Welcome to our lesson on integrating multiple techniques for comprehensive data analysis! Today, we'll dive deep into the Titanic dataset, using powerful functions and methods from pandas and numpy to uncover valuable insights. The goal is to learn how to combine techniques like groupby, merge, and pivot tables for thorough analysis.

Integrating multiple techniques is like preparing a delicious meal: you combine several ingredients to create a rich, flavorful dish. Similarly, combining data analysis techniques helps extract deeper insights from data.

Let's start stepping through our code!

First, we'll group the data by class and sex and calculate the mean values. Grouping helps us understand patterns within subgroups.

Using reset_index here is necessary to convert the multi-level index (created by the groupby operation) back into regular columns of the DataFrame. Without resetting the index, the resulting DataFrame would have and as index levels, which can complicate further data manipulation and readability