Mastering Python Lists and Dictionaries
Posted on June 1, 2024 (Last modified on June 8, 2024) • 2 min read • 313 wordsDiscover advanced techniques for working with lists and dictionaries in Python, including list comprehensions, dictionary comprehensions, and common operations.
Lists and dictionaries are fundamental data structures in Python. This guide covers advanced techniques for working with them, including comprehensions and common operations.
Create lists using comprehensions for more readable and concise code.
squares = [x**2 for x in range(10)]
print(squares)List comprehensions can include conditionals.
squares = [x**2 for x in range(10) if x % 2 == 0]
print(squares) # Output: [0, 4, 16, 36, 64]# Adding elements
my_list = [1, 2, 3]
my_list.append(4)
# Removing elements
my_list.remove(2)
# Slicing
print(my_list[1:3])Other common operations include sorting and reversing lists.
numbers = [5, 1, 8, 3]
numbers.sort()
print(numbers) # Output: [1, 3, 5, 8]
numbers.reverse()
print(numbers) # Output: [8, 5, 3, 1]Lists can contain other lists.
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
for row in matrix:
for item in row:
print(item)Similar to list comprehensions, but for creating dictionaries.
squares = {x: x**2 for x in range(10)}
print(squares)Dictionary comprehensions can also include conditionals.
even_squares = {x: x**2 for x in range(10) if x % 2 == 0}
print(even_squares) # Output: {0: 0, 2: 4, 4: 16, 6: 36, 8: 64}# Adding key-value pairs
my_dict = {"name": "Alice", "age": 25}
my_dict["email"] = "alice@example.com"
# Removing key-value pairs
del my_dict["age"]
# Iterating over a dictionary
for key, value in my_dict.items():
print(key, value)Other useful operations include getting keys and values.
keys = my_dict.keys()
values = my_dict.values()
print(keys)
print(values)Dictionaries can contain other dictionaries.
person = {
"name": "Alice",
"age": 25,
"address": {
"street": "123 Main St",
"city": "Wonderland"
}
}
print(person["address"]["city"]) # Output: WonderlandMastering lists and dictionaries is crucial for effective Python programming. Use these advanced techniques to manipulate and manage data more efficiently in your projects.