Yet another beautiful day in data town, pd is having a field day, since the missing import issue was fixed we have been on the row just then NULL|NAN values are displayed.
There is something endearing about pandas. All these attributes and yet still so cool. It takes one who loves data and understands pd to avoid a clash like the one that happened yesterday between concat and merge.
Yes, they have both come a long way but sometimes the data Engineer(DE) tries to fit a round peg in a square one, during transformation. The famous ETL has changed with the times, these days we have more of ELT-RL
One main issue is with our favorite nulls and NAN. Have you tried calling .concat on pd for multiple lists with different row count based on a unique key? And forgetting to specify the key? But then what about the other values on the table? If they don’t match we might be missing the details?
A lot of questions I know but that was how confused the DE was yesterday. Teamwork, a little googling, reading pandas documentation and stack-overflow helped the day. “It feels good when the proper middle name is called to action”.
At the end of the day, NAN|Null is not an enemy. Like every story, our imperfections make us perfect. To understand your data, listen to the story it is telling.