During my daily work, I do a lot quick data checks on various (energy and development) indicators. For sure the classic way is to go EIA, BP, World Bank or one of the other large, established databases and copy the data into Excel or so and start staring. Nowadays, I would find it actually more convenient – and sometimes faster – to just directly load the data from the databank into a pandas dataframe and do a prettier-than-Excel plot with matplotlib. But if I want to share the data with somebody or make it interactive, this doesn’t cut it. Then I would turn to D3 and NVD3. However, loading the data into D3 is fairly cumbersome, this is not even the hardest part. If you want to eliminate the intermediary step of processing and formatting with pandas, then you have some serious work to do.
From now on, I will start slowly shifting to d3plus, developed by Alexander Simoes at the MIT Media Lab, because of its superiority of handling multiple visualization types, compared to nvd3.