Python program to get percentage of word frequency
In this article, we will learn how to get word frequency as a percentage in Python.
Suppose we have obtained a string input list. Now, we will find the percentage of each word in the given list of input strings.
formula
(Occurrence of X word / Total words) * 100
usage instructions
Use sum(), Counter(), join() and split() functions
Use join(), split() and count() functions
Use the countOf() function of the operator module.
Method 1: Use sum(), Counter(), join() and split() functions
join() is a string function in Python that is used to join sequence elements separated by string delimiters to form a string.
Counter() The function is a subclass that counts the number of hashable objects. It implicitly creates a hash table of iterable objects when called/invoked.
Algorithm (steps)
The following are the algorithms/steps to perform the required task:
Use the import keyword to import the Counter function from the collection module.
Create a variable to store the input list string and print the list.
Use the join() function to join all string elements of the input list.
Use the split() function (split the string into a list. The delimiter can be defined; the default delimiter is any whitespace character) to split the concatenated string into a list of words, and use Counter() Function gets word frequency as key-value pair
Use values() function to get all values (frequency/count) from Counter and use sum() function to get their sum (returns the sum of all values) in the iterable project).
Use the items() function to get the percentage of each word in the above counter words (returns a view object, i.e. it contains the key-value pairs of the dictionary, as tuples in a list).
Print the percentage of each word in the input list.
Example
is:Example
The following program uses the sum(), Counter(), join() and split() functions to return the percentage of each word in a given list of input strings –
# importing a Counter function from the collections module from collections import Counter # input list of strings inputList = ["hello tutorialspoint", "python codes", "tutorialspoint for python", "see python codes tutorialspoint"] print("Input list:\n", inputList) # Joining all the string elements of the list using the join() function join_string = " ".join(i for i in inputList) # splitting the joined string into a list of words and getting the # frequency of words as key-value pairs using Counter() function counter_words = Counter(join_string.split()) # getting all the values(frequencies/counts) from counter and # finding the total sum of them total_sum = sum(counter_words.values()) # getting the percentage of each word from the above counter words res_percentage = {key: value / total_sum for key, value in counter_words.items()} # printing the percentage of each word from the input list print("Percentage of each word from the input list:\n", res_percentage)
Output
When executed, the above program will generate the following output -
Input list: ['hello tutorialspoint', 'python codes', 'tutorialspoint for python', 'see python codes tutorialspoint'] Percentage of each word from the input list: {'hello': 0.09090909090909091, 'tutorialspoint': 0.2727272727272727, 'python': 0.2727272727272727, 'codes': 0.18181818181818182, 'for': 0.09090909090909091, 'see': 0.09090909090909091}
Method 2: Use join(), split() and count() functions
Algorithm (steps)
The following are the algorithms/steps to perform the required task:
Create an empty dictionary to store the result percentage/term frequency.
Use for loop to traverse the word list.
Use the if conditional statement to check whether the current element is not in the key of the dictionary, use the keys() function.
If the above condition is true, use the count() function to get the count of the key (word).
Divide it by the number of words to get the current word frequency and store it as a key in the new dictionary created above.
Print the percentage of each word in the input list.
Example
is:Example
The following program uses the join(), split() and count() functions to return the percentage of each word in a given list of input strings –
# input list of strings inputList = ["hello tutorialspoint", "python codes", "tutorialspoint for python", "see python codes tutorialspoint"] # joining all the elements of the list using join() join_string = " ".join(i for i in inputList) # splitting the joined string into a list of words listOfWords = join_string.split() # Creating an empty dictionary for storing the resultant percentages resDict = dict() # traversing through the list of words for item in listOfWords: # checking whether the current element is not in the keys of a dictionary if item not in resDict.keys(): # getting the percentage of a current word if the condition is true resDict[item] = listOfWords.count(item)/len(listOfWords) # printing the percentage of each word from the input list print("Percentage of each word from the input list:\n", resDict)
Output
When executed, the above program will generate the following output -
Percentage of each word from the input list: {'hello': 0.09090909090909091, 'tutorialspoint': 0.2727272727272727, 'python': 0.2727272727272727, 'codes': 0.18181818181818182, 'for': 0.09090909090909091, 'see': 0.09090909090909091}
Method 3: Use the countOf() function of the operator module
The Chinese translation ofExample
is:Example
The following program uses the countOf() function to return the percentage of each word in a given list of input strings -
import operator as op # input list of strings inputList = ["hello tutorialspoint", "python codes", "tutorialspoint for python", "see python codes tutorialspoint"] # joining all the elements of list using join() join_string = " ".join(i for i in inputList) # splitting the joined string into list of words listOfWords = join_string.split() resDict = dict() for item in listOfWords: # checking whether the current element is not in the keys of dictionary if item not in resDict.keys(): resDict[item] = op.countOf(listOfWords, item)/len(listOfWords) print("Percentage of each word from the input list:\n", resDict)
Output
When executed, the above program will generate the following output -
Percentage of each word from the input list: {'hello': 0.09090909090909091, 'tutorialspoint': 0.2727272727272727, 'python': 0.2727272727272727, 'codes': 0.18181818181818182, 'for': 0.09090909090909091, 'see': 0.09090909090909091}
in conclusion
In this article, we learned three different Python methods to calculate percent word frequency. We also learned how to use the operator module's new function countOf() to get the frequency of a list element.
The above is the detailed content of Python program to get percentage of word frequency. 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

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.
