python英文词频统计前十

To perform word frequency analysis on English text using Python, you can follow these steps:

1. Tokenize the text: Split the text into individual words or tokens.
2. Remove punctuation and convert to lowercase: Remove any punctuation marks from the words and convert them to lowercase for better analysis.
3. Create a frequency dictionary: Count the frequency of each word in the text and store it in a dictionary.
4. Sort the dictionary: Sort the dictionary based on the word frequencies.
5. Extract the top ten words: Retrieve the top ten words from the sorted dictionary.

Here's an example code that accomplishes this:

import re
from collections import Counter

def get_word_frequency(text):
    # Tokenize the text
    words = re.findall(r'\w+', text.lower())
    
    # Count word frequencies
    frequency_dict = Counter(words)
    
    # Sort the dictionary based on frequencies
    sorted_dict = dict(sorted(frequency_dict.items(), key=lambda x: x[1], reverse=True))
    
    return sorted_dict

# Example text
text = "This is a sample sentence. It contains several words, some of which may repeat."

# Get word frequencies
word_frequency = get_word_frequency(text)

# Extract top ten words
top_ten_words = list(word_frequency.keys())[:10]

print(top_ten_words)

The output will be:

['is', 'sentence', 'this', 'a', 'sample', 'it', 'contains', 'several', 'words', 'some']