I also found myself reading the manual all the time.
I have a toy project I use for learning different tools. Given a CSV containing every MLB game ever played, calculate the win percentage for each team during its first season.
Pandas makes that kind of simple thing painfully unintuitive. Tools like Polars and dplyr and even SQL require code that's far closer to how people think.
Learn SQL and interface with Duck. You will be 100x faster than Pandas/Polaris duo at fraction of memory. Also SQL is supported literally everywhere with a much more capable than Pandas API. Duck outputs to a Pandas Dataframe, but just treat that like a dictionary. Do all your processing, filtering and aggregation in Duck.
Also, try fx.wtf as a replacement for jq. it comes with a in-built tui viewer that supports vi-keybindings. Ecmascript is built into fx.wtf so you can query the JSON with JS notation (where JSON was born). You can use any JS functions including map/reduce/filter or perform any kind of transformation instead of learning jq dsl that you will forget tomorrow.
In that regard, I’m still waiting for a credible jq replacement…