Do you know what are the top & most common Data Structures that you should be aware of as a programmer? Have you ever thought about what will be the list of Data Structures where you should have expertise? Let us try to make a list of the Data Structures that are commonly used in most programs.
But before start making the list of Data Structures, we need to first know about the Data Structures. We can assume you have a basic idea of the programming language. So first, we will concentrate on the definition of Data Structures. Then we will move to the topmost Data Structures list.
In the term “Data Structures”, we first focus on the word ‘Data’. Writing programming is like playing with data. There will be several data will be provided to you. Sometimes, while calculating some more data might arise from inside the program. Among those data, you need to find out the result by doing some calculations. It is a common process in every programming language. Now, if the number of data is huge in a program then you need to store them properly. So that, you can derive the data easily in the future. Also, you have to reduce the memory consumption of the device while writing the program.
In this context, the word ‘Structure’ need to be emphasized. A range of data can be easily accessible if they are stored structurally. It will help to reduce the memory consumption of any program whatever the number of data is being used there. Data Structures help to do the same thing. It is a concept that helps to learn programmers how to store a large number of data in a program. For that purpose, there are several structures are present. Each of them is different from the others. Among those, we will find out some important & top Data Structures that you should know. Also, If you are stuck in programming or coding then you can reach out to CodingZap for assistance regarding Data Structure.
List Of Top Data Structures:
Now as we have discussed the Data Structures concept briefly, we need to move to the list of the top Data Structures that you should be aware of. You need to focus on the following Data Structures concept well in your academics to grab good marks. So, let us focus on the following list:
Array: The first Data Structure concept will be the Array. An array can be visualized as a list of elements. You can store an infinite number of elements in this Data Structure. But if you try to place the integers in this structure, all other elements should be integers there. It means you can’t able to store different types of elements in one single array.
Linked List: It is another important Data structure that needs to be focused on. It might look like an array, but the concept is different. Here, the dynamic memory allocation process is followed. And here, different types of an element can be stored simultaneously. Also, picking up & removing an element from this concept is very easy rather than an array.
Stack: A stack is another Data Structure built up by either the Array concept or the Linked List concept. But their policy of storing data is completely different. In Stack, elements that are stored first will be removed at the last. And the element which is stored at the last will be removed at first. This addition & removal policy is known as Last-In-First-Out (LIFO).
Queue: The queue concept might look similar to the Stack concept, but there is some difference. The Queue concept is also built up with the help of the Array or Linked List. Here, the element which is stored first needs to be removed first. And the element which is stored last will be removed from the list at the last. This process is known as the First-In-First-Out (FIFO).
Hash Table: A hash Table is a concept that allocates elements in the table along with some index value & key value. These number needs to recognize an element from the list efficiently. Programmers need to use the key concept to mark the element in the Hash Table. The Hash table was created with the help of the Linked List concept. And there is no element insertion & deletion policy present as the Stack & Queue.
Tree: A tree is a concept that helps to define a complex problem. In a problem, if there is a large number of dataset present that needs to be aligned in the tree structure. There are different tree structures are present like Binary Trees. Based on the leaf number in the tree, the pattern is corrected. The Tree itself is a big topic. That needs to be discussed separately.
Graph: Graph is an advanced topic in Data Structures. Graph concept is developed from the Tree concept. Whereas the Tree concept is developed from the Linked List. Here, every node in the graphs has some values. And the edges in the graphs also get some values. It helps to find out the path that is minimum to go to a target node. This concept is highly needed in the Map development process. It is not considered a typical Data Structure.