Data Types in Python

Understanding data types in Python is crucial for programming. They help manage different kinds of information, from numbers to text. Mastering these types enhances problem-solving skills and lays the foundation for more complex coding concepts in AP Computer Science Principles.

1. Integer (int)

   • Represents whole numbers, both positive and negative, without any decimal points.
   • Supports basic arithmetic operations like addition, subtraction, multiplication, and division.
   • Can be used in loops and conditional statements for counting and indexing.

2. Float

   • Represents real numbers that include decimal points, allowing for fractional values.
   • Useful for calculations requiring precision, such as scientific computations or financial applications.
   • Supports arithmetic operations similar to integers, but may introduce rounding errors due to precision limits.

3. String (str)

   • Represents a sequence of characters, used for storing and manipulating text.
   • Strings can be concatenated, sliced, and formatted, making them versatile for various applications.
   • Enclosed in single or double quotes, and can include escape characters for special formatting.

4. Boolean (bool)

   • Represents one of two values: True or False, used for logical operations and conditions.
   • Essential for control flow in programs, allowing for decision-making through conditional statements.
   • Can be derived from comparisons and logical operations, such as AND, OR, and NOT.

5. List

   • An ordered collection of items that can be of different data types, including other lists.
   • Supports dynamic resizing, allowing items to be added or removed easily.
   • Provides various methods for manipulation, such as sorting, reversing, and slicing.

6. Tuple

   • Similar to lists, but immutable, meaning their contents cannot be changed after creation.
   • Useful for storing fixed collections of items, ensuring data integrity.
   • Can be used as keys in dictionaries due to their immutability.

7. Dictionary (dict)

   • A collection of key-value pairs, allowing for efficient data retrieval based on unique keys.
   • Keys must be immutable types (like strings or tuples), while values can be of any data type.
   • Supports operations like adding, updating, and deleting key-value pairs, making it flexible for data management.

8. Set

   • An unordered collection of unique items, automatically removing duplicates.
   • Supports mathematical set operations like union, intersection, and difference.
   • Useful for membership testing and eliminating duplicate entries in data.