Support tickets, order notes and shipping labels carry structured facts buried in free text, and the regex that grabs them wrong tends to grab something that merely looks right.
Write extract_skus(df). Given a DataFrame with a note column of free text, add a sku column holding the first SKU code mentioned in that note, normalised to uppercase "SKU-####" form (exactly four digits).
"sku-1234" and "Sku-1234" both extract as "SKU-1234".sku = NaN.SKU-#### must be its own token. A note containing "MYSKU-1234" does not count — "SKU" has to start a word, not sit in the middle of one. A run of more or fewer than four digits ("SKU-12345", "SKU-12") does not match either.Return all original columns plus sku; do not drop or reorder rows.
Build the architecture on a canvas: place the components, configure them, connect them into a data flow, and write a short reason for each one. The AI reviewer grades your design against a rubric written specifically for this problem.
Minimum 5 components · needs a wide desktop screen