forked from sheetjs/docs.sheetjs.com
Standalone Script Type Checks
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@ -90,9 +90,8 @@ For broad compatibility with JavaScript engines, the library is written using
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ECMAScript 3 language dialect. A "shim" script provides implementations of
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functions for older browsers and environments.
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Due to SSL compatibility issues, older versions of IE will not be able to
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use the CDN scripts directly. They should be downloaded and saved to a public
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directory in the site:
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Due to SSL compatibility issues, older versions of IE will not be able to use
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the CDN scripts directly. They should be downloaded and saved to a public path:
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<ul>
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<li>Standalone: <a href={"https://cdn.sheetjs.com/xlsx-" + current + "/package/dist/xlsx.mini.min.js"}>{"https://cdn.sheetjs.com/xlsx-" + current + "/package/dist/xlsx.mini.min.js"}</a></li>
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@ -118,12 +117,75 @@ importScripts("https://cdn.sheetjs.com/xlsx-${current}/package/dist/shim.min.js"
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importScripts("https://cdn.sheetjs.com/xlsx-${current}/package/dist/xlsx.full.min.js");`}
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</CodeBlock>
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### Type Checker
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:::danger VSCode Telemetry and Data Exfiltration
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The official Microsoft builds of Visual Studio Code embed telemetry and send
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information to external servers.
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**[VSCodium](https://vscodium.com/) is a telemetry-free fork of VSCode.**
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When writing code that may process personally identifiable information (PII),
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the SheetJS team strongly encourages building VSCode from source or using IDEs
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that do not exfiltrate data.
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:::
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The type checker integrated in VSCodium and VSCode do not currently provide type
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hints when using the standalone build. Using the JSDoc `@type` directive coupled
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with type imports, VSCodium will recognize the types:
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![VSCodium types](pathname:///files/standalone-types.png)
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<ol start="1">
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<li><p>Download the types (<code parentName="pre">index.d.ts</code>) for
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the desired version. The current version is available at <a href={"https://cdn.sheetjs.com/xlsx-" + current + "/package/types/index.d.ts"}>{"https://cdn.sheetjs.com/xlsx-" + current + "/package/types/index.d.ts"}</a></p></li>
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</ol>
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2) Rename the types file to `xlsx.d.ts`. It does not need to reside in the same
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folder as the standalone script.
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3) In the browser script referencing the global, prepend the following lines:
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```js title="Prepend this fragment in each source file referencing the XLSX global"
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/** @type {import("./xlsx")} */
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const XLSX = globalThis.XLSX;
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```
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4) If the `xlsx.d.ts` file is in a different folder, change the argument to the
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`import` method to reflect the relative path. For example, given the structure:
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```text title="Folder Structure"
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- /vendor
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- /vendor/xlsx.ts
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- /src
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- /src/app.js
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```
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`/src/app.js` must refer to the types as `../vendor/xlsx`:
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```js title="Preamble for /src/app.js when types are at /vendor/xlsx.d.ts"
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// highlight-next-line
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/** @type {import("../vendor/xlsx")} */
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const XLSX = globalThis.XLSX;
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```
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The `.d.ts` file extension must be omitted.
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:::warning pass
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JSDoc types using the `@import` directive are not supported in `<script>` tags.
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**This is a known bug with VSCode!**
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:::
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## ECMAScript Module Imports
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:::caution pass
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This section refers to imports in HTML pages using `script type="module"`.
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This section refers to imports in HTML pages using `<script type="module">`.
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The ["Frameworks and Bundlers"](/docs/getting-started/installation/frameworks)
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section covers imports in projects using bundlers (ViteJS) or frameworks
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@ -367,6 +367,9 @@ function SheetJSToTFJSCSV() {
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#### NodeJS Demo
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<details>
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<summary><b>Demo Steps</b> (click to show)</summary>
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0) Create a new project:
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```bash
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@ -393,6 +396,8 @@ npm i --save https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz @tensor
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node SheetJSTF.js
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```
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</details>
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#### Kaioken Demo
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:::tip pass
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@ -404,6 +409,9 @@ The SheetJS team strongly recommends using Kaioken in projects using TF.js.
