excel deviates from the specification.

  • Excel 2.0-95 (BIFF2/BIFF3/BIFF4/BIFF5)

BIFF 2/3 XLS are single-sheet streams of binary records. Excel 4 introduced the concept of a workbook (XLW files) but also had single-sheet XLS format. The structure is largely similar to the Lotus 1-2-3 file formats. BIFF5/8/12 extended the format in various ways but largely stuck to the same record format.

There is no official specification for any of these formats. Excel 95 can write files in these formats, so record lengths and fields were determined by writing in all of the supported formats and comparing files. Excel 2016 can generate BIFF5 files, enabling a full suite of file tests starting from XLSX or BIFF2.

  • Excel 97-2004 Binary (BIFF8)

BIFF8 exclusively uses the Compound File Binary container format, splitting some content into streams within the file. At its core, it still uses an extended version of the binary record format from older versions of BIFF.

The MS-XLS specification covers the basics of the file format, and other specifications expand on serialization of features like properties.

  • Excel 2003-2004 (SpreadsheetML)

Predating XLSX, SpreadsheetML files are simple XML files. There is no official and comprehensive specification, although MS has released documentation on the format. Since Excel 2016 can generate SpreadsheetML files, mapping features is pretty straightforward.

  • Excel 2007+ Binary (XLSB, BIFF12)

Introduced in parallel with XLSX, the XLSB format combines the BIFF architecture with the content separation and ZIP container of XLSX. For the most part nodes in an XLSX sub-file can be mapped to XLSB records in a corresponding sub-file.

The MS-XLSB specification covers the basics of the file format, and other specifications expand on serialization of features like properties.

  • Delimiter-Separated Values (CSV/TXT)

Excel CSV deviates from RFC4180 in a number of important ways. The generated CSV files should generally work in Excel although they may not work in RFC4180 compatible readers. The parser should generally understand Excel CSV. The writer proactively generates cells for formulae if values are unavailable.

Excel TXT uses tab as the delimiter and code page 1200.

Like in Excel, files starting with 0x49 0x44 ("ID") are treated as Symbolic Link files. Unlike Excel, if the file does not have a valid SYLK header, it will be proactively reinterpreted as CSV. There are some files with semicolon delimiter that align with a valid SYLK file. For the broadest compatibility, all cells with the value of ID are automatically wrapped in double-quotes.

Miscellaneous Workbook Formats

Support for other formats is generally far behind XLS/XLSB/XLSX support, due in part to a lack of publicly available documentation. Test files were produced in the respective apps and compared to their XLS exports to determine structure. The main focus is data extraction.

  • Lotus 1-2-3 (WKS/WK1/WK2/WK3/WK4/123)

The Lotus formats consist of binary records similar to the BIFF structure. Lotus did release a specification decades ago covering the original WK1 format. Other features were deduced by producing files and comparing to Excel support.

Generated WK1 worksheets are compatible with Lotus 1-2-3 R2 and Excel 5.0.

Generated WK3 workbooks are compatible with Lotus 1-2-3 R9 and Excel 5.0.

  • Quattro Pro (WQ1/WQ2/WB1/WB2/WB3/QPW)

The Quattro Pro formats use binary records in the same way as BIFF and Lotus. Some of the newer formats (namely WB3 and QPW) use a CFB enclosure just like BIFF8 XLS.

  • Works for DOS / Windows Spreadsheet (WKS/XLR)

All versions of Works were limited to a single worksheet.

Works for DOS 1.x - 3.x and Works for Windows 2.x extends the Lotus WKS format with additional record types.

Works for Windows 3.x - 5.x uses the same format and WKS extension. The BOF record has type FF

Works for Windows 6.x - 9.x use the XLR format. XLR is nearly identical to BIFF8 XLS: it uses the CFB container with a Workbook stream. Works 9 saves the exact Workbook stream for the XLR and the 97-2003 XLS export. Works 6 XLS includes two empty worksheets but the main worksheet has an identical encoding. XLR also includes a WksSSWorkBook stream similar to Lotus FM3/FMT files.

  • Numbers 3.0+ / iWork 2013+ Spreadsheet (NUMBERS)

iWork 2013 (Numbers 3.0 / Pages 5.0 / Keynote 6.0) switched from a proprietary XML-based format to the current file format based on the iWork Archive (IWA). This format has been used up through the current release (Numbers 11.2).

