Summary
In this chapter, we learned what the term data wrangling means. We also got examples from various real-life data science situations where data wrangling is very useful and is used in industry. We moved on to learn about the different built-in data structures that Python has to offer. We got our hands dirty by exploring lists, sets, dictionaries, tuples, and strings. They are the fundamental building blocks in Python data structures, and we need them all the time while working and manipulating data in Python. We did several small hands-on exercises to learn more about them. We finished this chapter with a carefully designed activity, which let us combine a lot of different tricks from all the different data structures into a real-life situation and let us observe the interplay between all of them.
In the next chapter, we will learn about the data structures in Python and utilize them to solve real-world problems.
