Welcome to Python data types! Python provides several built-in data types to handle different kinds of information. We have numeric types for numbers, sequence types for ordered collections, set types for unique elements, mapping types for key-value pairs, boolean types for true-false values, and the None type for representing absence of value. Let's explore each category in detail.
Let's start with numeric types. Python has three main numeric types. The int type stores whole numbers like 42, negative 17, or zero. The float type stores decimal numbers like 3.14, negative 2.5, or zero point zero. The complex type stores numbers with both real and imaginary parts, like 3 plus 4j or 1 minus 2j. These types handle all mathematical operations you need.
Next are sequence types, which store ordered collections of items. Strings store text and are immutable, meaning you cannot change them after creation. Examples include hello and Python. Lists store ordered items and are mutable, so you can modify them. Examples are lists like 1, 2, 3 or a, b. Tuples also store ordered items but are immutable like strings. Examples include tuples like 1, 2 or x, y.
Finally, let's cover the remaining important types. Sets store unique items and are mutable, like the set containing 1, 2, 3. Dictionaries store key-value pairs for mapping relationships. Booleans represent truth values, either True or False, useful for conditions and logic. The NoneType has only one value, None, which represents the absence of a value or null state. These types complete Python's core data type system.
To wrap up, Python's data types are fundamental building blocks for programming. Choose the right type for your data: integers for whole numbers, floats for decimals, strings for text, lists for changeable collections, and dictionaries for key-value relationships. Remember that some types are mutable while others are immutable. Use the type function to check what type your data is, and convert between types when necessary. Understanding these data types will make you a more effective Python programmer.