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:::
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<details>
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<summary><b>Demo Steps</b> (click to show)</summary>
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1) Create a new site.
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```bash
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@ -470,6 +478,8 @@ The process will display a URL:
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Open the displayed URL (`http://localhost:5173/` in this example) with a web
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browser. Click the "Click to Run" button to see the results.
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</details>
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## JS Array Interchange
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[The official Linear Regression tutorial](https://www.tensorflow.org/js/tutorials/training/linear_regression)
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@ -508,17 +518,19 @@ Differences from the official example are highlighted below:
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*/
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async function getData() {
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// highlight-start
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/* fetch file */
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/* fetch file and pull data into an ArrayBuffer */
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const carsDataResponse = await fetch('https://docs.sheetjs.com/cd.xls');
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/* get file data (ArrayBuffer) */
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const carsDataAB = await carsDataResponse.arrayBuffer();
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/* parse */
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const carsDataWB = XLSX.read(carsDataAB);
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/* get first worksheet */
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const carsDataWS = carsDataWB.Sheets[carsDataWB.SheetNames[0]];
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/* generate array of JS objects */
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const carsData = XLSX.utils.sheet_to_json(carsDataWS);
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// highlight-end
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const cleaned = carsData.map(car => ({
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mpg: car.Miles_per_Gallon,
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horsepower: car.Horsepower,
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@ -560,8 +572,8 @@ When a `tensor2d` can be exported, it will look different from the spreadsheet:
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```js
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const data_set_2d = [
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[5.1, 4.9, ...],
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[3.5, 3, ...],
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[5.1, 4.9, /*...*/],
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[3.5, 3, /*...*/],
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// ...
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];
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```
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@ -572,49 +584,85 @@ This is the transpose of how people use spreadsheets!
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The `aoa_to_sheet` method[^11] can generate a worksheet from an array of arrays.
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ML libraries typically provide APIs to pull an array of arrays, but it will be
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transposed. To export multiple data sets, the data should be transposed:
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transposed. The following function transposes arrays of normal and typed arrays:
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```js title="Transpose array of arrays"
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/* `data` is an array of (typed or normal) arrays */
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function transpose_array_of_arrays(data) {
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const aoa = [];
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for(let i = 0; i < data.length; ++i) {
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for(let j = 0; j < data[i].length; ++j) {
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if(!aoa[j]) aoa[j] = [];
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aoa[j][i] = data[i][j];
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}
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}
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return aoa;
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}
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```
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It is recommended to create a new worksheet from the header row and add the
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transposed data using the `sheet_add_aoa` method. The option `origin: -1`[^12]
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ensures that the data is written after the headers:
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```js
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/* assuming data is an array of typed arrays */
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const aoa = [];
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for(let i = 0; i < data.length; ++i) {
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for(let j = 0; j < data[i].length; ++j) {
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if(!aoa[j]) aoa[j] = [];
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aoa[j][i] = data[i][j];
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}
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}
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/* aoa can be directly converted to a worksheet object */
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const ws = XLSX.utils.aoa_to_sheet(aoa);
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const headers = [ "sepal length", "sepal width"];
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const data_set_2d = [
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[5.1, 4.9, /*...*/],
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[3.5, 3, /*...*/],
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// ...
