Summary

In this chapter we started our travel around the data world on board of Titanic. We started with a preliminary statistical analysis of each feature, we continued with univariate analysis, feature engineering to create derived or aggregated features. We extracted multiple features from text, and we also created complex graphs, to visualize multiple features at the same time and reveal their predictive value. We also learned how to assign a uniform visual identity for our analysis by using a custom colormap across the Notebook. For some of the features, most notably those derived from Names, we perform a deep-dive exploration, to learn about the fate of large families on Titanic or name distribution according to the embarking port. Some of the analysis and visualization tools are easy reusable and in one of the next chapters we will see how to extract them to be as utility scripts in other Notebooks as well.