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    You are at:Home ยป The 10 Best Data Structures for Day to Day use

    The 10 Best Data Structures for Day to Day use

    0
    By AM on May 7, 2023 Databases

    List: A list is a collection of items that are Organized in a particular order. Imagine you have a list of your favorite toys. You might put them in order from your most Favourite to your least favourite. Lists are useful when you want to keep things in order or when you want to easily add or remove items from the list.

    Example: A grocery list is a type of list. It helps you keep track of the things you need to buy at the store, in the order you want to find them.

    Array: An array is a collection of items that are stored in a specific order and can be accessed by their position in the array. Imagine you have a row of toy boxes, each labeled with a number. You can easily find a specific toy by knowing its box number. Arrays are useful when you want to work with a large collection of data and need to be able to quickly access individual items.

    Example: A collection of your favorite snacks, each labeled with a number, could be stored in an array so you can easily find the one you want.

    The 10 Best Day to Day Use Data Structures

    Queue: A queue is a collection of items where the first item added is the first item removed. Imagine a line of people waiting to get on a ride at an amusement park. The first person in line is the first person to get on the ride. Queues are useful when you need to keep track of items in the order they were added.

    Example: Imagine a queue of animals waiting to get into the zoo. The first animal to arrive would be the first to get in.

    Stack: A stack is a collection of items where the last item added is the first item removed. Imagine a stack of pancakes. The last pancake added is the first one to be taken off the stack. Stacks are useful when you need to keep track of items in a “last-in, first-out” order.

    Example: Imagine a stack of books. The last book added is the first one to be taken off the stack.

    Heap: A heap is a collection of items where the highest (or lowest) priority item is always at the top. Imagine a pile of toys, each with a certain value. The toy with the highest value is always at the top of the pile. Heaps are useful when you need to keep track of the highest or lowest priority items.

    Example: Imagine a heap of fruits, with each fruit having a certain value. The fruit with the highest value (e.g., the ripest) is always at the top of the heap.

    Tree: A tree is a collection of items that are organized in a hierarchical structure. Imagine a family tree, where each person is connected to their parents and children. Trees are useful when you need to organize items into a hierarchical structure.

    Example: A file system on a computer is organized like a tree, with folders containing files and subfolders.

    Suffix Tree: A suffix tree is a special type of tree that is used to efficiently search for substrings within a larger string. Imagine a long book and you want to quickly find all instances of a particular word. A suffix tree can help you do that. Suffix trees are useful when you need to search for substrings in a large piece of text.

    Example: A suffix tree could be used to quickly find all instances of the word “apple” in a large document.

    Graph: A graph is a collection of items (called “nodes” or “vertices”) that are connected by edges. Imagine a map of a city, where each intersection is a node and the roads connecting them are the edges. Graphs are useful when you need to represent relationships between items.

    For example, on a social media platform like Facebook, each user would be represented as a node in the graph, and the edges would represent the connections between them such as friend requests, followers, or mutual friends

    R-Tree: An R-tree is a special type of tree used for storing and querying spatial data. Imagine a map with different types of landmarks (e.g., restaurants, parks, stores). An R-tree can help you efficiently find all landmarks within a certain distance from a given point. R-trees are useful when you need to store and query spatial data.

    Example: An R-tree could be used to find all restaurants within a 5-mile radius of your current location.

    Hashtable: A hashtable is a collection of key-value pairs. Imagine a box of keys, each labeled with the name of a toy, and a corresponding box of values, each containing a description of the toy. A hashtable can help you quickly find the description of a toy by its name. Hashtables are useful when you need to store and quickly access key-value pairs.

    Example: A hashtable could be used to store the name and phone number of all your friends, with the name as the key and the phone number as the value. This way, you can quickly find a friend’s phone number by their name.

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    AM, The Founder and CEO of RetailMarketingTechnology.com is an Entrepreneur & Business Management Professional with over 20+ Years Experience and Expertise in many industries such as Retail, Brand, Marketing, Technology, Analytics, AI and Data Science. The Industry Experience spans across Retail, FMCG, CPG, Media and Entertainment, Banking and Financial Services, Media & Entertainment, Telecom, Technology, Big Data, AI, E-commerce, Food & Beverages, Hospitality, Travel & Tourism, Education, Outsourcing & Consulting. Currently based in Austria and India

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