You're definitely correct that its a nuanced question whether for a given (user, analysis) pair they are better off in Excel or Python/R/etc. Specifically with respect to building intuition for a dataset, however, there is a huge benefit of having an interactive data representation (if only for the ability to scroll and see all of your data).

Because you can think of Mito as a frontend interface to Pandas, using Mito doesn't prohibit you from building intuition or analyzing your data in the same way you would if you didn't have the spreadsheet frontend. It just helps you write the Python/Pandas code faster + see the most up to date version of your data set in live time.

The typical Mito user uses Mito multiple times throughout an analysis. A common pattern is: start by just visualizing the data in Mito, create a few graphs to help understand the distribution using matplotlib (right now we only have a tiny bit of graphing support), passing the data back into Mito to do some filtering and cleaning, then lastly creating a pivot table output using Mito. Of course, it varies greatly from user to user, but that's a general flow we see often!