Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
Build a defaultdict histogram of categories in Python
Count occurrences of each category in a list using collections.defaultdict(int) for automatic initialization.
from collections import defaultdict
def build_category_histogram(items):
"""Count occurrences of each category in a list of items."""
histogram = defaultdict(int)
for item in items:
histogram[item] += 1
return dict(histogram)
if __name__ == "__main__":
categories = ["fruit", "vegetable", …
Count Word Frequency in Python with dict
Count how often each word appears in a text using Python's collections.Counter and regular expressions.
from collections import Counter
import re
def count_word_frequency(text):
"""Count frequency of each word in text (case-insensitive)."""
words = re.findall(r"\b\w+\b", text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The …
Count Words in Python with Dictionaries and Sets
Text analysis example that counts total words, finds unique words with a set, and tallies character frequencies with a dictionary.
def analyze_text(text: str) -> dict:
"""Count words, find unique words, and show common characters."""
words = text.lower().split()
word_count = len(words)
unique_words = set(words)
char_counts = {}
for word in words:
for char in word:
if char.isalpha():
…
Count word frequency in Python with dict and Counter
Count how often each word appears in a string using Counter, converted to a plain dict, and print results alphabetically.
from collections import Counter
import re
def count_word_frequency(text):
words = re.findall(r'\b\w+\b', text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The dog barks, and the fox runs."
frequency = count_word_frequency(…
How to Convert a Counter to a Plain Dict with Sorted Items in Python
This code converts a collections.Counter into a regular dictionary with items sorted by key, useful for stable, readable output.
from collections import Counter
def counter_to_sorted_dict(counter):
"""Convert a Counter to a plain dict with sorted items."""
return dict(sorted(counter.items()))
if __name__ == "__main__":
# Example usage
data = Counter(['apple', 'banana', 'apple', 'cherry', 'banana', 'date', 'apple'])
print("…
How to Count Co-occurrence Pairs in Python with Nested Dictionaries
This code counts how often any two items appear together in the same group, using a nested defaultdict keyed by item pairs.
from itertools import combinations
from collections import defaultdict
def count_cooccurrences(items_per_group):
cooccurrence = defaultdict(lambda: defaultdict(int))
for group in items_per_group:
for a, b in combinations(sorted(group), 2):
cooccurrence[a][b] += 1
cooccurrence[b…
How to Count Elements and Find Duplicates in a Python List
Count occurrences of each element in a list, extract unique values, and identify duplicates using Python dictionaries and sets.
def analyze_counts(data):
"""Count elements, return unique values, and find duplicates."""
# Count occurrences using a dictionary
counts = {}
for item in data:
counts[item] = counts.get(item, 0) + 1
# Alternative compact approach with set
unique_items = set(data)
# Fi…
How to Count Tags with Sets and Dictionaries in Python
Count tag frequencies and collect unique tags from a list of dictionaries using Counter and sets in Python.
from collections import Counter
import json
def count_tags(entries):
"""Count tag frequencies across a list of entry dicts, using sets/dicts."""
tag_counter = Counter()
all_tags = set()
for entry in entries:
tags = set(entry["tags"])
all_tags.update(tags)
tag_counter.update(ta…
How to Count Word Frequencies in Python
Count how often each word appears in a string and list the unique words using Python dictionaries and sets.
def text_processor(text):
words = text.lower().split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
return word_count, unique_words
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog and t…
How to Count Word Frequencies in Python with Counter and Sets
This code processes a text string by lowercasing, splitting into words, counting frequencies with Counter, and extracting unique and sorted word lists using sets.
from collections import Counter
def process_text(text):
words = text.lower().split()
word_counts = Counter(words)
unique_words = set(words)
sorted_words = sorted(unique_words)
return {
"total_words": len(words),
"unique_words": len(unique_words),
"word_frequencies": di…
How to Count Words and Find Common Words in Python with Dictionaries and Sets
Build a simple text processor that counts unique words with dictionaries and finds common words across text halves using sets.
def process_text(text):
"""Process text: count unique words with counts, find common words."""
words = text.lower().replace(",", "").replace(".", "").split()
word_counts = {}
for word in words:
word_counts[word] = word_counts.get(word, 0) + 1
total_words = len(words)
unique_wo…
How to Subtract Counters in Python for Bag Differences
Use the Counter class's subtraction operator to compute bag differences, removing items and counts that appear in one multiset but not the other.
from collections import Counter
def subtract_counters(bag1, bag2):
"""Return the difference of two Counters (bag1 - bag2)."""
return bag1 - bag2
if __name__ == "__main__":
inventory = Counter(apples=10, bananas=5, oranges=3)
sold = Counter(apples=4, bananas=2, grapes=2)
remaining = subtract_count…
How to Use Counter for Most Common Elements in Python
This code demonstrates how to find the most frequent elements in a list using Python's Counter class from the collections module.
from collections import Counter
def most_common_elements(items, n=1):
"""Return the n most common elements and their counts."""
counter = Counter(items)
return counter.most_common(n)
if __name__ == "__main__":
data = ["apple", "banana", "apple", "orange", "banana", "apple", "grape"]
print(most_co…
How to Use Dictionaries and Sets in Python for Beginners
Introduces Python dictionaries and sets with practical examples including creating, modifying, and performing set operations, plus a word-frequency counter.
def demonstrate_dict_sets():
# Create a dictionary with basic info
person = {
"name": "Alice",
"age": 30,
"city": "New York"
}
print("Dictionary:", person)
# Access and modify dictionary values
person["age"] = 31
person["email"] = "alice@example.com"
print("Afte…
How to Validate Text and Count Words in Python
Count word frequencies, find unique and repeated words in a text using Python dictionaries and sets for beginner text validation.
def validate_text(text):
words = text.lower().split()
word_counts = {}
for word in words:
cleaned = word.strip('.,!?;:"\'')
if cleaned:
word_counts[cleaned] = word_counts.get(cleaned, 0) + 1
unique_words = set(word_counts.keys())
repeated_words = {word for word…
How to count words and find unique words in Python
Build a beginner-friendly text processor that counts word frequencies, finds unique words, and identifies words with vowels using dictionaries and sets.
def text_processor(text):
words = text.lower().replace(",", "").replace(".", "").split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
vowels = set("aeiou")
words_with_vowels = {word for word in unique_words if vowe…
Multiset with Counter update and elements in Python
Demonstrates using collections.Counter as a multiset: updating counts with update() and iterating elements() to get repeated items.
from collections import Counter
multiset = Counter(['apple', 'banana', 'apple'])
multiset.update(['banana', 'cherry', 'apple'])
print("Elements after update:", sorted(multiset.elements()))
print("Counts:", dict(multiset))
print("Most common:", multiset.most_common(2))
Text Processor with Dictionaries and Sets in Python
Build a simple text processor that counts word frequencies with a dictionary and tracks unique words with a set.
def analyze_text(text):
words = text.lower().split()
word_freq = {}
unique_words = set()
for word in words:
clean_word = word.strip('.,!?;:')
if clean_word:
word_freq[clean_word] = word_freq.get(clean_word, 0) + 1
unique_words.add(clean_word)
return…
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