Easy solutions || MySQL || Pandas || Beats 100% !!
\n# Code\n\n# Write your MySQL query statement below\nSELECT salesperson.name\nFROM orders o JOIN company c ON (o.com_id = c.com_id AND c.name = \'RED\')\nRIGHT
\n# Code\n```\n# Write your MySQL query statement below\nSELECT salesperson.name\nFROM orders o JOIN company c ON (o.com_id = c.com_id AND c.name = \'RED\')\nRIGHT JOIN salesperson ON salesperson.sales_id = o.sales_id\nWHERE o.sales_id IS NULL\n```\n```\nimport pandas as pd\n\ndef sales_person(sales_person: pd.DataFrame, company: pd.DataFrame, orders: pd.DataFrame) -> pd.DataFrame:\n    # Merge DataFrames to find salespersons with orders related to "RED" companies\n    merged_df = pd.merge(orders, company, on=\'com_id\', how=\'inner\')\n    red_sales_ids = merged_df[merged_df[\'name\'] == \'RED\'][\'sales_id\'].unique()\n    \n    # Filter salespersons who do not have orders related to "RED" companies\n    result_df = sales_person[~sales_person[\'sales_id\'].isin(red_sales_ids)][[\'name\']]\n    return result_df\n```
['MySQL', 'Pandas']