Here are the basic Python data structures that you need to learn to be as proficient as a data scientist. Leaving aside the real basics (numbers, arithmetic, strings, Booleans, variable assignments, and comparisons), the list is indeed short. We will briefly deal with it by touching upon only the recurrent structures in data science projects. Remember that the topics are quite challenging, but they are necessary to master if you want to write effective code:
- Lists
- Dictionaries
- Classes, objects, and object-oriented programming
- Exceptions
- Iterators and generators
- Conditionals
- Comprehensions
- Functions
Take it as a refresher or a learning list depending on your actual knowledge of the Python language. However, examine all the proposed examples because you will come across them again during the course of this book.
