List column to rows

Pandas data engineering interview problem. Difficulty: beginner. Pattern: Filtering. About 10 minutes. Free to practice.

Turn a comma-separated string column into one trimmed row per value. Treat this as a production helper: match the contracted return shape, including empty and duplicate inputs.

Many tables store several values in one text column, separated by commas, for example a, b ,c. To work with them, you want 1 row for each value. The text can be messy: spaces around the values, empty pieces like x,,y, or a missing value. df has id and tags. Return 1 row for each id and tag, with the spaces around each tag removed. Do not return empty or missing tags. Return id and tag, keep the original order of the ids and of the tags inside each id, and reset the index. The editor builds df and ends with result = df. Change the last line. Split the text, explode the lists, strip the spaces and filter.

Requirements

• Split tags on commas and use explode to get 1 row for each piece.
• Remove the spaces around each tag with str.strip().
• Drop tags that are missing or empty.
• Return id and tag with a clean index in result.

Constraints

• Keep the order of ids and the order of tags inside each id. Do not sort.
• A missing tags value gives a missing tag after explode, which must be removed.
• Strip before you test for empty, because a tag with only spaces becomes empty after stripping.

Examples

Input: df id | tags 1 | a, b ,c 2 | 3 | NULL 4 | red ,blue 5 | x,,y Output: id | tag 1 | a 1 | b 1 | c 4 | red 4 | blue 5 | x 5 | y Ticket 1 gives a, b and c. Row 2 (spaces only) and row 3 (missing) give nothing; 4 gives red and blue; 5 gives x and y.

Topics: lakebench, pandas, str.split, explode, strip.

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