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But I don't want to learn 50 different tools that are all best-in-class. My use case is social media analysis of specific communities with fairly limited resources, so every hour that I spend on tooling is time not spent observing my subjects.

You're not wrong about the value of all the different tools you mention, but I think overlooking the integration and maintenance costs that a specialty tool can reduce, at the expense of some flexibility. I think that's the same reason many people prefer an IDE.




Learning the time tested tools almost always involves spending less time setting up / reading tutorials / etc. The time sink of betting the farm on latest and greatest data science frameworks is often gigantic and gets worse over time.




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