I have been working with data for more than 5 years now and my 2 cents is that Pandas shines with exploratory analysis. Because you have the data in memory it's

I have been working with data for more than 5 years now and my 2 cents is that Pandas shines with exploratory analysis. Because you have the data in memory it's easy to empirically arrive at the exact data transformation you need and figure out whether your analysis is worth pursuing further. At this stage of the development your ability to iterate and experiment quickly is most valuable. I see no value in worrying about the deployment of the work you are doing if you haven't got any results just yet. Now when the analysis is done and there's a conclusion about putting some of it in production, I am yet to see a single company that relies on pandas to do data transforms "online", i.e. on the live production data stream. Typically in my experience I would end up rewriting my data transforms in either a compiled language or SQL - i.e. something much more performant and maintainable. As a result as you progress in your career you become very proficient in both pandas and SQL - and you also start glancing at the source code of some of the transforms performed by pandas when you need to port them to the language of choice of the company you're working for.