Right, so defining data science as 90% sklearn+DL+numpy is just as silly as saying that it's 90% table manipulation. That's exactly my point.
Still, if anyone here has managed to find a data science job in which tabular data management is not a sizable piece of what you do, I'd like to know some details!
I imagine there are data scientists who operate primarily on unstructured rather than tabular data. Part of my current job involves stuff like text classification, and it's not that difficult to imagine someone for whom that's a more sizable proportion of their day-to-day.
Still, my suspicion -- at least from my corner of data science -- is that such individuals are rare, and that most data scientists do make use of tabular data more often than not.
I totally get what you mean - I would suspect that when you work with unstructured data, tabular data manipulation is maybe 20-40% of what you do, and when you work with structured data, it's more like 60-80%.
I worked as a datascientist for a couple of years and tabular data was a very small part of my job. I spent far more time with image-analysis and JSON, both of which I found R sucks at.
Still, if anyone here has managed to find a data science job in which tabular data management is not a sizable piece of what you do, I'd like to know some details!