Data Cleaning for 100% Accuracy

I have a data-analysis assignment focused solely on cleaning a dataset I refer to as “Point 131.” The current raw file shows a CPM value of 116 but contains inconsistencies, blanks, and probable entry errors that must be resolved so the final table reflects 100 % accuracy. What I need from you is a systematic, well-documented cleaning pass: remove duplicates, correct obvious typos, standardize formats, flag outliers, and leave me with a pristine file plus a brief change log that explains every edit. I am not under time pressure, so you can take the time required to reach the highest quality standard rather than rushing through. You may use whichever tools you are most comfortable with—Python (pandas), R (dplyr), Excel Power Query, or any reliable data-wrangling environment—as long as the end result is a fully validated dataset and a concise report of steps taken. Deliverables • Cleaned dataset in the same original format (CSV or Excel) • Change log / quality-assurance notes summarizing fixes and assumptions I’ll happily answer clarifying questions up front so you can dive straight into the work.

Project ID: 40437686