Seconding the IPython Notebook. I've used matplotlib but also like Plot.ly for its prettier, more sharable charts.
It's also not a huge amount of work to set up a JSON-Flask-D3 visualisation pipeline out of test data; that's exactly what I did for my current data project, using cubism.js to easily visualise a time series. Again, benefits are the ability to easily share.
Also, sometimes, Google Spreadsheets/Excel can be the easiest solution to throw up quickly - or using built-in data explorations in RStudio. I've also thrown graph data into Neo4j because it gives you a nice visual interface for free.