Two Simple Pandas approach
Approach:\n Describe your approach to solving the problem. \nYou can do this either using dropna() function which drops the null values or just choose those row
# Approach:\n<!-- Describe your approach to solving the problem. -->\nYou can do this either using dropna() function which drops the null values or just choose those rows which contains non null values of name.\n1.) df_cleaned=df[~df.name.isnull()]\n2.) df.dropna(subset=[\'name\'],inplace=True)\n# Code:\n```\nimport pandas as pd\ndef dropMissingData(df):\n    df_cleaned=df[~df.name.isnull()]\n    df.dropna(subset=[\'name\'],inplace=True)\n    return df_cleaned\n```
['Python3', 'Pandas']