# Primitive Data Types ## Understanding Data Types - A data type is a classification that groups data according to what kind of information it represents - Computers need different data types to handle different types of information in programs - Choosing the correct data type ensures accuracy and efficiency in your code

A data type defines the kind of value a variable can hold and the operations that can be performed on it

## The Five Basic Data Types ### Integer - Used to represent whole numbers (no decimal places) - Can be positive or negative - Examples: `42`, `-17`, `0`, `2024` ### Real - Used to represent numbers with fractional parts - Also called floating-point numbers - Can be positive or negative - Examples: `9.81`, `-0.5`, `3.14159`, `100.0` ### Char - Used to represent a single character - Can be a letter, digit, or symbol - Examples: `'z'`, `'X'`, `'7'`, `'?'`

Characters are typically enclosed in single quotes to distinguish them from strings

### String - Used to represent a sequence of characters (text) - Can contain letters, numbers, symbols, or spaces - Examples: `"Python"`, `"User123"`, `"!@#$"`, `"The year is 2024"` ### Boolean - Used to represent logical values - Only two possible values: `True` or `False` - Essential for decision-making in programs - Examples: `True`, `False` ## Why Data Types Matter - **Memory efficiency**: Different types use different amounts of storage - **Accuracy**: Using the wrong type can lead to errors (e.g., storing ages as strings prevents mathematical operations) - **Performance**: Operations are optimized for specific types - **Validation**: Data types help catch errors early ## Type Casting - Casting is the process of converting data from one type to another - Essential when user input needs to be processed numerically

Casting converts a value from one data type to another, such as converting a string to an integer

### Why Cast? - User input is typically received as strings - Mathematical operations require numeric types - Some languages cannot compare text data numerically - Example: The string `"25"` must be cast to integer `25` before checking if it's less than `30` ### Python Casting Examples ```python # String to integer age = int("18") # converts "18" to 18 # String to float pi_value = float("3.14159") # converts "3.14159" to 3.14159 # Integer to string score = str(95) # converts 95 to "95" ``` ### Java Casting Examples ```java // String to integer int quantity = Integer.parseInt("50"); // converts "50" to 50 // String to double double price = Double.parseDouble("19.99"); // converts "19.99" to 19.99 // Integer to string String result = String.valueOf(100); // converts 100 to "100" ``` ## Common Casting Operations | Conversion | Example Code | Input | Output | |------------|--------------|-------|--------| | Integer to Real | `price = float(10)` | `10` | `10.0` | | Real to Integer | `whole = int(7.8)` | `7.8` | `7` | | String to Integer | `num = int("42")` | `"42"` | `42` | | Integer to String | `text = str(99)` | `99` | `"99"` | | Boolean to String | `msg = str(True)` | `True` | `"True"` | | String to Boolean | `flag = bool("Yes")` | `"Yes"` | `True` |

Converting from Real to Integer truncates the decimal part; 7.8 becomes 7, not 8

## Practical Example: Online Store System Consider a system that manages product information for an online store: | Product Information | Recommended Data Type | Reason | |---------------------|----------------------|---------| | Product name | String | Names are text sequences | | Quantity in stock | Integer | Cannot have partial items | | Price | Real/Float | Prices have decimal parts | | On sale status | Boolean | Either on sale or not | | Average rating | Real/Float | Ratings use decimal values (e.g., 4.5 stars) | ### Why These Choices? - **Product name**: `"Wireless Mouse"` needs to store multiple characters → String - **Quantity in stock**: `42` items must be a whole number → Integer - **Price**: `£24.99` requires decimal precision → Real - **On sale status**: `True` or `False` are the only options → Boolean - **Average rating**: `4.7` stars needs decimal precision → Real

Always consider what operations you'll perform on data when choosing types

## Casting in Real-World Applications ### Scenario: Age Verification System ```python # User enters age as text user_input = input("Enter your age: ") # Returns "21" as string # Cast to integer for comparison age = int(user_input) # Now age = 21 as integer # Perform comparison if age >= 18: print("Access granted") else: print("Access denied") ``` Without casting, the comparison `age >= 18` would fail because you cannot directly compare a string to a number in most programming languages. ### Scenario: Price Calculator ```python # Product prices stored as strings in a file price1 = "15.99" price2 = "23.50" # Cast to float for calculation total = float(price1) + float(price2) # total = 39.49 # Cast back to string for display display_text = "Total: £" + str(total) # "Total: £39.49" ``` ## Key Principles 1. **Match the data type to the data**: Use integers for counts, reals for measurements, strings for text, booleans for yes/no decisions 2. **Cast when necessary**: Convert types when performing operations that require specific data types 3. **Be aware of data loss**: Some conversions lose information (real to integer drops decimals) 4. **Consider storage**: Using appropriate types can save memory in large applications 5. **Think about operations**: Choose types based on what you need to do with the data