Python Data Structures Cheat Sheet: A Quick Reference Guide

Introduction

Data Manipulation is a very important aspect of dealing with data within the Python programming ecosystem. The language comes with inbuilt data structures for efficient packaging and management of data.

In this article, I present you with a comprehensive Cheat Sheet covering Data Structures in Python programming. This Cheatsheet will serve as a generous reference for the operations of data structures helping you write concise and clean code.

Read further to explore this guide!

1. Lists:

   • Creation: my_list = [] or my_list = list()

   • Accessing Elements: my_list[index]

   • Modifying Elements: my_list[index] = value

   • Adding Elements: my_list.append(value) or my_list.insert(index, value)

   • Removing Elements: my_list.remove(value) or del my_list[index]

2. Tuples:

   • Creation: my_tuple = () or my_tuple = tuple()

   • Accessing Elements: my_tuple[index]

   • Immutable: Tuples are immutable, meaning their values cannot be changed after creation.

   • Useful for representing fixed collections of items.

3. Sets:

   • Creation: my_set = set() or my_set = {value1, value2, value3}

   • Adding Elements: my_set.add(value)

   • Removing Elements: my_set.remove(value)

   • Set Operations: Union (|), Intersection (&), Difference (-), Symmetric Difference (^)

4. Dictionaries:

   • Creation: my_dict = {} or my_dict = dict()

   • Adding/Updating Elements: my_dict[key] = value

   • Accessing Elements: my_dict[key]

   • Removing Elements: del my_dict[key]

   • Useful for storing key-value pairs and fast lookup operations.

5. Strings:

   • Creation: my_string = "Hello, World!"

   • Accessing Characters: my_string[index]

   • Slicing: my_string[start:end]

   • String Concatenation: new_string = string1 + string2

   • String Methods: len(), split(), join(), lower(), upper(), replace(), and more.

6. Arrays (from the array module):

   • Creation: import array then my_array = array.array('type_code', [elements])

   • Accessing Elements: my_array[index]

   • Modifying Elements: my_array[index] = value

   • Supported data types include 'b' (signed char), 'B' (unsigned char), 'f' (float), 'i' (signed int), and more.

Conclusion

This Cheat Sheet provides a reference for basic data structures(lists, tuples, sets, dictionaries, strings, and arrays.) With this cheat sheet handy, you can quickly refresh your memory and choose the appropriate data structure for your specific use cases. Remember to leverage the built-in methods and operations provided by Python to maximize your productivity and write clean, elegant code. Happy coding with Python's powerful data structures!