I will clean and prepare your dataset for analysis or modeling

Dirty data leads to unreliable analysis. Before any EDA, visualization, model, or business decision, your dataset needs to be trustworthy and that starts with proper cleaning and preparation suited to the data you're working with.

What I'll handle:

• Missing values: detection, imputation or justified removal
• Duplicates and inconsistent records
• Data type corrections and formatting standardization
• Outlier detection and treatment
• Variable renaming and structural reorganization
• Normalization / standardization (Standard or Premium)
• Categorical encoding and feature preparation (Premium)
• Any other technique that I consider necessary given the context of the data and the desired use for the dataset.

I can work in Python or R. You'll receive, in any of the packages, clean, well-documented code so the process is fully reproducible and auditable, and also a written description of every step that was done.

If there are any questions or doubts on why a certain step was done, I can explain it with no inconvenience at all.