Data Cleaning & Preprocessing Service — Up to 50,000 Records

I will clean and preprocess your dataset of up to 50,000 records using Python — handling missing values, removing duplicates, correcting data type inconsistencies, standardising formats, resolving encoding issues, and delivering a clean, structured dataset ready for analysis, reporting, or AI model training. Raw data is almost never usable directly; the data cleaning phase consistently accounts for 60–80% of the effort in any data or AI project, and skipping it properly produces unreliable outputs regardless of how sophisticated the analysis or model built on top of it.

The cleaning process covers missing value treatment (imputation, flagging, or removal based on your instructions and data context), duplicate detection and resolution, format standardisation (dates, phone numbers, postcodes, currency fields), categorical value harmonisation, outlier flagging, and a before/after data quality comparison report. The cleaned dataset is delivered in your preferred format (CSV, Excel, or JSON) alongside the Python cleaning script so the process is fully reproducible as new data arrives.

Suitable for any business, analyst, or developer working with messy CRM exports, web-scraped data, survey responses, transactional records, or legacy system data that needs cleaning before it can be used reliably