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http://vega.github.io/datalib/

JavaScript data utility library.
http://vega.github.io/datalib/

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JavaScript data utility library.

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# datalib



[![Build Status](https://travis-ci.org/vega/datalib.svg?branch=master)](https://travis-ci.org/vega/datalib)

[![npm version](https://img.shields.io/npm/v/datalib.svg)](https://www.npmjs.com/package/datalib)



_**NOTE:** Datalib is no longer being actively maintained. The [Arquero](https://github.com/uwdata/arquero) library provides similar functionality plus much more. In addition, Vega now includes its own data utilities in the [vega-util](https://github.com/vega/vega/tree/master/packages/vega-util) and [vega-statistics](https://github.com/vega/vega/tree/master/packages/vega-statistics) packages._



Datalib is a JavaScript data utility library. It provides facilities for data loading, type inference, common statistics, and string templates. While datalib was created to power [Vega](http://vega.github.io) and related projects, it is also a standalone library useful for data-driven JavaScript applications on both the client (web browser) and server (e.g., node.js).



For documentation, see the datalib [API Reference](../../wiki/API-Reference).



## Use



Datalib provides a set of utilities for working with data. These include:



- Loading and parsing data files (JSON, TopoJSON, CSV, TSV).

- Summary statistics (mean, deviation, median, correlation, histograms, etc).

- Group-by aggregation queries, including streaming data support.

- Data-driven string templates with expressive formatting filters.

- Utilities for working with JavaScript functions, objects and arrays.



Datalib can be used both server-side and client-side. For use in node.js,

simply `npm install datalib` or include datalib as a dependency in your package.json file. For use on the client, install datalib via `bower install datalib` or include datalib.min.js on your web page. The minified JS file is built using rollup (see below for details).



### Example



```javascript

// Load datalib.

var dl = require('datalib');



// Load and parse a CSV file. Datalib does type inference for you.

// The result is an array of JavaScript objects with named values.

// Parsed dates are stored as UNIX timestamp values.

var data = dl.csv('https://vega.github.io/datalib/data/stocks.csv');



// Show summary statistics for each column of the data table.

console.log(dl.format.summary(data));



// Compute mean and standard deviation by ticker symbol.

var rollup = dl.groupby('symbol')

  .summarize({'price': ['mean', 'stdev']})

  .execute(data);

console.log(dl.format.table(rollup));



// Compute correlation measures between price and date.

console.log(

  dl.cor(data, 'price', 'date'),      // Pearson product-moment correlation

  dl.cor.rank(data, 'price', 'date'), // Spearman rank correlation

  dl.cor.dist(data, 'price', 'date')  // Distance correlation

);



// Compute mutual information distance between years and binned price.

var bin_price = dl.$bin(data, 'price'); // returns binned price values

var year_date = dl.$year('date');       // returns year from date field

var counts = dl.groupby(year_date, bin_price).count().execute(data);

console.log(dl.mutual.dist(counts, 'bin_price', 'year_date', 'count'));

```



## Build Process



To use datalib in the browser, you need to build the datalib.js and datalib.min.js files. We assume that you have [npm](https://www.npmjs.com/) installed.



1. Run `npm install` in the datalib folder to install dependencies.

2. Run `npm run build`. This will invoke [rollup](https://rollupjs.org) to bundle the source files into datalib.js, and then [uglify-js](http://lisperator.net/uglifyjs/) to create the minified datalib.min.js.



### Webpack 1



If you are using Webpack 1, you need to enable a JSON-loader. To do so, first `npm install --save json-loader`, then add the loader to your webpack config:



```js

{

  module: {

    loaders: [{

      test: /\.json$/,

      loader: 'json-loader'

    }]

  }

}

```