I need a reliable partner to take a raw, mixed-format dataset and turn it into something clean, structured, and immediately usable. The source files could end up being text, numerical tables, or even images—I’m still finalising input formats—so I’m open to whichever workflow you recommend. The tech stack is flexible: whether you prefer Python with Pandas/NumPy, R and tidyverse tools, or a well-structured MATLAB script, propose the environment you’re most productive in and explain why it suits the task. Deliverables • A fully reproducible script or notebook with clear, in-line comments • The processed dataset in an agreed format (CSV, Parquet, or similar) • A concise README covering setup, execution, and a summary of each processing step Acceptance criteria • All steps run end-to-end on a fresh machine after installing listed dependencies • Output dataset passes basic sanity checks (no missing values in required fields, consistent data types) • Code follows clear naming conventions and logical structure When you reply, let me know the data types you’re happiest handling, a brief outline of your approach, and how soon you could deliver a first draft.