A Data Analyst Recently Joined HackerRank as an Intern: A Python Solution

A data analyst recently joined HackerRank as an intern.
As an initial task, data for n days is provided to the intern. Then, updates are performed on the data, where each update is of the form [I, r]. This indicates that the subarray of data starting at index /and ending at index r is negated. For example, if data = [1, 2, 3, 4] and the updates are [2, 4] then the data
becomes data = [1, -2, -3, -4].
Given the initial data arld k updates, find the final
data after all updates.
Note: 1-based indexing is used.
Example
Consider n = 4, data = [1, -4, -5, 2], k = 2 and
updates = [[2, 4], [1, 2]].
1. After the first update, the data becomes data = [1,
4, 5, -2].
2. After the second update, the data becomes data =
[-1, -4, 5, -2].
The final data is [-1, -4, 5, -2].

The challenge in hand consisted of an array or list of integers, data, representing the data for n days, and a list of k updates. Each update was a list of two integers [I, r], representing the start and end indices (1-based index) of a subarray within data. The task was to negate all numbers within this subarray.

For instance, if the initial data was [1, 2, 3, 4], and an update arrived as [2, 4], the resulting data would be transformed to [1, -2, -3, -4]. It's important to note that the start and end indices included both ends.

Now, let's look at how to solve this task using Python.

Python Solution for the Data Analyst's Task

Here's a simple Python function, named getFinalData, which takes the initial data and the updates as input, and returns the final data after applying all updates:

def getFinalData(data, updates):
    for update in updates:
        start, end = update
        # Correcting for 1-based indexing.
        start -= 1
        # Negate each element in the subarray defined by start and end.
        for i in range(start, end):
            data[i] *= -1
    return data

To test this function, you can use the following code:

data = [1, -4, -5, 2]
updates = [[2, 4], [1, 2]]
print(getFinalData(data, updates))  # Output: [-1, -4, 5, -2]

The function works by looping over each update in the updates list. For every update, it negates each element in the subarray defined by the start and end indices. The 'data' array is updated in place, which is quite efficient as it doesn't require additional space.

Keep in mind, this function assumes that the input data and updates are valid. That is, the update indices are within the bounds of the data array and are in ascending order. If this is not guaranteed, consider adding error checking mechanisms to this function for robustness.

We hope this solution helps you better understand Python's utility in data manipulation and analytics tasks. Whether you are a data analyst intern at HackerRank or any other organization, Python's power and flexibility can undoubtedly make your work more efficient. Happy coding!