PYTHON
Grouping Data by Key with collections.defaultdict
Discover how collections.defaultdict simplifies grouping items by a common key without needing to check if the key already exists, making dictionary construction cleaner.
from collections import defaultdict
data = [
{'name': 'Alice', 'city': 'New York'},
{'name': 'Bob', 'city': 'London'},
{'name': 'Charlie', 'city': 'New York'},
{'name': 'David', 'city': 'London'},
{'name': 'Eve', 'city': 'Paris'}
]
# Grouping people by city
grouped_by_city = defaultdict(list)
for person in data:
grouped_by_city[person['city']].append(person['name'])
print(f"People grouped by city: {dict(grouped_by_city)}")
# defaultdict with int for counting
word_counts = defaultdict(int)
sentence = "the quick brown fox jumps over the lazy dog"
for word in sentence.split():
word_counts[word] += 1
print(f"Word counts: {dict(word_counts)}")
How it works: collections.defaultdict is a subclass of dict that calls a factory function (e.g., list, int, set) to supply missing values when a key is accessed for the first time. This eliminates the need for if key in dict: checks when appending to a list or incrementing a count, making the code significantly more concise and less error-prone, especially for grouping operations in data processing.