zlacker

>>heyden+(OP)
This is why I like tools like datastation and hex.tech. You write the initial query using SQL than process the results as a dataframe using Python/pandas. Surely, mixing Pandas and SQL like that is not good for data pipelines but for exploration and analytics, I have found this approach to be enjoyable.

>>ahmed_+SPa
Yes, it's very convenient to be able to use SQL with your massively parallel commercial database (Oracle, Snowflake, etc.) and then again with the results sets (Pandas, etc.). Interestingly, it's a concept that was implemented 35 years ago in SAS (link below) but is just now gaining traction in today's "modern" software (e.g., via DuckDB).

USING THE NEW SQL PROCEDURE IN SAS PROGRAMS (1989) https://support.sas.com/resources/papers/proceedings-archive... The Sql procedure uses SQL to create, modify, and retrieve data from SAS data sets and views derived from those data sets. You can also use the SOL procedure to join data sets and views with those from other database management systems through the SAS/ACCESS software interfaces.