Rediscovering Data Structures from Childhood

🧸 As kids, we unknowingly used data structures all the time.

Now, let's rediscover these hidden gems from our childhood:

📚 Arrays
🔗 Lists
🥞 Stacks
🎢 Queues
🌳 Trees
🗺️ Graphs

Here's how I'd explain them to a 5-year-old in a single tweet each.

A thread:

— Francesco (@FrancescoCiull4) April 10, 2023

Learning data structures doesn't have to be boring! Discover these fundamental tools in a fun and engaging way with @brilliantorg.

Their courses break down complex concepts into easy-to-understand building blocks.

Try them out for yourself at https://t.co/xaHSNNArQQ

— Francesco (@FrancescoCiull4) April 10, 2023

📚Array

An array is like a long shelf with several compartments to put things in a specific order.

You can quickly find the item you want if you know its position on the shelf.

— Francesco (@FrancescoCiull4) April 10, 2023

💡Interesting fact:

Arrays can hold more than just numbers or words! They can store other arrays, called multidimensional arrays. A 2D array can be used to create a grid-like structure, also called Matrix.

— Francesco (@FrancescoCiull4) April 10, 2023

🔗 List

A list is similar to an array, but it's like a magic shelf that can grow or shrink depending on how many items you want to store.

You can add or remove items quickly, but finding a specific item might take longer.

— Francesco (@FrancescoCiull4) April 10, 2023

About linked lists, if you want to know more, there is a very understandable lesson in the "Data Structures course" on @brilliantorghttps://t.co/xaHSNNArQQ pic.twitter.com/aoZxtOg20v

— Francesco (@FrancescoCiull4) April 10, 2023

Imagine a stack of pancakes.

With a stack data structure, you can only add a new pancake on top or take the top one off, just like when you eat pancakes, you start from the top.

This is called LIFO (Last-In-First-Out).

— Francesco (@FrancescoCiull4) April 10, 2023

💡Stacks can be used to perform algorithms such as Depth-First Search (DFS) of tree/graph data structures.

By keeping track of visited nodes using a stack, we can explore the structure in a way that prioritizes going deeper into the structure before exploring other branches.

— Francesco (@FrancescoCiull4) April 10, 2023

🎢Queue

A queue is like a line of people waiting to get on a ride at an amusement park.

The person who arrives first goes on the ride first, and new people join the line at the end.

This is called FIFO (First-In-First-Out or FIFO).

— Francesco (@FrancescoCiull4) April 10, 2023

💡 Another use of the queue is in simulating a print spooler to manage multiple print requests from different users.

Each print request is added to the queue & processed in a first-come, first-served manner: each print job is processed in the order it was received.

— Francesco (@FrancescoCiull4) April 10, 2023

🌳 Tree

A tree is like a family tree, with a root at the top & branches below.

Each item (except the root) has a parent & may have children.

Organizes info for easy searching!

— Francesco (@FrancescoCiull4) April 10, 2023

💡Interesting fact about trees:

Did you know that adding extra edges between nodes can turn a tree into a graph?

This process is called "grafting".

It can be helpful in graph algorithms that require a tree-like structure.

But what are graphs?

— Francesco (@FrancescoCiull4) April 10, 2023

🗺️Graphs

Graphs are like maps that show how things are connected. (even a virtual one is a good example!)

For example, on a map of your town, a graph can help you see how your house, the park, the grocery store, and your friend's house are all connected.

— Francesco (@FrancescoCiull4) April 10, 2023

That's all, folks!

We've explored some of the most fascinating and useful data structures, from arrays to graphs.

This was a good point to start, but definitely not the end!

— Francesco (@FrancescoCiull4) April 10, 2023

If you want to know more about algorithm complexity, you can check this excellent course by @brilliantorghttps://t.co/xaHSNNAZGo pic.twitter.com/C3QOrsYFcU

— Francesco (@FrancescoCiull4) April 10, 2023