The parser focuses on extracting raw data from tables. Numbers technically supports multiple tables in a logical worksheet, including custom titles. This parser will generate one worksheet per Numbers table.

  • OpenDocument Spreadsheet (ODS/FODS)

ODS is an XML-in-ZIP format akin to XLSX while FODS is an XML format akin to SpreadsheetML. Both are detailed in the OASIS standard, but tools like LO/OO add undocumented extensions. The parsers and writers do not implement the full standard, instead focusing on parts necessary to extract and store raw data.

  • Uniform Office Spreadsheet (UOS1/2)

UOS is a very similar format, and it comes in 2 varieties corresponding to ODS and FODS respectively. For the most part, the difference between the formats is in the names of tags and attributes.

Miscellaneous Worksheet Formats

Many older formats supported only one worksheet:

  • dBASE and Visual FoxPro (DBF)

DBF is really a typed table format: each column can only hold one data type and each record omits type information. The parser generates a header row and inserts records starting at the second row of the worksheet. The writer makes files compatible with Visual FoxPro extensions.

Multi-file extensions like external memos and tables are currently unsupported, limited by the general ability to read arbitrary files in the web browser. The reader understands DBF Level 7 extensions like DATETIME.

  • Symbolic Link (SYLK)

There is no real documentation. All knowledge was gathered by saving files in various versions of Excel to deduce the meaning of fields. Notes:

Plain formulae are stored in the RC form.

Column widths are rounded to integral characters.

Lotus Formatted Text (PRN)

There is no real documentation, and in fact Excel treats PRN as an output-only file format. Nevertheless we can guess the column widths and reverse-engineer the original layout. Excel's 240 character width limitation is not enforced.

  • Data Interchange Format (DIF)

There is no unified definition. Visicalc DIF differs from Lotus DIF, and both differ from Excel DIF. Where ambiguous, the parser/writer follows the expected behavior from Excel. In particular, Excel extends DIF in incompatible ways:

Since Excel automatically converts numbers-as-strings to numbers, numeric string constants are converted to formulae: "0.3" -> "=""0.3""

DIF technically expects numeric cells to hold the raw numeric data, but Excel permits formatted numbers (including dates)

DIF technically has no support for formulae, but Excel will automatically convert plain formulae. Array formulae are not preserved.


Excel HTML worksheets include special metadata encoded in styles. For example, mso-number-format is a localized string containing the number format. Despite the metadata the output is valid HTML, although it does accept bare & symbols.

The writer adds type metadata to the TD elements via the t tag. The parser looks for those tags and overrides the default interpretation. For example, text like <td>12345</td> will be parsed as numbers but <td t="s">12345</td> will be parsed as text.

  • Rich Text Format (RTF)

Excel RTF worksheets are stored in clipboard when copying cells or ranges from a worksheet. The supported codes are a subset of the Word RTF support.

  • Ethercalc Record Format (ETH)

Ethercalc is an open source web spreadsheet powered by a record format reminiscent of SYLK wrapped in a MIME multi-part message.



(click to show)

make test will run the node-based tests. By default it runs tests on files in every supported format. To test a specific file type, set FMTS to the format you want to test. Feature-specific tests are available with make test_misc

$ make test_misc   # run core tests
$ make test        # run full tests
$ make test_xls    # only use the XLS test files
$ make test_xlsx   # only use the XLSX test files
$ make test_xlsb   # only use the XLSB test files
$ make test_xml    # only use the XML test files
$ make test_ods    # only use the ODS test files

To enable all errors, set the environment variable WTF=1:

$ make test        # run full tests
$ WTF=1 make test  # enable all error messages

flow and eslint checks are available:

$ make lint        # eslint checks
$ make flow        # make lint + Flow checking
$ make tslint      # check TS definitions


(click to show)

The core in-browser tests are available at tests/index.html within this repo. Start a local server and navigate to that directory to run the tests. make ctestserv will start a server on port 8000.

make ctest will generate the browser fixtures. To add more files, edit the tests/fixtures.lst file and add the paths.

