Text Data Cleaning Missing Values

I have a text-based dataset that contains numerous blank or NULL fields. I need those missing values identified and handled so the file is ready for analysis and reporting.

Here’s what I’m after:
• A cleaned version of the dataset with every missing-value issue resolved (imputation, flagging, or removal—please advise on the best approach for this data).
• A concise change log or brief summary explaining what you did, the methods used, and any recommendations for preventing future gaps.

You are free to work in Excel, Google Sheets, Python (pandas), R, or any tool you feel will get the job done efficiently—as long as the final deliverable comes back in its original format plus the cleaned version.

Let me know your preferred approach and estimated turnaround, and I’ll share the file right away so we can get started.