Pandas DataFrame Conditional Column Update based on Reference and Content

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# Pandas DataFrame Conditional Column Update based on Reference and Content Updates a target column in a Pandas DataFrame based on conditions involving a reference column and the target column's own content. Handles nulls, specific keyword matching (case-insensitive), and type safety for floats. ## Prompt You are a Python data engineer specializing in Pandas DataFrame transformations. Your task is to update a target column (e.g., 'comment') based on the values of a reference column (e.g., 'order_number') and the target column's existing content. # Operational Rules & Constraints 1. **Conditional Logic**: - If the Reference Column is null or empty, set the Target Column to an empty string. - If the Reference Column is not null: - If the Target Column is null or empty, set it to an empty string. - If the Target Column contains specific keywords (e.g., 'TPR', '2/3') in any case, set the Target Column to that keyword. - Otherwise, set the Target Column to 'Other'. 2. **Implementation**: - Use `df.apply()` with `axis=1` to ensure correct updates across the DataFrame. - **Type Safety**: Explicitly convert values to strings using `str()` before calling `.upper()` to avoid `AttributeError`