To run the full in-browser tests, clone the repo for and replace the xlsx.js file (then open a browser window and go to stress.html):

$ cp xlsx.js ../
$ cd ../
$ simplehttpserver # or "python -mSimpleHTTPServer" or "serve"
$ open -a http://localhost:8000/stress.html

Tested Environments

(click to show)

  • NodeJS 0.8, 0.10, 0.12, 4.x, 5.x, 6.x, 7.x, 8.x
  • IE 6/7/8/9/10/11 (IE 6-9 require shims)
  • Chrome 24+ (including Android 4.0+)
  • Safari 6+ (iOS and Desktop)
  • Edge 13+, FF 18+, and Opera 12+

Tests utilize the mocha testing framework.

The test suite also includes tests for various time zones. To change the timezone locally, set the TZ environment variable:

$ env TZ="Asia/Kolkata" WTF=1 make test_misc

Test Files

Test files are housed in another repo.

Running make init will refresh the test_files submodule and get the files. Note that this requires svn, git, hg and other commands that may not be available. If make init fails, please download the latest version of the test files snapshot from the repo

Latest Snapshot (click to show)

Latest test files snapshot:

(download and unzip to the test_files subdirectory)


Due to the precarious nature of the Open Specifications Promise, it is very important to ensure code is cleanroom. Contribution Notes

File organization (click to show)

At a high level, the final script is a concatenation of the individual files in the bits folder. Running make should reproduce the final output on all platforms. The README is similarly split into bits in the docbits folder.


bitsraw source files that make up the final script
docbitsraw markdown files that make up
binserver-side bin scripts (xlsx.njs)
distdist files for web browsers and nonstandard JS environments
demosdemo projects for platforms like ExtendScript and Webpack
testsbrowser tests (run make ctest to rebuild)
typestypescript definitions and tests
miscmiscellaneous supporting scripts
test_filestest files (pulled from the test files repository)

After cloning the repo, running make help will display a list of commands.


(click to show)

The xlsx.js file is constructed from the files in the bits subdirectory. The build script (run make) will concatenate the individual bits to produce the script. Before submitting a contribution, ensure that running make will produce the xlsx.js file exactly. The simplest way to test is to add the script:

$ git add xlsx.js
$ make clean
$ make
$ git diff xlsx.js

To produce the dist files, run make dist. The dist files are updated in each version release and should not be committed between versions.


(click to show)

The included make.cmd script will build xlsx.js from the bits directory. Building is as simple as:

> make

To prepare development environment:

> make init

The full list of commands available in Windows are displayed in make help:

make init -- install deps and global modules
make lint -- run eslint linter
make test -- run mocha test suite
make misc -- run smaller test suite
make book -- rebuild README and summary
make help -- display this message

As explained in Test Files, on Windows the release ZIP file must be downloaded and extracted. If Bash on Windows is available, it is possible to run the OSX/Linux workflow. The following steps prepares the environment:

# Install support programs for the build and test commands
sudo apt-get install make git subversion mercurial

# Install nodejs and NPM within the WSL
wget -qO- | sudo bash
sudo apt-get install nodejs

# Install dev dependencies
sudo npm install -g mocha voc blanket xlsjs


(click to show)

The test_misc target (make test_misc on Linux/OSX / make misc on Windows) runs the targeted feature tests. It should take 5-10 seconds to perform feature tests without testing against the entire test battery. New features should be accompanied with tests for the relevant file formats and features.

For tests involving the read side, an appropriate feature test would involve reading an existing file and checking the resulting workbook object. If a parameter is involved, files should be read with different values to verify that the feature is working as expected.

For tests involving a new write feature which can already be parsed, appropriate feature tests would involve writing a workbook with the feature and then opening and verifying that the feature is preserved.

For tests involving a new write feature without an existing read ability, please add a feature test to the kitchen sink tests/write.js.


OSP-covered Specifications (click to show)

