Having been in industry for a while, my puzzle on this question still remains unsolved. What exactly is the relationship between visualization and feature engineering? While on Kaggle or elsewhere we can frequently bump into beautiful visualization of data. However, I myself see it little reference values when coming into how it helps in feature engineering. In particular, I can complete the entire feature engineering without plotting any graphs and still manage to get highly accurate models, by simply relying on statistics I print from data. And more often than not, those graphs neither fail to show precisely the intervals or the exact numerical values for a certain data field. To me, it's too approximative to be useful.
Thus, I'm seeing there's little use of visualization if I already can feature engineer based on calculating some statistics. I am looking for someone to correct my concept and point out what I've been missing in terms of the contributions of visualization in feature engineering, so I won't be so blind. TIA.