Introduction
Dictionaries in Python are powerful data structures that allow storing and managing data in a key-value format. Unlike lists, which are indexed numerically, dictionaries use unique keys to store and access values efficiently.
In this guide, we will explore Python dictionaries in detail, covering their creation, operations, best practices, exceptions, and practical programs at different levels.
1. What is a Dictionary in Python?
A dictionary in Python is an unordered collection of items where each item is a key-value pair.
Key Features of Dictionaries:
- Unordered: Items do not have a fixed order.
- Mutable: You can modify, add, or delete key-value pairs.
- Unique Keys: Each key in a dictionary must be unique.
- Efficient Lookup: Accessing values using keys is faster than searching in a list.
Creating a Dictionary
# Empty dictionary
my_dict = {}
# Dictionary with data
person = {"name": "Alice", "age": 25, "city": "New York"}
print(person)
# Output: {'name': 'Alice', 'age': 25, 'city': 'New York'}2. Accessing Dictionary Elements
Using Keys
print(person["name"]) # Output: AliceUsing get() Method
print(person.get("age")) # Output: 25get()is preferred because it does not raise an error if the key is missing.
Handling Missing Keys
print(person.get("salary", "Key not found")) # Output: Key not found3. Modifying Dictionaries
Adding a New Key-Value Pair
person["country"] = "USA"
print(person)
# Output: {'name': 'Alice', 'age': 25, 'city': 'New York', 'country': 'USA'}Updating an Existing Key’s Value
person["age"] = 26
print(person)
# Output: {'name': 'Alice', 'age': 26, 'city': 'New York', 'country': 'USA'}Removing Key-Value Pairs
del person["city"] # Deletes 'city'
age = person.pop("age") # Removes and returns the value of 'age'
print(person) # Output: {'name': 'Alice', 'country': 'USA'}4. Iterating Through Dictionaries
Iterating Over Keys
for key in person:
print(key)Iterating Over Values
for value in person.values():
print(value)Iterating Over Key-Value Pairs
for key, value in person.items():
print(f"{key}: {value}")5. Dictionary Methods and Operations
Common Dictionary Methods
| Method | Description |
|---|---|
keys() | Returns all dictionary keys |
values() | Returns all values |
items() | Returns key-value pairs |
update(dict2) | Merges dict2 into the current dictionary |
clear() | Removes all items from the dictionary |
Example:
student = {"name": "Bob", "grade": "A"}
print(student.keys()) # Output: dict_keys(['name', 'grade'])6. Dictionary Comprehensions
squares = {x: x*x for x in range(1, 6)}
print(squares)
# Output: {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}7. Exception Handling in Dictionaries
1. KeyError (When a non-existent key is accessed)
try:
print(person["salary"])
except KeyError:
print("Key not found!")2. TypeError (When a mutable type like a list is used as a key)
try:
my_dict = {[1, 2, 3]: "value"}
except TypeError as e:
print("Error:", e)8. Practical Programs
Basic Level: Count word frequency in a string
text = "apple banana apple orange banana apple"
words = text.split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
print(word_count) # Output: {'apple': 3, 'banana': 2, 'orange': 1}Intermediate Level: Merge two dictionaries and sum common keys
dict1 = {"a": 5, "b": 10, "c": 15}
dict2 = {"b": 20, "c": 25, "d": 30}
merged_dict = {key: dict1.get(key, 0) + dict2.get(key, 0) for key in set(dict1) | set(dict2)}
print(merged_dict) # Output: {'a': 5, 'b': 30, 'c': 40, 'd': 30}Advanced Level: Nested dictionary example
employees = {
"emp1": {"name": "Alice", "age": 30, "department": "HR"},
"emp2": {"name": "Bob", "age": 25, "department": "Finance"}
}
print(employees["emp1"]["name"]) # Output: Alice9. Do’s and Don’ts
✅ Do’s:
✔ Use .get() to avoid KeyError.
✔ Use dictionary comprehensions for clean and efficient code.
✔ Use immutable data types (like tuples) as keys.
❌ Don’ts:
✘ Avoid using mutable keys like lists.
✘ Avoid modifying dictionaries while iterating over them.
✘ Avoid using .update() if you need to preserve old values.
Conclusion
Dictionaries in Python are an essential tool for efficient data storage and retrieval. They provide fast lookups, flexible modifications, and various useful methods. By following best practices and understanding potential pitfalls, you can leverage dictionaries effectively in Python programming.