2.3 Mixed data types

Python's numeric data types and operations are crucial for performing calculations. Integers and floats behave differently in operations, with type conversion playing a key role in mixed-type expressions.

String manipulation in Python is versatile. The repetition operator allows for easy string duplication, while concatenation enables combining strings. Understanding these operations is essential for effective string handling in Python programs.

Numeric Data Types and Operations

Integer vs float operations

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Operations involving only integers result in an integer data type (

5 + 3

evaluates to

8

) while integer division (

//

) always returns an integer, discarding any remainder (

7 // 2

evaluates to

3

) Operations involving at least one float result in a float data type (

5 + 3.0

evaluates to

8.0

) and regular division (

/

) always returns a float, even if the result is a whole number (

6 / 2

evaluates to

3.0

) Mixing integers and floats in an expression causes Python to implicitly convert integers to floats before performing the operation (

2 * 3.14

evaluates to

6.28

)

• Python uses type inference to determine the appropriate data type for the result of mixed-type operations

Type conversion for arithmetic

Convert a string to an integer using the

###[int](https://www.fiveableKeyTerm:int)()_0###

function (

int("42")

returns

42

) and raises a

[ValueError](https://www.fiveableKeyTerm:ValueError)

if the string cannot be converted Convert a string to a float using the

[float()](https://www.fiveableKeyTerm:float())

function (

float("3.14")

returns

3.14

) and raises a

ValueError

if the string cannot be converted Convert a numeric type (integer or float) to a string using the

[str](https://www.fiveableKeyTerm:str)()

function (

str(42)

returns

"42"

and

str(3.14)

returns

"3.14"

) Arithmetic operations cannot be performed directly on strings (

"2" + 3

raises a

[TypeError](https://www.fiveableKeyTerm:TypeError)

) so first convert the string to the appropriate numeric type

• Data type conversion (also known as type casting) is essential when working with mixed data types to ensure compatibility

Type Checking and Dynamic Typing

• Use the

  [type()](https://www.fiveableKeyTerm:type())

  function to check the data type of a variable or expression
• Python supports dynamic typing, allowing variables to change types during runtime
• Type compatibility is important when performing operations with mixed data types
• Operator overloading allows Python to define how operators behave with different data types

String Repetition and Concatenation

String repetition with integers

The repetition operator (

*

) repeats a string a specified number of times using the syntax

string * integer

or

integer * string

(

"Hello" * 3

evaluates to

"HelloHelloHello"

and

2 * "World"

evaluates to

"WorldWorld"

) The repetition operator creates a new string containing the original string repeated the specified number of times The integer used with the repetition operator must be non-negative or a

ValueError

is raised The repetition operator can be combined with string concatenation (

+

) to create more complex strings (

"Hello" + " " + "World" * 3

evaluates to

"Hello WorldWorldWorld"

)