Which of the following is a common library used for data manipulation in Python?

Pandas is widely recognized as a powerful library specifically designed for data manipulation and analysis in Python. It provides data structures like DataFrames and Series that facilitate handling structured data easily. With its capabilities, users can perform complex operations such as filtering, grouping, and aggregating data efficiently. This makes Pandas particularly suitable for tasks that involve preparing and cleaning data before analysis.

While other libraries listed, such as Numpy and Scikit-learn, are essential in the Python ecosystem, they serve different primary purposes. Numpy is focused on numerical operations and working with arrays, which underpins many scientific computing activities. Scikit-learn is a library for machine learning that relies on data preprocessed typically with Pandas but does not directly provide data manipulation tools.

Matplotlib, on the other hand, is primarily a visualization library, used for creating static, animated, and interactive visualizations in Python. Though it is often used alongside Pandas for plotting data, it does not function as a manipulation library itself.

Therefore, among the choices, Pandas stands out as the most suitable option for data manipulation.