Which Python library is commonly used for data exploration and data cleaning tasks, providing interactive and user-friendly interfaces?

Pandas is a popular Python library widely used for data exploration and data cleaning tasks.

It provides easy-to-use, flexible, and powerful data structures, especially DataFrames, which allow for efficient data manipulation and analysis.

With Pandas, users can perform operations such as filtering, merging, grouping, and reshaping data quickly and effectively.

It is commonly used in conjunction with other libraries like NumPy and Matplotlib to extend its data handling capabilities and support data visualization.