FIFA Players Statistics – Exploratory Data Analysis (EDA) & Data Wrangling

Data Analyst specializing in Python-based data cleaning, transformation, and exploratory data analysis (EDA). Experienced in handling raw datasets, resolving missing and inconsistent values, engineering meaningful features, and building insightful visualizations using Pandas, NumPy, Matplotlib, Seaborn, and Plotly.

Developed a comprehensive FIFA player data analysis project, transforming complex player statistics into structured, analysis-ready datasets and actionable insights. Skilled in correlation analysis, performance comparisons, outlier detection, and visual storytelling to support data-driven decision-making.

I help clients turn messy data into clear insights, clean datasets, and professional reports ready for machine learning models or business dashboards.