In this chapter, we will break down the different Python Data Types one by one and understand how each type works with simple, practical examples. A clear understanding of Data Types in Python is essential because they determine the kind of data a variable can store and the operations Python can perform on it.
Data Types in Python
- A data type determines how Python stores and processes a particular kind of data.
- Data types help us understand:
- The type of values that can be stored.
- The memory allocated for storing data.
- The range of values supported by the data type.
- Python provides the following built-in core data types:
- Numbers – used for numeric values.
- String – used for text data.
- List – used to store a collection of items.
- Tuple – used to store an ordered collection of items.
- Dictionary – used to store data in key–value pairs.
Numbers in Python
- Numbers are used to store numeric values in Python.
- Python supports three main number data types:
- Integers
- Floating-Point Numbers
- Complex Numbers
Integers
- Integers are whole numbers without any fractional or decimal part, such as 5, 39, 1917, and 0.
- Integers can be positive or negative, for example +12, -15, 3000. If no sign is written, the number is considered positive.
- Python has two types of integers:
- Signed Integers – Normal whole numbers that can be positive or negative.
- Booleans – Represent the truth values True and False
- Boolean values True and False are a subtype of integers.
- In Python, False behaves like 0 and True behaves like 1.
- False and True (with capital first letters) are the only Boolean objects in Python. The forms false and true are not valid Boolean values.
Floating-Point Numbers
- A floating-point number (float) is a number that contains a decimal or fractional part, such as 3.14159 or 12.0.
- Floating-point numbers can be written in two forms:
- Fractional Form: 3500.75, 0.00005, 147.9101
- Exponent Notation: 3.50075E03, 0.5E-04, 1.479101E02
- Floating-point variables represent real numbers and are commonly used for measurable quantities such as distance, area, and temperature.
- The range of floating-point numbers depends on the underlying machine architecture and available memory.
Complex Numbers in Python
- Python provides a Complex Number data type to represent numbers having both real and imaginary parts.
- A complex number is of the form A + Bi, where A is the real part, B is the imaginary part, and i² = -1.
- In Python, the imaginary unit is represented by j instead of i.
- Examples of complex numbers:
- 0 + 3.1j
- 1.5 + 2j
- Python internally stores complex numbers as a pair of floating-point numbers (real part and imaginary part).
Strings in Python
- A string is a sequence of characters enclosed within quotation marks.
- A string can contain letters, digits, spaces, and special characters.
- Python does not have a separate character data type. A single character is also treated as a string.
- Strings are stored as a sequence of individual characters, and each character can be accessed using its index.
- Example: “LearAIhindi”
- Python provides two-way indexing for strings:
- Forward indexing: 0, 1, 2, …
- Backward indexing: -1, -2, -3, …
Lists in Python
- Lists are a compound data type used to store multiple values in a single variable.
- A list contains comma-separated values enclosed within square brackets [ ].
- List elements can be of the same or different data types.
- Examples of lists:
[1, 2, 3, 4, 5]
[‘a’, ‘e’, ‘i’, ‘o’, ‘u’]
[‘Neha’, 102, 79.5]
- Lists are mutable, which means their elements can be changed after creation.
- Each element in a list has an index number, starting from 0.
Tuples in Python
- Tuples are collections of comma-separated values enclosed within parentheses ( ).
- A tuple can store elements of different data types.
- Examples:
(1, 2, 3, 4, 5)
(‘a’, ‘e’, ‘i’, ‘o’, ‘u’)
(7, 8, 9, ‘A’, ‘B’, ‘C’)
- Tuples are immutable, which means their elements cannot be changed, added, or deleted after creation.
- Tuples are similar to lists, but unlike lists, they are non-modifiable.
Sets in Python
- Sets are collections of values enclosed within curly brackets { }.
- Set elements are unordered and unindexed.
- Sets do not allow duplicate values. Duplicate entries are automatically removed.
- A set itself is mutable, meaning items can be added or removed from it.
- Example:
myset = {1, 2, 3, 4}
Dictionary in Python
- A dictionary is an unordered collection of key : value pairs enclosed within curly brackets { }.
- Each key in a dictionary must be unique; no two keys can be the same.
- Dictionaries store data in the form: key : value
- Example:
{‘a’: 1, ‘e’: 2, ‘i’: 3, ‘o’: 4, ‘u’: 5}
| Type | Data Type | Use / Description | Example |
| Number | Integer (int) | Stores whole numbers without a decimal point. | age = 15 |
| Float (float) | Stores numbers with a decimal point. | marks = 89.5 | |
| Missing value | None | Represents the absence of a value. | result = None |
| Sequence | String (str) | Stores text or a sequence of characters enclosed in quotes. | name = “Sanjay” |
| List (list) | Stores an ordered collection of multiple values. Lists are mutable (can be changed). | subjects = [“Python”, “AI”, “Math”] | |
| Tuple (tuple) | Stores an ordered collection of values that cannot be changed. | student = (101, “Sanjay”, 15) | |
| Mapping | Set (set) | Stores an unordered collection of unique values. Duplicate values are automatically removed. | numbers = {1, 2, 2, 3, 3} |
| Dictionary (dict) | Stores data as key-value pairs for quick retrieval. | student = {“name”:”Sanjay”, “age”:15} |
