What are NumPy and Pandas, and how are they used for data analysis in Python? Provide examples of their functionalities.

NumPy and Pandas are two powerful libraries in Python that are widely used for data analysis and manipulation. Let's explore what each library is and how they are used in data analysis: 1. NumPy: NumPy, which stands for "Numerical Python," is a fundamental library for scientific computing in Python. It provides efficient data structures, high-performance mathematical functions, and tools for working with arrays and matrices. NumPy is the foundation upon which many other data analysis libraries are built. Key features and functionalities of NumPy include: * Multi-dimensional Arrays: NumPy introduces the `ndarray` data structure, which allows efficient storage and manipulation of arrays of homogeneous data types. It provides a wide range of array operations and mathematical functions optimized for performance. Example: ``` python`import numpy as np # Create a NumPy array data = np.array([1, 2, 3, 4, 5]) # Perform operations on the arr....