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What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
I am currently adding new functionality to my Assignment 2. Specifically, I am implementing additional features to improve the program's performance and enhance its user interaction. This includes optimizing existing code, utilizing libraries such as NumPy for efficient data handling. I am also ensuring that the code is well-structured, with proper documentation and testing in place to ensure smooth execution and maintainability.
What did you learn from the changes you have made?
I learned how to use NumPy to efficiently calculate summary statistics such as mean, median, and standard deviation, which has improved my understanding of data manipulation. Additionally, I learned how to open and process .csv files in Python using libraries like csv and Pandas, which made handling large datasets much easier. These changes deepened my understanding of how to work with real-world data and apply various Python libraries to streamline the workflow. I also gained more confidence in debugging and refining my code to make it more efficient and readable.
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
Yes, I considered using tables and charts to better visualize the data. I was thinking about how to create them using Python, possibly by leveraging libraries like Pandas for tables and Matplotlib or Seaborn for charts. These tools would allow me to generate clear, informative visual representations of the data for easier analysis.
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
I used a for loop in part 2, but after researching and thinking about it, I found another approach that didn't require a for loop. The new method is easier to understand.
How were these changes tested?
I tested the changes by running the code multiple times and identifying any errors that occurred. I then debugged the issues by carefully reviewing the error messages, adjusting the code, and re-running it to ensure that all problems were resolved. I also used sample data to verify that the code produced the expected results, ensuring the changes worked correctly under different conditions.
A reference to a related issue in your repository (if applicable)
I utilized resources such as Google and ChatGPT to research potential solutions and clarify concepts. While there wasn't a specific issue directly related to the repository, these tools helped me understand best practices and alternative approaches, which were applied during the development process.
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