"An approximate answer to the right question is worth a great deal more than a precise answer to the wrong question."
Exploratory data analysis is a fascinating area as it blends the art of conversation, skills of data science, and aspects of the domain being studied. It is a structured process where you discover information about the data characteristics and relationships among two or more variables.
The biostatistician, Roger Peng, has said that developing questions is a practical way of reducing the exponential number of ways you can explore a dataset. In particular, a sharp question or hypothesis can serve as a dimension reduction tool that can eliminate variables that are not immediately relevant to the question (Peng, 2015, p. 17).
The use case highlights the importance of asking good questions. Your success in conducting exploratory data analysis will rely on your skills as an investigator. For a moment, take on...