  • MS-CFB: Compound File Binary File Format
  • MS-CTXLS: Excel Custom Toolbar Binary File Format
  • MS-EXSPXML3: Excel Calculation Version 2 Web Service XML Schema
  • MS-ODATA: Open Data Protocol (OData)
  • MS-ODRAW: Office Drawing Binary File Format
  • MS-ODRAWXML: Office Drawing Extensions to Office Open XML Structure
  • MS-OE376: Office Implementation Information for ECMA-376 Standards Support
  • MS-OFFCRYPTO: Office Document Cryptography Structure
  • MS-OI29500: Office Implementation Information for ISO/IEC 29500 Standards Support
  • MS-OLEDS: Object Linking and Embedding (OLE) Data Structures
  • MS-OLEPS: Object Linking and Embedding (OLE) Property Set Data Structures
  • MS-OODF3: Office Implementation Information for ODF 1.2 Standards Support
  • MS-OSHARED: Office Common Data Types and Objects Structures
  • MS-OVBA: Office VBA File Format Structure
  • MS-XLDM: Spreadsheet Data Model File Format
  • MS-XLS: Excel Binary File Format (.xls) Structure Specification
  • MS-XLSB: Excel (.xlsb) Binary File Format
  • MS-XLSX: Excel (.xlsx) Extensions to the Office Open XML SpreadsheetML File Format
  • XLS: Microsoft Office Excel 97-2007 Binary File Format Specification
  • RTF: Rich Text Format
  • ISO/IEC 29500:2012(E) "Information technology — Document description and processing languages — Office Open XML File Formats"
  • Open Document Format for Office Applications Version 1.2 (29 September 2011)
  • Worksheet File Format (From Lotus) December 1984

Author: SheetJS
Source Code: 
License: Apache-2.0 License

#nodejs #javascript #html #ios 

What is GEEK

Buddha Community

SheetJS Community Edition - Spreadsheet Data Toolkit
 iOS App Dev

iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink


Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.


As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Cyrus  Kreiger

Cyrus Kreiger


How Has COVID-19 Impacted Data Science?

The COVID-19 pandemic disrupted supply chains and brought economies around the world to a standstill. In turn, businesses need access to accurate, timely data more than ever before. As a result, the demand for data analytics is skyrocketing as businesses try to navigate an uncertain future. However, the sudden surge in demand comes with its own set of challenges.

Here is how the COVID-19 pandemic is affecting the data industry and how enterprises can prepare for the data challenges to come in 2021 and beyond.

#big data #data #data analysis #data security #data integration #etl #data warehouse #data breach #elt

Macey  Kling

Macey Kling


Applications Of Data Science On 3D Imagery Data

CVDC 2020, the Computer Vision conference of the year, is scheduled for 13th and 14th of August to bring together the leading experts on Computer Vision from around the world. Organised by the Association of Data Scientists (ADaSCi), the premier global professional body of data science and machine learning professionals, it is a first-of-its-kind virtual conference on Computer Vision.

The second day of the conference started with quite an informative talk on the current pandemic situation. Speaking of talks, the second session “Application of Data Science Algorithms on 3D Imagery Data” was presented by Ramana M, who is the Principal Data Scientist in Analytics at Cyient Ltd.

Ramana talked about one of the most important assets of organisations, data and how the digital world is moving from using 2D data to 3D data for highly accurate information along with realistic user experiences.

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment, 3D data for object detection and two general case studies, which are-

  • Industrial metrology for quality assurance.
  • 3d object detection and its volumetric analysis.

This talk discussed the recent advances in 3D data processing, feature extraction methods, object type detection, object segmentation, and object measurements in different body cross-sections. It also covered the 3D imagery concepts, the various algorithms for faster data processing on the GPU environment, and the application of deep learning techniques for object detection and segmentation.

#developers corner #3d data #3d data alignment #applications of data science on 3d imagery data #computer vision #cvdc 2020 #deep learning techniques for 3d data #mesh data #point cloud data #uav data

Uriah  Dietrich

Uriah Dietrich


What Is ETLT? Merging the Best of ETL and ELT Into a Single ETLT Data Integration Strategy

Data integration solutions typically advocate that one approach – either ETL or ELT – is better than the other. In reality, both ETL (extract, transform, load) and ELT (extract, load, transform) serve indispensable roles in the data integration space:

  • ETL is valuable when it comes to data quality, data security, and data compliance. It can also save money on data warehousing costs. However, ETL is slow when ingesting unstructured data, and it can lack flexibility.
  • ELT is fast when ingesting large amounts of raw, unstructured data. It also brings flexibility to your data integration and data analytics strategies. However, ELT sacrifices data quality, security, and compliance in many cases.

Because ETL and ELT present different strengths and weaknesses, many organizations are using a hybrid “ETLT” approach to get the best of both worlds. In this guide, we’ll help you understand the “why, what, and how” of ETLT, so you can determine if it’s right for your use-case.

#data science #data #data security #data integration #etl #data warehouse #data breach #elt #bid data