Welcome to our data-wrangling project repository!

In this project, we leverage the power of Python's data manipulation libraries - Pandas and NumPy, along with the visualization capabilities of Matplotlib, to clean, transform, and analyze datasets. Our goal is to provide a comprehensive guide to data wrangling techniques, showcasing real-world examples and best practices.

Key Features:

• Data Cleaning: Learn how to handle missing values, outliers, and inconsistencies in your datasets effectively.
• Data Transformation: Explore various methods for reshaping data, merging datasets, and creating new variables.
• Data Analysis: Dive into exploratory data analysis (EDA) techniques to gain insights and visualize trends in your data.
• Jupyter Notebooks: Access interactive Jupyter notebooks containing step-by-step tutorials and code examples.

Whether you're a beginner looking to learn the basics of data wrangling or an experienced data scientist seeking advanced techniques, this repository has something for everyone. Get started today and unlock the full potential of your datasets!