With this CSV example:
Source,col1,col2,col3
foo,1,2,3
bar,3,4,5
The standard method I use Pandas is this:
Parse CSV<
I think the closest thing are libraries like:
Recline in particular has a Dataset object with a structure somewhat similar to Pandas data frames. It then allows you to connect your data with "Views" such as a data grid, graphing, maps etc. Views are usually thin wrappers around existing best of breed visualization libraries such as D3, Flot, SlickGrid etc.
Here's an example for Recline:
// Load some data
var dataset = recline.Model.Dataset({
records: [
{ value: 1, date: '2012-08-07' },
{ value: 5, b: '2013-09-07' }
]
// Load CSV data instead
// (And Recline has support for many more data source types)
// url: 'my-local-csv-file.csv',
// backend: 'csv'
});
// get an element from your HTML for the viewer
var $el = $('#data-viewer');
var allInOneDataViewer = new recline.View.MultiView({
model: dataset,
el: $el
});
// Your new Data Viewer will be live!