0

I am looking for books/tutorials that help you gain the insight into the thought process behind data analysis.

Most of the books I've read were mostly documentation - the author shows you a function and some data that he applies that function to. They also show how to use graphs and how histogram/boxplots etc. work. They go through popular libraries like numpy, pandas and how to use them.

I am interested in how people on (for example) Kaggle in their kernels on Titanic get their ideas from, on what to apply to datasets. Those people know which columns to plot as a function of each other, when to plot histograms, when to plot density functions and so on.

I am somewhat experienced in Machine Learning. It's pretty obvious which algorithm can be applied to what situation. Data exploring seems like a very ambiguous exercise with many solutions/ideas.

Another way to put is: Where to get the ideas for data exploration from?