Ask HN: What are some good exploratory data analysis tutorial in python?

I am basically confused by the term exploratory data analysis. I think it means things we should look for in a new dataset. But most of the data science tutorials do a kind of hand waving job on it before immediately jumping to the 'exciting' machine learning part. I would like to find out some tutorials where the author is not dealing with a toy dataset, but showing how to handle a messy real-life dataset, and what to look for in that dataset before jumping on a possible future machine learning part. Mostly, my wish is to give the abstract smoky concept of 'EDA' in my mind a concrete framework to work from when I encounter a new dataset in future.