


How to Count and Sort Word Frequencies in Python Using Counter?
Counting and Sorting Word Frequencies in a List
In a recent project, you encountered a problem where you needed to count the occurrences of words in a list and sort them by frequency, with the most frequently appearing word at the beginning of the list. While you had a basic idea of the solution, you were unsure how to implement it in Python 3.3 effectively.
Fortunately, Python's collections.Counter class provides a simple and efficient solution to this problem. Here's an example:
<code class="python">from collections import Counter # Create a list of words list1 = ['apple', 'egg', 'apple', 'banana', 'egg', 'apple'] # Use Counter to count word occurrences counts = Counter(list1) # Print the counts print(counts) # Counter({'apple': 3, 'egg': 2, 'banana': 1})</code>
In this example, Counter creates a dictionary-like object where the keys are words, and the values are their counts. The print statement outputs the counts for each unique word.
To sort the words based on frequency, you can use the most_common() method of Counter. This method returns a list of tuples, where each tuple contains a word and its count. By default, the list is sorted in descending order of frequency, meaning the most frequent word will be at the beginning.
Here's how you can sort the list of words:
<code class="python"># Sort the words based on frequency sorted_words = [word for word, count in sorted(counts.most_common(), key=lambda x: x[1], reverse=True)] # Print the sorted list print(sorted_words) # ['apple', 'egg', 'banana']</code>
In this code, sorted sorts the list of tuples by the second element (count) in descending order using the reverse=True argument. This ensures that the most frequent word comes first in the sorted_words list.
The above is the detailed content of How to Count and Sort Word Frequencies in Python Using Counter?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
