Data Preprocessing & Cleaning Project

In this project, I worked on preparing a raw dataset for analysis by applying a complete data preprocessing workflow using Python, Pandas, and NumPy.

I started by exploring the dataset and identifying missing values, duplicate records, inconsistent data, and incorrect data types. Then, I cleaned and transformed the data by handling missing values, removing duplicates, correcting data types, and standardizing the dataset structure.

I also performed basic data analysis to identify unusual values and ensure the data was consistent and ready for further processing. Finally, I exported the cleaned dataset in a structured format that can be used for Data Analysis, Visualization, or Machine Learning.

Tools: Python, Pandas, NumPy, Jupyter Notebook

Skills: Data Cleaning, Data Preprocessing, Data Transformation, Exploratory Data Analysis (EDA)