In the previous installments of our "Python for Scripting" series, we explored Python's basics, including variables, data types, operators, and conditional statements. Now, it's time to delve deeper into Python's powerful data structures. In Part 3, we'll cover the following topics:
Lists
Tuples
Dictionaries
Sets
Working with sequences and collections
1. Lists
Lists: Creation, Indexing, Slicing, and Methods
A list is a versatile and ordered collection of items. It can contain elements of different data types.
Creation:
fruits = ["apple", "banana", "cherry"]
Indexing and Slicing:
You can access elements in a list using index numbers. Indexing starts at 0.
first_fruit = fruits[0] # "apple"
sliced_fruits = fruits[1:3] # ["banana", "cherry"]
Common List Methods
append(): Add an item to the end of the list.
fruits = ["apple", "banana", "cherry"]
fruits.append("date")
print(fruits)
# Output: ['apple', 'banana', 'cherry', 'date']
insert(): Insert an item at a specific position.
fruits = ["apple", "banana", "cherry"]
fruits.insert(1, "orange")
print(fruits)
# Output: ['apple', 'orange', 'banana', 'cherry']
remove(): Remove a specific item by value.
fruits = ["apple", "banana", "cherry"]
fruits.remove("banana")
print(fruits)
# Output: ['apple', 'cherry']
pop(): Remove an item by index.
fruits = ["apple", "banana", "cherry"]
removed_fruit = fruits.pop(1)
print("Removed fruit:", removed_fruit)
print(fruits)
# Output: Removed fruit: banana
# ['apple', 'cherry']
len(): Get the length of the list.
fruits = ["apple", "banana", "cherry"]
length = len(fruits)
print("Length of the list:", length)
# Output: Length of the list: 3
2. Tuples
Tuples: Creation, Immutability, and Uses
Tuples are similar to lists, but they are immutable, meaning you can't change their contents after creation.
Creation:
coordinates = (3, 4)
Tuples are often used to represent fixed collections of data, such as coordinates, RGB colors, or points in a game.
3. Dictionaries
Dictionaries: Key-Value Pairs and Methods
Dictionaries store data in key-value pairs. They are unordered and very efficient for quick lookups.
Creation:
person = {
"name": "Virat",
"age": 33,
"city": "Delhi"
}
Accessing Values:
name = person["name"] # "Virat"
Common Dictionary Methods
keys(): Get a list of keys.
person = {
"name": "Virat",
"age": 33,
"city": "Delhi"
}
keys = person.keys()
print("Keys:", keys)
# Output: Keys: dict_keys(['name', 'age', 'city'])
values(): Get a list of values.
person = {
"name": "Virat",
"age": 33,
"city": "Delhi"
}
values = person.values()
print("Values:", values)
# Output: Values: dict_values(['Virat', 33, 'Delhi'])
items(): Get a list of key-value pairs.
person = {
"name": "Virat",
"age": 33,
"city": "Delhi"
}
items = person.items()
print("Items:", items)
# Output: Items: dict_items([('name', 'Virat'), ('age', 33), ('city', 'Delhi')])
get(): Safely get the value for a key.
person = {
"name": "Virat",
"age": 33,
"city": "Delhi"
}
age = person.get("age")
country = person.get("country", "India")
print("Age:", age)
print("Country:", country)
# Output: Age: 33
# Country: India
4. Sets
Sets: Creation, Methods, and Common Operations
Sets are unordered collections of unique elements.
Creation:
fruits = {"apple", "banana", "cherry"}
Common Set Operations
add(): Add an element to the set.
colors = {"red", "green", "blue"}
colors.add("yellow")
print(colors)
# Output: {'red', 'green', 'yellow', 'blue'}
remove(): Remove an element from the set.
colors = {"red", "green", "blue"}
colors.remove("green")
print(colors)
# Output: {'red', 'blue'}
union(): Combine two sets.
set1 = {1, 2, 3}
set2 = {3, 4, 5}
union_set = set1.union(set2)
print(union_set)
# Output: {1, 2, 3, 4, 5}
intersection(): Find elements common to two sets.
set1 = {1, 2, 3}
set2 = {3, 4, 5}
intersection_set = set1.intersection(set2)
print(intersection_set)
# Output: {3}
5. Working with Sequences and Collections
Python provides several built-in functions and methods for working with sequences and collections like lists, tuples, dictionaries, and sets. Examples include len(), sorted(), and max().
