Mastering Python Data Types: A Practical Guide

Python Data Types

This guide walks you through the core data types in Python, illustrating how they work and how to convert between them.

Data Types in Python

Every value in Python is an object, and each object is an instance of a class that defines its type. Understanding these types is essential for writing clear, efficient, and reliable code.

Below we cover the most frequently used data types: numbers, lists, tuples, strings, sets, and dictionaries.

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Python Numbers

Python’s numeric types include int, float, and complex. Use type() to inspect a value’s class and isinstance() to test membership in a class hierarchy.

a = 5
print(a, "is of type", type(a))

a = 2.0
print(a, "is of type", type(a))

a = 1+2j
print(a, "is complex number?", isinstance(1+2j, complex))

Output

5 is of type <class 'int'>
2.0 is of type <class 'float'>
(1+2j) is complex number? True

Integers can be arbitrarily large, limited only by available memory. Floating‑point numbers are accurate to about 15 decimal places; for example, 1 is an integer while 1.0 is a float.

Complex numbers follow the form x + yj, where x is the real part and y the imaginary part. Sample values:

>>> a = 1234567890123456789
>>> a
1234567890123456789
>>> b = 0.1234567890123456789
>>> b
0.12345678901234568
>>> c = 1+2j
>>> c
(1+2j)

The float b was truncated to fit the precision limits.

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Python List

Lists are ordered, mutable sequences that can contain elements of any type. Declared with square brackets, items are separated by commas:

a = [1, 2.2, 'python']

Use slicing to retrieve sub‑lists. Indices start at zero:

a = [5,10,15,20,25,30,35,40]

print("a[2] = ", a[2])
print("a[0:3] = ", a[0:3])
print("a[5:] = ", a[5:])

Output

a[2] =  15
a[0:3] =  [5, 10, 15]
a[5:] =  [30, 35, 40]

Lists are mutable; elements can be reassigned:

a = [1, 2, 3]
a[2] = 4
print(a)

Output

[1, 2, 4]

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Python Tuple

Tuples are ordered but immutable. They are often used to protect data and can offer slight performance advantages over lists because their size cannot change. Defined with parentheses:

t = (5,'program', 1+3j)

Slicing works, but reassignment raises an error:

t = (5,'program', 1+3j)

print("t[1] = ", t[1])
print("t[0:3] = ", t[0:3])
# t[0] = 10  # would raise TypeError

Output

t[1] =  program
t[0:3] =  (5, 'program', (1+3j))

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Python Strings

Strings are immutable sequences of Unicode characters. Use single or double quotes; triple quotes allow multiline literals.

s = "This is a string"
print(s)

s = '''A multiline
string'''
print(s)

Output

This is a string
A multiline
string

Slicing works, but attempting to modify a character triggers an error:

s = 'Hello world!'
print("s[4] = ", s[4])
print("s[6:11] = ", s[6:11])
# s[5] = 'd'  # would raise TypeError

Output

s[4] =  o
s[6:11] =  world

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Python Set

A set is an unordered collection of unique items, defined with braces. Sets automatically eliminate duplicates and support set operations like union and intersection.

a = {5,2,3,1,4}
print("a = ", a)
print(type(a))

Output

a =  {1, 2, 3, 4, 5}
<class 'set'>

Duplicates are removed automatically:

a = {1,2,2,3,3,3}
print(a)

Output

{1, 2, 3}

Because sets are unordered, indexing and slicing are not supported.

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Python Dictionary

Dictionaries store key‑value pairs and are highly optimized for lookup by key. Keys and values can be of any hashable type.

d = {1:'value','key':2}
print(type(d))
print("d[1] = ", d[1])
print("d['key'] = ", d['key'])
# print("d[2] = ", d[2])  # would raise KeyError

Output

<class 'dict'>
d[1] =  value
d['key'] =  2

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Conversion Between Data Types

Python provides built‑in constructors for type conversion: int(), float(), str(), and more. Converting a float to an int truncates toward zero.

float(5)  # 5.0
int(10.6)  # 10
int(-10.6)  # -10

String conversions require compatible representations:

float('2.5')  # 2.5
str(25)  # '25'
# int('1p')  # ValueError

Sequences can be converted to one another:

set([1,2,3])  # {1, 2, 3}
tuple({5,6,7})  # (5, 6, 7)
list('hello')  # ['h', 'e', 'l', 'l', 'o']

To create a dictionary from an iterable of pairs:

dict([[1,2],[3,4]])  # {1: 2, 3: 4}
dict([(3,26),(4,44)])  # {3: 26, 4: 44}