I agree completely that SQL is not the language for the kind of data analysis you're discussing in this book - to me, the question is whether it's useful to do

I agree completely that SQL is not the language for the kind of data analysis you're discussing in this book - to me, the question is whether it's useful to do querying and filtering through SQL and data analysis through python and R on the resulting datasets. I think pretty much everything you've written here would be continue useful if you used sqldf to generate data frames in R, but I don't know R well enough to be sure of that. Because pandasql returns a data frame from a data frame (not sure if this is the case with R), I find it relatively easy to do data things with sql and data analysis with python. However, that's not a huge surprise since I've been using SQL for a while but don't know the pandas or R data frame syntax especially well. I'm not sure why sqlite was chosen - could it have to do with the in-memory nature of dataframes? So far, my use of sql with data frames has been pretty generic, so I haven't bumped up any implementation specific SQL issues.