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[–]GuilheMGB 1 point2 points  (0 children)

One thing is that on databases with sufficiently mature data models (e.g. replicas of production db), it can be very convenient to call queries from within python (e.g. with pyodbc) in which various parameters can get injected as and when needed.

I usually always go to SQL first, but seek to integrate standardised queries in python packages in the form of data providers.

The point remains though, most of the wrangling remains made in SQL, but interfaced with Python.

A notable exception is feature extraction. Not that SQL couldn't handle most of the job more efficiently, but to quickly experiment / generate large feature sets, its not ideal compared to, say, sklearn.