22  Summary - Python Data Types

22.1 Inbuilt Data Types

In programming, data type is an important concept. Variables can store data of different types, and different types can do different things.

Python has the following data types built-in without needing any other libraries:

Simple/primitive data types:

• None Type: NoneType

• Boolean Type: bool

• Text Type: str

• Numeric Types: int, float, complex

• Binary Types: bytes

Composite Datatypes / data structures

• Sequence Types: list, tuple, range

• Set Types: set, frozenset

• Mapping Type: dict

• Binary composite type: bytearray, memoryview

We will also look at the numpy arrays and pandas dataframes, you can also use the decimal module for correctly rounded arithmetic

In Python, each data type has specific use cases and trade-offs. Let’s look at each category and examine when it might be used, along with its benefits and disadvantages:

Category	Type	Common Use Case	Benefits	Disadvantages	Syntax
None Type	NoneType	Represents absence of value	Useful for optional values and placeholders	Can cause errors if operations expect a value	None
Boolean	bool	Represents True or False	Simple and efficient for control flow	Limited to two states (True/False)	True, False
Text	str	Text representation	Immutable, Unicode support, rich manipulation methods	Inefficient for heavy modifications	"Hello", 'World'
Numeric	int	Represents whole numbers	No precision issues	Limited to integers	42, -7
	float	Represents decimal numbers	Supports real numbers	Precision issues due to storage	3.14, -0.5
	complex	Represents complex numbers	Direct support for complex arithmetic	Rarely needed in general programming	2+3j
Sequence	list	Mutable sequence of items	Flexible, dynamic size, rich methods	Slower resizing operations	[1, 2, 3]
	tuple	Immutable sequence of items	Memory-efficient, safe	Cannot change values once set	(1, 2, 3)
	range	Sequence of numbers	Memory-efficient	Less flexible than lists	range(5)
Mapping	dict	Key-value pairs	Fast lookups, flexible types	Higher memory usage due to hashing	{"a": 1, "b": 2}
Set	set	Unordered collection of unique items	Fast membership testing	Unordered in Python; no indexing	{1, 2, 3}
	frozenset	Immutable set	Hashable, can be used as dictionary keys	Cannot modify after creation	frozenset([1, 2, 3])
Binary	bytes	Immutable binary data	Efficient, compact for binary data	Not human-readable, cumbersome for some operations	b"hello"
	bytearray	Mutable binary data	Allows modification of binary data	Consumes more memory than bytes	bytearray([1, 2, 3])
	memoryview	Efficient access to binary data without copying	No data duplication	More complex to use	memoryview(b"data")

Custom Data types

• In python it is possible to define custom data types with custom syntax and behaviours. Many of the common desired data types have already been made for you by others.

22.2 Initialising and converting between data types

Different data types have different syntax. You will notice that all inbuilt data types in python have inbuilt functions which can be used to convert to that data type or specify as that data type.

It is not possible to convert between all data types; some conversions require additional information and input.

Resources about data types can be found in the python documentation: https://docs.python.org/3/library/functions.html https://docs.python.org/3/library/stdtypes.html

22.3 Data type Characteristics

Mutability

• Primitive Data Types: Immutable - new items are created if the value changes

• Lists: Mutable - items can be changed or updated.

• Tuples: Immutable - once defined, items cannot be changed.

• Dictionaries: Mutable - keys and values can be added or updated.

• Sets: Mutable - can add or remove items, but cannot contain duplicates.

Order

• Lists and Tuples: Ordered collections (the order of elements matters).

• Dictionaries: Maintains insertion order as of Python 3.7.

• Sets: Unordered - no guaranteed order of elements

Duplicates

• Lists and Tuples: Allow duplicates.

• Dictionaries: Keys must be unique, but values can be duplicated.

• Sets: Do not allow duplicates.