Data Types -Introduction to Data types-Data Types-Types of Data

1. Primitive Data Types
These are the basic building blocks of data in programming languages. They typically represent single values and are directly supported by the language.

Integer (int):

Description: Represents whole numbers, both positive and negative, without any fractional or decimal part.
Example: 42, -3
Operations: Addition, subtraction, multiplication, division, etc.
Floating Point (float or double):

Description: Represents numbers with fractional parts using a decimal point. float typically offers single precision, while double offers double precision.
Example: 3.14, -0.001, 2.71828
Operations: Arithmetic operations including addition, subtraction, multiplication, division.
Character (char):

Description: Represents a single character, such as a letter, digit, or symbol.
Example: 'a', 'Z', '3'
Operations: Comparison, concatenation with strings.
Boolean (bool):

Description: Represents a value that can be either true or false.
Example: true, false
Operations: Logical operations like AND, OR, NOT.
2. Composite Data Types
These data types are built from primitive types and can hold multiple values or more complex structures.

String (string):

Description: Represents a sequence of characters, used for text data.
Example: "Hello, World!", "123"
Operations: Concatenation, substring extraction, length computation, etc.
Array:

Description: A collection of elements of the same type, stored in contiguous memory locations.
Example: [1, 2, 3, 4], ['a', 'b', 'c']
Operations: Access elements by index, iterate over elements, modify elements.
List:

Description: Similar to arrays but often more flexible. Lists can hold elements of different types and can grow or shrink dynamically.
Example: [1, "text", 3.14]
Operations: Append, remove, sort, access by index.
Tuple:

Description: An ordered, immutable collection of elements, which can be of different types.
Example: (1, "text", 3.14)
Operations: Access elements by index, unpack into variables.
Set:

Description: A collection of unique elements, typically unordered.
Example: {1, 2, 3}, {"apple", "banana"}
Operations: Union, intersection, difference.
Dictionary (or Map):

Description: A collection of key-value pairs, where each key is unique.
Example: {"name": "Alice", "age": 30}
Operations: Access values by key, add or remove key-value pairs.
3. Abstract Data Types (ADTs)
These are more conceptual and define operations on data without specifying how they are implemented.

Stack:

Description: A collection of elements with Last In, First Out (LIFO) access.
Operations: Push (add an element), Pop (remove the top element), Peek (view the top element).
Queue:

Description: A collection of elements with First In, First Out (FIFO) access.
Operations: Enqueue (add an element), Dequeue (remove the front element), Peek (view the front element).
Linked List:

Description: A collection of nodes where each node contains data and a reference to the next node.
Operations: Insert, delete, traverse.

1. Dr U Praveen Assistant Professor Sri Ramakrishna College of Arts & Science Coimbatore Topic: Types of Data

2. Introduction to Data Types Data types are crucial for understanding and representing information in computer programming. They define the kind of data a variable can hold, influencing how it's stored, processed, and manipulated.

3. Numeric Data Types Numeric data types represent numerical values, forming the foundation of calculations and mathematical operations. They can be further categorized into integers and floating-point numbers. Integers Represent whole numbers without decimals, ideal for counting or discrete values. Floating-Point Represent numbers with decimals, suitable for precise measurements or scientific calculations.

4. Integer Data Types Integers are whole numbers without fractions or decimals, used for representing counts, IDs, or positions. They can be positive, negative, or zero. 1 Examples Age, number of items in a shopping cart, student ID. 2 Advantages Efficient storage and faster calculations. 3 Limitations Inability to represent fractions or decimals.

5. Floating-Point Data Types Floating-point numbers represent real numbers with decimals, often used for measurements, scientific calculations, or financial data. Precision Store numbers with a varying number of digits after the decimal point. Applications Suitable for calculations involving fractions or precise measurements. Example Temperature readings, currency values, scientific data analysis.

6. Boolean Data Types Boolean data types represent truth values, typically "true" or "false," used for conditional statements and logic operations. True Represents a positive or affirmative condition. False Represents a negative or non-affirmative condition.

7. Character Data Types Character data types store individual characters like letters, numbers, punctuation marks, and special symbols. They are often used for representing single-character input or output. Character Example Use Case A Letter Text processing 5 Number Password validation * Punctuation Text formatting

8. String Data Types String data types store sequences of characters, used for representing text, labels, or messages. They are essential for handling text-based data. Text Store written content such as paragraphs or articles. Labels Provide descriptions or identifiers for various data elements. Email Addresses Store electronic mail addresses for communication.

9. Date and Time Data Types Date and time data types store specific points in time, commonly used for recording events, scheduling tasks, or managing timestamps. 1 Date Store year, month, and day. 2 Time Store hours, minutes, and seconds. 3 Timestamp Combine date and time for a precise point in time.

10. Compound Data Types Compound data types, also known as composite data types, combine multiple values of various data types into a single structure, allowing for more complex data representation. Arrays Store collections of elements of the same data type in a contiguous memory location. Lists Store ordered collections of elements, potentially of different data types, in a sequence. Dictionaries Store key-value pairs, mapping keys to associated values, allowing for efficient data retrieval.

11. Conclusion and Key Takeaways Understanding data types is essential for effective programming. They provide a structured way to represent and manipulate data, enabling efficient computations and logical operations. 1 Choice Select appropriate data types for each variable, considering the type of data being stored and its intended usage. 2 Operations Perform operations based on the data type, leveraging the capabilities and limitations of each type. 3 Efficiency Use data types that optimize storage and processing, leading to improved performance and resource management.