Certainly! Let's explore in more detail how to work with sequences and collections in Python using built-in functions and methods. These functions and methods are incredibly useful for performing various operations on data structures. We'll focus on some common ones:
1. len(): Get the Length of a Sequence or Collection
The len() function is used to find the length of a sequence, collection, or any iterable object. It returns the number of elements in the object.
Example:
fruits = ["apple", "banana", "cherry"]
length = len(fruits)
print("Length of the list:", length)
# Output: Length of the list: 3
2. sorted(): Sort Elements in a Sequence
The sorted() function is used to sort elements in a sequence or collection in ascending order. By default, it sorts elements alphabetically for strings and numerically for numbers.
Example:
numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
sorted_numbers = sorted(numbers)
print("Sorted numbers:", sorted_numbers)
# Output: Sorted numbers: [1, 1, 2, 3, 3, 4, 5, 5, 5, 6, 9]
3. max() and min(): Find Maximum and Minimum Values in a Sequence
The max() function returns the maximum value from a sequence, while the min() function returns the minimum value.
Example:
numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
maximum = max(numbers)
minimum = min(numbers)
print("Maximum:", maximum)
print("Minimum:", minimum)
# Output: Maximum: 9
# Minimum: 1
4. sum(): Calculate the Sum of Elements in a Sequence
The sum() function is used to calculate the sum of all elements in a sequence or collection.
Example:
numbers = [1, 2, 3, 4, 5]
total = sum(numbers)
print("Sum of numbers:", total)
# Output: Sum of numbers: 15
5. any() and all(): Check for Truthiness in Sequences
The any() function returns True if at least one element in the sequence is True or true. The all() function returns True if all elements in the sequence are True or true.
Example:
bool_values = [True, False, True, False]
any_true = any(bool_values)
all_true = all(bool_values)
print("Any true:", any_true)
print("All true:", all_true)
# Output: Any true: True
# All true: False
6. enumerate(): Iterate with Index and Value
The enumerate() function is used to loop through a sequence or collection while keeping track of the index and value of each element.
Example:
fruits = ["apple", "banana", "cherry"]
for index, fruit in enumerate(fruits):
print(f"Index {index}: {fruit}")
Output:
Index 0: apple
Index 1: banana
Index 2: cherry
These functions and methods are essential tools for working with sequences and collections in Python. Whether you need to find the length of a list, sort data, calculate sums, or check the truthiness of elements, Python provides built-in functions to simplify these operations.
Now, let's conclude this part with a final exercise:
Exercise
Now that you've learned about Python data structures, let's practice:
Exercise 1: Create a list of your favorite movies and print them.
Exercise 2: Create a tuple of your personal information (name, age, city) and display it.
Exercise 3: Build a dictionary representing a book with keys like "title," "author," and "year," and then print the book's details.
Exercise 4: Create two sets with your favorite colors and a friend's favorite colors. Find the common colors between the sets and print them.
Exercise 5: Given a list of words, write a Python program that finds and prints the longest word(s) in the list. If there are multiple longest words, print all of them.
Solution to Previous Exercises (Part 2):
Exercise 1:
# Get the user's name
name = input("What's your name? ")
# Greet the user
print("Hello, " + name + "!")
Exercise 2:
# Check if a number is even or odd
number = int(input("Enter a number: "))
if number % 2 == 0:
print(number, "is even.")
else:
print(number, "is odd.")
Exercise 3:
# Convert Celsius to Fahrenheit
celsius = float(input("Enter temperature in Celsius: "))
fahrenheit = (celsius * 9/5) + 32
print("Temperature in Fahrenheit:", fahrenheit)
Exercise 4:
# Simple calculator
num1 = float(input("Enter first number: "))
operator = input("Enter operator (+, -, *, /): ")
num2 = float(input("Enter second number: "))
if operator == '+':
result = num1 + num2
elif operator == '-':
result = num1 - num2
elif operator == '*':
result = num1 * num2
elif operator == '/':
result = num1 / num2
else:
result = "Invalid operator"
print("Result:", result)
In this blog post, we explored Python data structures, including lists, tuples, dictionaries, and sets. We also discussed working with sequences and collections. These concepts are fundamental to scripting and automation tasks in Python. Feel free to share your solution in the comments section below.
In the next part of our series, we'll dive into loops and iteration, so stay tuned for more Python scripting tutorials!