Update assignment_2.ipynb

[kfuentes0524]

Update

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

Implementing a function detect_problems that identifies if any patients in the dataset have a mean inflammation score of zero, signaling a potential data anomaly.

What did you learn from the changes you have made?

I learned how to integrate different functions effectively to detect data anomalies. By using NumPy to compute summary statistics

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

Another approach I considered was manually iterating over the data without relying on the patient_summary function

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

Initially, I encountered an issue when dealing with file paths and reading CSV data. Understanding the structure of NumPy arrays and their interaction with CSV files also took some time.

How were these changes tested?

I tested the changes by running the detect_problems function with different CSV files from the dataset (all_paths). I also validated that the function correctly returns True when a zero mean value is found and False otherwise.

A reference to a related issue in your repository (if applicable)

Checklist

• I can confirm that my changes are working as intended

[SidraBushra]

Assignment marked.