Lists and Loops in Python

Lists in Python

What Are Lists?

• A list is an ordered collection of items.
• Items can be any data type: numbers, strings, or other lists.
• Lists are mutable, meaning you can modify them after creation.

fruits = ["apple", "banana", "cherry"]
print(fruits)

['apple', 'banana', 'cherry']

Why Use Lists in NLP?

• Lists can store words, sentences, or entire texts.
• NLP tasks often require managing large datasets of tokens or documents.

sentence = "Natural language processing is fun"
tokens = sentence.split()  # Tokenize sentence into words
print(tokens)

['Natural', 'language', 'processing', 'is', 'fun']

Accessing List Elements

Indexing

• Access list elements using indexing.
• Python indexing starts at 0.

fruits = ["apple", "banana", "cherry"]
print(fruits[0])  # Outputs: apple
print(fruits[1])  # Outputs: banana

apple
banana

Negative Indexing

• Negative indexing starts from the end of the list.

print(fruits[-1])  # Outputs: cherry (last element)

cherry

• Useful for quickly accessing the last few elements of a list.

Modifying Lists

Changing Elements

• Modify a list by assigning a new value at a specific index.

fruits = ["apple", "banana", "cherry"]
fruits[1] = "blueberry"  # Replacing 'banana'
print(fruits)

['apple', 'blueberry', 'cherry']

Real-World NLP Use

• You might replace tokens or correct errors in a tokenized sentence.

tokens = ["NLP", "is", "coool"]
tokens[2] = "cool"  # Fix typo
print(tokens)

['NLP', 'is', 'cool']

Adding and Removing Elements

Adding Elements

• Use .append() to add items to the end of the list.

fruits = ["apple", "banana"]
fruits.append("cherry")
print(fruits)

['apple', 'banana', 'cherry']

Removing Elements

• Use .remove() to delete specific items.

fruits.remove("banana")
print(fruits)

['apple', 'cherry']

• Lists are flexible, allowing easy manipulation in NLP tasks.

List Operations: Length, Sorting, and Checking

List Length

• Use len() to find the number of elements in a list.

fruits = ["banana", "cherry", "apple"]
print(len(fruits))

3

Sorting and Checking Elements

• Use .sort() to sort the list.
• Use in to check if an item exists in a list.

fruits.sort()
print(fruits)

print("apple" in fruits)
print("grape" in fruits)

['apple', 'banana', 'cherry']
True
False

Loops in Python

What Are Loops?

• Loops help you iterate over a list and perform actions on each element.
• Commonly used in NLP for tasks like text processing.

fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
    print(fruit)

apple
banana
cherry

Real-World NLP Example

• Tokenizing and processing text using loops.

tokens = ["NLP", "is", "fun"]
for token in tokens:
    print(token)

NLP
is
fun

Using Loops for Simple Operations

Squaring Numbers in a List

• Loops allow you to apply operations to list elements.

numbers = [1, 2, 3, 4]
squares = []
for number in numbers:
    squares.append(number ** 2)

print(squares)

[1, 4, 9, 16]

NLP Example: Word Length Calculation

• Use loops to calculate the length of each word in a sentence.

tokens = ["NLP", "is", "great"]
for token in tokens:
    print(f"{token}: {len(token)} characters")

NLP: 3 characters
is: 2 characters
great: 5 characters

Looping with range()

Using range()

• Sometimes you need to iterate a set number of times.
• range() generates a sequence of numbers.

for i in range(5):
    print(i)

0
1
2
3
4

Combining range() with Lists

• Use range() to loop over list indices, allowing more control.

fruits = ["apple", "banana", "cherry"]
for i in range(len(fruits)):
    print(f"Index {i}: {fruits[i]}")

Index 0: apple
Index 1: banana
Index 2: cherry

Common List Methods

Adding and Removing Elements

• .append(): Adds an item to the end.
• .remove(): Removes a specific item.

fruits.append("orange")
fruits.remove("banana")
print(fruits)

['apple', 'cherry', 'orange']

Inserting and Popping Elements

• .insert(): Inserts an item at a specific index.
• .pop(): Removes and returns the last item or the item at a specific index.

fruits.insert(1, "blueberry")
print(fruits)

last_fruit = fruits.pop()
print(fruits)

['apple', 'blueberry', 'cherry', 'orange']
['apple', 'blueberry', 'cherry']

Summary: Lists and Loops

• Lists: Allow you to store and manipulate multiple elements, useful in NLP for text processing.
• Loops: Help automate repetitive tasks and process list elements.
• You can easily modify, sort, and check elements within lists.
• Loops and lists combined allow for efficient handling of data in Python, especially in NLP.