Closed
Conversation
Revert "Assignment-1 completed"
anjali-deshpande-hub
suggested changes
May 13, 2025
anjali-deshpande-hub
left a comment
There was a problem hiding this comment.
Question 2:
In the implementation of patient_summary, you have used for loop with np.append(). Its better to use Numpy's vectorized functions mean, max, min because they are faster and more memory efficient since I believe that the append function creates a new array every time its called. You could directly do:
if operation == 'mean':
summary_values = data.mean(axis=ax)
It will be more readable, maintainable and efficient.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
I added a patient_summary() function to calculate mean, max, or min values for each patient, and a detect_problems() function to check for zero averages.
What did you learn from the changes you have made?
I learned how to load data with NumPy, process it row by row, and use functions
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
--
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
Yes, figuring out how to apply operations row-wise. I solved it by looping through each patient (row).
How were these changes tested?
I opened the file in another Jupyter notebook and run them all...
A reference to a related issue in your repository (if applicable)
--
Checklist