Counter
Counter is a Python standard-library mapping that associates each hashable object with its integer occurrence count.
Natural Language Processing in Action, Second Edition
A Python Counter is a mapping type that counts hashable objects and stores each object with its frequency.
- How it is used
- Builds bag-of-words token counts for document vectors used in NLP search and machine learning.
- How deep it goes
- Works through counting, common tokens, and normalized frequencies, but leaves comparison with CountVectorizer output as an exercise.
- Examples
- Counts split greetings and spaCy-tokenized algorithmic-bias prose, including punctuation and repeated words.
- What you can do after
- Apply it via collections.Counter to count tokens, inspect common entries, and prepare counts for consistently indexed document vectors.
Read how Natural Language Processing in Action, Second Edition explains Counter →
Python Workout: 50 ten-minute exercises
Counter is a dictionary subclass in Python's standard library that maps hashable objects to their integer counts.
- How it is used
- Solves sequence-counting problems and supports selecting items by their highest frequency.
- How deep it goes
- Explains construction, dictionary inheritance, most_common results, limiting, indexing, and composition with max.
- Examples
- Uses words and letters, Counter('abcabcabbbc'), most_common outputs, and a most-repeating-word function.
- What you can do after
- Apply it via collections.Counter to count sequence items and rank them with most_common.
Read how Python Workout: 50 ten-minute exercises explains Counter →
Python Workout, Second Edition
Counter is a Python class in the collections module that maps hashable elements to their occurrence counts.
- How it is used
- Solves sequence-counting tasks and selects items by their highest occurrence count.
- How deep it goes
- Explains dict inheritance, sequence initialization, most_common ranking, and indexed extraction, but omits broader Counter operations.
- Examples
- Uses letter frequencies in words, Counter output, most_common listings, and helper functions for selecting the winning word.
- What you can do after
- Apply it via collections.Counter and most_common to count sequence elements and rank their frequencies.
Related concepts
- Mapkind of · A map is an associative data structure that stores key-value pairs and supports retrieving values by key.
- Counter.most_commonhas part · Counter.most_common is a Python method that returns counted elements and their frequencies in descending order, optionally limited to a specified number.
- collectionpart of · A collection is a data structure or abstraction that groups multiple elements for storage, access, traversal, or processing.
- token iduses · A token ID is a numeric identifier assigned to a token in a vocabulary so it can be represented and processed numerically.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.