Pandas Merge and Join Troubleshooter
Fix wrong row counts after merging tables.
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My pandas merge gives the wrong number of rows and I need to find out why. Describe the two tables, their keys, and the symptom: [TABLES_KEYS_AND_SYMPTOM]. The merge code I used: [PASTE_MERGE_CODE]. Row counts before and after: [ROW_COUNTS]. Follow this decision tree and show your reasoning at each node: 1. Is the key unique in each table? If a key repeats in both, the result multiplies rows (m x n per key). Give the code to measure duplicates: df.duplicated(subset=key).sum() and df.groupby(key).size().describe(). 2. Are the key dtypes and formats identical (int versus string, leading zeros, case, whitespace)? Give the check. 3. Is the merge type right (inner, left, outer)? State what row count each should give with my numbers. 4. Are there null keys, which pandas matches to each other? Explain. 5. Did suffixes or duplicate column names silently overwrite data? Output format: a diagnosis table (Check | Result expected | Command | What it means if it fails), then the corrected merge using validate="one_to_one" or "one_to_many" and indicator=True, then three tests that prove the row count is now correct. End with a one-paragraph explanation I can paste into a code review.
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