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The JavaScript data transformation and analysis toolkit inspired by Pandas and LINQ.
Implemented in TypeScript.
Used in JavaScript ES5+ or TypeScript.
To install for Node.js and the browser:
npm install --save data-forge
If working in Node.js and you want the functions to read and write data files:
npm install --save data-forge-fs
Data-Forge can load CSV, JSON or arbitrary data sets.
Parse the data, filter it, transform it, aggregate it, sort it and much more.
Use the data however you want or export it to CSV or JSON.
Here's an example:
const dataForge = require('data-forge');
require('data-forge-fs'); // For readFile/writeFile.
dataForge.readFileSync('./input-data-file.csv') // Read CSV file (or JSON!)
.parseCSV()
.parseDates(["Column B"]) // Parse date columns.
.parseInts(["Column B", "Column C"]) // Parse integer columns.
.parseFloats(["Column D", "Column E"]) // Parse float columns.
.dropSeries(["Column F"]) // Drop certain columns.
.where(row => predicate(row)) // Filter rows.
.select(row => transform(row)) // Transform the data.
.asCSV()
.writeFileSync("./output-data-file.csv"); // Write to output CSV file (or JSON!)Data-Forge has been tested with Browserify and Webpack. Please see links to examples below.
If you aren't using Browserify or Webpack, the npm package includes a pre-packed browser distribution that you can install and included in your HTML as follows:
<script language="javascript" type="text/javascript" src="node_modules/data-forge/dist/web/index.js"></script>This gives you the data-forge package mounted under the global variable dataForge.
Please remember that you can't use data-forge-fs or the file system functions in the browser.
- Import and export CSV and JSON data and text files (when using Data-Forge FS).
- Or work with arbitrary JavaScript data.
- Many options for working with your data:
- Filtering
- Transformation
- Extracting subsets
- Grouping, aggregation and summarization
- Sorting
- And much more
- Great for slicing and dicing tabular data:
- Add, remove, transform and generate named columns (series) of data.
- Great for working with time series data.
- Your data is indexed so you have the ability to merge and aggregate.
- Your data is immutable! Transformations and modifications produce a new dataset.
- Build data pipeline that are evaluated lazily.
- Inspired by Pandas and LINQ, so it might feel familiar!
- Node.js (npm install --save data-forge data-forge-fs) (see example here)
- Browser
- Via bower (bower install --save data-forge) (see example here)
- Via Browserify (see example here)
- Via Webpack (see example here)