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Python List Data Type

Introduction​

In Python, we have already seen that fundamental data types such as int, float, bool, complex, and str are used to store individual values. However, in real-world programming, it is very rare that we only deal with a single value at a time. Most applications require handling multiple related values together, such as a list of student names, employee IDs, or transaction records.

This is where collection data types come into the picture.

1. Fundamental vs Collection Data Types​

Let us begin by revisiting a simple concept.

a = 10          # int
b = 10.5        # float
c = True        # bool
d = 10 + 20j    # complex
e = "Durga"     # string

Each variable here holds only one value. To store a group of values as a single entity, then fundamental data types are not sufficient. You must use collection data types.

2. Collection Data Types in Python​

Python provides several collection types:

  • List
  • Tuple
  • Set
  • Frozenset
  • Dictionary
  • Range
  • Bytes / Bytearray

Each of these serves a different purpose depending on:

  • Whether order matters
  • Whether duplicates are allowed
  • Whether data is key-value based

3. Introduction to List​

A list is used when:

  • You want to store multiple values
  • Order of elements is important
  • Duplicate values are allowed

A list is a collection of values where order is preserved and duplicates are allowed.

4. List Representation​

A list is represented using square brackets [].

l = [10, "Durga", 20, 10, 30]
  • Total elements = 5
  • Duplicate value 10 appears twice
  • Elements are of different types

5. Order is preserved in List​

The order in which elements are inserted is the same order in which they are stored and displayed.

l = [10, "Durga", 20, 10, 30]
print(l) # [10, 'Durga', 20, 10, 30]

6. Duplicates are Allowed in List​

You can store the same value multiple times.

l = [10, 10, 10]

No restriction exists on duplicate entries.

7. Heterogeneous Data Allowed​

A list can contain different types of data.

l = [10, "Hello", True, 10.5]

This flexibility makes lists extremely powerful.

8. Checking Type of List​

l = [10, "Durga", 20]
print(type(l)) # <class 'list'>

9. Indexing in List​

Since order is preserved, indexing is supported.

l = [10, "Durga", 20, 10, 30]

print(l[0])    # First element 10
print(l[-1])   # Last element 30
  • Index starts from 0
  • Negative index starts from -1 (last element)

10. Slicing in List​

Lists support slicing using the syntax:

list[start:end]

11. Creating an Empty List​

Sometimes we need to start with an empty structure.

l = []

This creates an empty list.

12. Adding Elements (append)​

To add elements dynamically, we use:

l.append(value)

Example​

l = []

l.append(10)
l.append(20)
l.append(30)
l.append(40)

print(l) # [10, 20, 30, 40]

13. Removing Elements​

To remove an element:

l.remove(value)

Example​

l = [10, 20, 30, 40]

l.remove(30)

print(l) # [10, 20, 40]

14. Growable Nature of List​

One of the most important features of lists is: Lists are growable in nature.

This means:

  • You can add elements
  • You can remove elements
  • Size is not fixed

This makes lists very flexible compared to arrays in other languages.

15. Mutability of List​

Lists are Mutable. Mutable means that we can modify the existing object without creating a new one.

l = [10, 20, 30, 40]

l[0] = 7777

print(l) # [7777, 20, 30, 40]