What are advanced data types in NumPy?

What are advanced data types in NumPy?

Advanced data types in NumPy include structured arrays, record arrays, and masked arrays, which allow for complex data handling.

Can you explain structured arrays with an example?

Sure! A structured array allows you to define a compound data type with multiple fields. For example, you can create an array of students with fields like name, age, and grade.

How do I create a structured array in code?

You can create a structured array using the numpy.array function with a defined dtype. Here's an example:

import numpy as np

student_dtype = np.dtype([('name', 'U10'), ('age', 'i4'), ('grade', 'f4')])
students = np.array([('Alice', 20, 88.5), ('Bob', 22, 91.0)], dtype=student_dtype)

What are masked arrays and when should I use them?

Masked arrays are used to handle missing or invalid entries in your data. They allow you to perform operations while ignoring these masked values.