Python has several built-in data types, including integers, floats, strings, lists, tuples, dictionaries, and sets. Each type serves a specific purpose, allowing developers to manage data effectively.

Python offers a rich variety of built-in data types that facilitate effective data management and manipulation. Understanding these data types is essential for any Python programmer, as they form the foundation for constructing complex data structures and algorithms. The fundamental data types include integers and floats, which represent whole numbers and decimal numbers, respectively. Strings are another critical data type, used for representing text and sequences of characters. Python provides several methods for manipulating strings, such as slicing and concatenation. Collections are also a significant part of Python's data types. Lists are ordered, mutable collections that can hold elements of varying data types, making them incredibly versatile for managing dynamic datasets. Tuples, in contrast, are ordered but immutable, offering a way to group data without the risk of modification. Dictionaries are key-value pairs that enable efficient data retrieval, and sets are unordered collections that store unique items. In addition to these built-in types, Python supports more advanced data types through its extensive libraries, allowing developers to work with complex data structures like arrays and data frames. By leveraging Python's diverse data types, developers can create efficient and effective programs tailored to their specific needs.