Data cleaning and prepossessing

I provide professional Data Cleaning and Data Preprocessing services to transform raw, messy datasets into clean, structured, and analysis-ready data. My work includes: • Handling missing values (removal or imputation) • Removing duplicate records • Fixing inconsistent or incorrect data formats • Detecting and treating outliers • Converting categorical data into numerical format (encoding) • Feature scaling and normalization • Data transformation and formatting • Preparing datasets for Machine Learning models or Data Analysis Tools I use: Python, Pandas, NumPy, Jupyter Notebook, and SQL. The final result will be a clean, well-structured dataset ready for analysis, visualization, or machine learning modeling. I focus on accuracy, efficiency, and clear documentation so the data becomes reliable and easy to work with.