sparse arrays hackerrank solution optimized approach
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sure! in this tutorial, we will discuss the sparse arrays problem on hackerrank and how to solve it efficiently. the sparse arrays problem essentially involves counting the occurrences of specific strings in a larger list.
problem statement
you are given two arrays:
1. an array of strings (let's call it `strings`).
2. an array of query strings (let's call it `queries`).
the task is to determine how many times each query string appears in the `strings` array.
sample input
sample output
approach
1. **understanding the problem**:
we need to count occurrences of each query string in the `strings` array.
a naive approach would involve iterating through the `strings` array for each query, leading to a time complexity of o(n * m), where n is the size of `strings` and m is the size of `queries`. this is inefficient, especially for large arrays.
2. **optimized approach using hash map**:
instead of re-checking the entire `strings` array for each query, we can use a hash map (or dictionary) to store the counts of each string in the `strings` array.
this allows us to count the occurrences in o(n) time and then retrieve the counts for each query in o(1) time.
steps
1. build a frequency dictionary for the `strings` array.
2. for each query, check the frequency dictionary and collect the results.
implementation
here is a python implementation of the optimized approach:
explanation of the code
1. **frequency dictionary**: we create a dictionary `frequency` to count how many times each string appears in the `strings` array.
2. **counting occurrences**: we iterate through the `strings`, and for each string, we either increment the count if it exists in the dictionary or initialize it to 1 if it’s the first time we see it.
3. **query processing**: for each query in the `queries` array, we use `frequency.get(query, 0)` to get the count. if the query does not exist in the dictionary, it returns 0.
4. **return results**: finally, we return ...
#SparseArrays #HackerRank #python
Sparse arrays
Hackerrank
optimized approach
string comparison
frequency count
data structures
algorithm efficiency
input handling
output generation
time complexity
space complexity
query processing
list manipulation
coding challenge
problem-solving
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