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Quickly browse and filter csv files from a web front-end. Built on D3.js


Prereq: d3.js is included on your page.

Include d3.data_grid.js or d3.data_grid.min.js.

Create a new data_grid object, passing in the id of where it should be placed:

var data_grid = new data_grid.DataGrid("data_grid", options);

Use the d3.js functionality to load a csv, tsv, or json file:

d3.csv(options.filename, data_loaded);

In your data_loaded, call the show method of your data_grid:;


If you have python installed, simply start up the built-in server:

python -m SimpleHTTPServer 8888

and navigate to localhost:8888/demo


The Problem : We wanted to provide a quick look at large sets of data and allow for filtering and quick understanding. Essentially, we wanted a super basic version of Excel that ran in the browser.

We wanted to be able to throw in a csv or tsv file and have it rendered nicely.

We didn’t want to have to specify what type of data each column contained.

We wanted it to be fast.

We didn’t want any backend.

The Solution : Existing javascript solutions I looked at either required a html table to work on, or required explicit information about the data being displayed.

d3.data_grid is fast, as it uses pagination (currently very basic) instead of attempting to display the entire dataset at one time. However, filtering works on the entire dataset – so you are not limited by only seeing part of your data.

d3.data_grid is built on d3.js – which allows for interesting and informative visualizations of your rows and columns (currently very basic).

d3.data_grid works with data parsed by d3. So it can work on csv or json files with no problems. Using d3.tsv , you can also easily parse tsv files.

d3.data_grid uses the same filtering code as the picnet table filter , but doesn’t rely on jquery, or closure. Picnet Table filter is a great solution for this kind of problem. I completely recommend using it if you want a mature and stable form of this kind of filtering that works on html tables, or uses a back-end.

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