Data-Forge, inspired by the powerful tools Pandas and LINQ, is an elegant JavaScript data transformation and analysis toolkit. It allows you to manipulate and analyze data effortlessly using TypeScript and works with JavaScript ES5+ as well.

Installation

To get started with Data-Forge, you need to install it for Node.js and the browser.

• Run the following command to install Data-Forge:

npm install --save data-forge

• If you are working in Node.js and need functions to read and write data files, install the following:

npm install --save data-forge-fs

Quick Start Guide

With Data-Forge, you can load CSV, JSON, or arbitrary datasets. You can parse the data, filter it, transform it, aggregate it, sort it, and much more. Here’s a practical example to illustrate how you can leverage Data-Forge effectively:

const dataForge = require('data-forge');
require('data-forge-fs');

dataForge.readFileSync('input-data-file.csv')
    .parseCSV()
    .parseDates(['Column B'])
    .parseInts(['Column B', 'Column C'])
    .parseFloats(['Column D', 'Column E'])
    .dropSeries(['Column F'])
    .where(row => predicate(row))
    .select(row => transform(row))
    .asCSV()
    .writeFileSync('output-data-file.csv');

Think of Data-Forge like a well-organized kitchen for data. Just as a chef prepares and transforms raw ingredients to create a delicious dish, Data-Forge takes raw data and lets you finely chop, dice, and sauté it into a structured output. You first gather your ingredients (data), clean and prepare them (parse dates and ints), discard unwanted parts (drop series), and finally, serve (write to an output file). This analogy emphasizes how data can be manipulated in various ways to achieve the desired outcome.

Working with Data in the Browser

If you want to use Data-Forge in the browser, you can include it directly in your HTML after installing with Browserify or Webpack:

Just remember: you won’t be able to use file system functions in the browser.

Features of Data-Forge

• Import and export CSV and JSON data files when using Data-Forge FS.
• Filter, transform, extract, group, aggregate, and sort your data.
• Manipulate tabular data seamlessly with support for adding, removing, and transforming columns.
• Immutable data ensuring transformations produce new datasets.
• Build data pipelines that evaluate lazily.

Troubleshooting

If you encounter any issues, here are a few tips to help you out:

• Ensure that the correct package versions are installed. If you’re upgrading, note the breaking changes listed in the README.
• If you’re having trouble with AngularJS 6, be sure to check out the provided workaround.
• Have a dependency issue? Remember to check the documentation for updates or changes to APIs.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.