Programming Assignment: Assignment 2: Modeling and Transforming Text Data for ML Grading problem

Title: C4W2 - All exercises output correct data but grader gives 0/10 on ex04, ex05, ex06

Tags: Coursera-platform, course-4, week-2

Body:

My code runs successfully and produces correct outputs, but the grader scores 0/10 on ex04 (process_metadata), ex05 (clean_text), and ex06 (reviews_product_metadata_df.head()).

The issue seems to be that my code is in the wrong cells. I noticed the grader uses the graded metadata tag to identify which cells to check. In my notebook, the cell tagged graded for ex04 was empty (pass), while my actual working code was in a different cell below it — so the grader was checking an empty cell and returning 0 lines.

Questions:

  1. If code accidentally gets moved to a non-graded cell, is there any way to restore the original cell tags? Or do I need a fresh copy of the notebook?

  2. For the clean_text graded cell (ex05) — should it contain ONLY the function definition, or should it also include the application of clean_text to the DataFrame columns with .head() at the end? The grader expects 69 lines of output but a function definition alone produces no output.

  3. Is the expected column order for process_metadata output: asin, description, title, price, brand, sales_category, sales_rank? And should rows without salesRank be dropped?

Any help appreciated — been stuck on this for hours.

I’m not a mentor for this course. But here are a couple of common issues:
Did you add any cells to the notebook?
Did you move, copy, or delete any cells?

Yes, unfortunately cells were added, moved, and modified before I realized the grader uses cell metadata tags. The graded tags are now on the wrong cells (e.g., the ex04 graded cell has pass while my actual code is in a different cell).

Is there a way to get a fresh copy of the original C4_W2_Assignment.ipynb with the correct cell tags intact? That would be the easiest way to start clean

Yes, there is. Instructions are here:

Thank u so much that’s actually Works very well