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Embarking on a 100-day adventure: Day 5 – No.Of Occurrences In An Array

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Welcome to Day 5 of our coding journey! Today, we dive deep into the world of programming to tackle a common, yet curious problem: finding the number of occurrences of a specific value within an array. Brace yourself as we unravel the magic behind an elegant solution utilizing the power of HashMaps.

The Journey for Occurrence Count:

In the middle of our array adventures, a common challenge surfacesâ€”how often does a particular value appear within an array? This simple question unfolds into a journey that starts with developers across various domains. In data analysis, understanding the distribution of values becomes paramount. In algorithmic problem-solving, decoding the frequency of the key elements is often the key to optimization.

Introducing the HashMap:

In our search for an efficient solution, we turn to the flexible HashMap, a key-value pair storage mechanism within the extensive Collections framework. The HashMap proves to be our trusted partner in effortlessly tallying the occurrences of each element in an array.

The Code Unveiled:

Let’s take a peek at the code that makes this magic happen:

Breaking Down The Code:

The code begins by initializing an integer array ‘a’ containing a sequence of numbers. The variable ‘v’ represents the value whose occurrences we want to count within the array. A ‘HashMap’ named ‘map’ is created to store element-frequency pairs. The key represents the array element, and the value represents the frequency (number of occurrences). The code uses a ‘for each’ loop to iterate through each element of the array ‘a’. For each element ‘i’, the code checks whether it is already in the ‘HashMap ‘ using ‘map.containsKey(i)’.

If present, it increments the frequency by 1. If not present, it adds the element to the ‘ HashMap ‘ with a frequency of 1. Finally, the code prints the number of occurrences of the target value ‘ v ‘ by retrieving the frequency from the ‘ HashMap ‘ using ‘ map.get(v) ‘.

Time Complexity:

The time complexity is O(N) because we are iterating through each element from the given array.

Space Complexity:

Space complexity is how much memory we need. We use a HashMap to remember numbers and their counts. If there are 10 different numbers, we use memory for 10 things; if there are 100, we use memory for 100 things. So, space complexity is O(N), where N is the number of unique elements in the array.

Wrapping Up:

In this blog post, we’ve explored a simple and effective way to find the number of occurrences of a specific value in an array using Java. The use of a HashMap allows us to efficiently track the frequency of each element, providing a clear and concise solution to the problem. Happy Coding!

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