The correct answer is B. Numpy.
NumPy is a Python library that provides fast, efficient numerical computation. It is the foundation of scientific computing with Python. NumPy arrays are the fundamental data structure of NumPy. They are multidimensional arrays that can be used to represent data of any type. NumPy arrays are very efficient for storing and manipulating data. They are also very fast, which makes them ideal for scientific computing.
Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for creating attractive and informative statistical graphics. Seaborn is designed to be easy to use, even for people who are not familiar with Matplotlib.
Pandas is a Python library for data analysis. It provides high-performance, easy-to-use data structures and data analysis tools for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data. Pandas is built on top of NumPy, and its core data structure is the DataFrame. A DataFrame is a two-dimensional labeled tabular data structure with columns of potentially different types.
SciPy is a Python library that provides various scientific and numerical computing tools. It includes modules for linear algebra, numerical integration, optimization, signal processing, and more. SciPy is a popular choice for scientific computing in Python.
In conclusion, NumPy is the Python library that provides tools for working with large and multidimensional arrays and matrices and is often used in scientific computing.