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];
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// highlight-start
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/* transpose data */
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const transposed_data = transpose_array_of_arrays(data_set_2d);
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// highlight-end
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/* create worksheet from headers */
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const ws = XLSX.utils.aoa_to_sheet([ headers ])
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/* add the transposed data starting on row 2 */
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XLSX.utils.sheet_add_aoa(ws, transposed_data, { origin: 1 });
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```
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### Importing Data from a Spreadsheet
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`sheet_to_json` with the option `header: 1`[^12] will generate a row-major array
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`sheet_to_json` with the option `header: 1`[^13] will generate a row-major array
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of arrays that can be transposed. However, it is more efficient to walk the
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sheet manually:
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sheet manually. The following function accepts a number of header rows to skip:
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```js
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/* find worksheet range */
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const range = XLSX.utils.decode_range(ws['!ref']);
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const out = []
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/* walk the columns */
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for(let C = range.s.c; C <= range.e.c; ++C) {
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/* create the typed array */
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const ta = new Float32Array(range.e.r - range.s.r + 1);
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/* walk the rows */
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for(let R = range.s.r; R <= range.e.r; ++R) {
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/* find the cell, skip it if the cell isn't numeric or boolean */
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const cell = ws["!data"] ? (ws["!data"][R]||[])[C] : ws[XLSX.utils.encode_cell({r:R, c:C})];
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if(!cell || cell.t != 'n' && cell.t != 'b') continue;
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/* assign to the typed array */
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ta[R - range.s.r] = cell.v;
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```js title="Worksheet to transposed array of typed arrays"
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function sheet_to_array_of_f32(ws, header_row_count) {
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const out = [];
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/* find worksheet range */
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const range = XLSX.utils.decode_range(ws['!ref']);
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/* skip specified number of headers */
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range.s.r += (header_row_count | 0);
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/* walk the columns */
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for(let C = range.s.c; C <= range.e.c; ++C) {
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/* create the typed array */
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const ta = new Float32Array(range.e.r - range.s.r + 1);
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/* walk the rows */
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for(let R = range.s.r; R <= range.e.r; ++R) {
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/* find the cell, skip it if the cell isn't numeric or boolean */
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const cell = ws["!data"] ? (ws["!data"][R]||[])[C] : ws[XLSX.utils.encode_cell({r:R, c:C})];
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if(!cell || cell.t != 'n' && cell.t != 'b') continue;
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/* assign to the typed array */
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ta[R - range.s.r] = cell.v;
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}
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/* add typed array to output */
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out.push(ta);
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}
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out.push(ta);
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return out;
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}
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```
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If the data set has a header row, the loop can be adjusted to skip those rows.
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### TF.js Tensors
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A single `Array#map` can pull individual named fields from the result, which
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@ -674,4 +722,5 @@ const worksheet = XLSX.utils.aoa_to_sheet(aoa);
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[^9]: See [`sheet_to_json` in "Utilities"](/docs/api/utilities/array#array-output)
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[^10]: See [`sheet_to_json` in "Utilities"](/docs/api/utilities/array#array-output)
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[^11]: See [`aoa_to_sheet` in "Utilities"](/docs/api/utilities/array#array-of-arrays-input)
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[^12]: See [`sheet_to_json` in "Utilities"](/docs/api/utilities/array#array-output)
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[^12]: See [the `origin` option of `sheet_add_aoa` in "Utilities"](/docs/api/utilities/array#array-of-arrays-input)
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[^13]: See [`sheet_to_json` in "Utilities"](/docs/api/utilities/array#array-output)
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@ -191,6 +191,7 @@ This demo was tested in the following environments:
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| macOS 14.4 | `darwin-x64` | `29.1.4` | 2024-03-15 |
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| macOS 14.5 | `darwin-arm` | `30.0.8` | 2024-05-28 |
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| Windows 10 | `win10-x64` | `31.2.0` | 2024-07-12 |
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| Windows 11 | `win11-x64` | `31.2.0` | 2024-08-18 |
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| Windows 11 | `win11-arm` | `30.0.8` | 2024-05-28 |
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| Linux (HoloOS) | `linux-x64` | `29.1.4` | 2024-03-21 |
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| Linux (Debian) | `linux-arm` | `30.0.8` | 2024-05-28 |
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docz/static/files/standalone-types.png
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docz/static/files/standalone-types.png
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