python数据预处理，jieba分词，去除停用词，词频分析，并生成词云图代码

以下是 Python 数据预处理、jieba 分词、去除停用词、词频分析并生成词云图的代码：

import jieba
from collections import Counter
from wordcloud import WordCloud
import matplotlib.pyplot as plt

# 读取文本文件
with open('text.txt', 'r', encoding='utf-8') as f:
    text = f.read()

# 使用 jieba 分词
words = jieba.cut(text)

# 去除停用词
stopwords = ['的', '了', '是', '我', '你', '他', '她', '我们', '你们', '他们']
words = [word for word in words if word not in stopwords]

# 统计词频
word_counts = Counter(words)

# 生成词云图
wordcloud = WordCloud(font_path='msyh.ttc', background_color='white').generate_from_frequencies(word_counts)
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()

希望能对你有所帮助！

相关问题

python数据预处理，jieba分词，去除停用词表，词频分析，并生成词云图代码

以下是 Python 数据预处理、jieba 分词、去除停用词表、词频分析并生成词云图的代码：

import jieba
from wordcloud import WordCloud
import matplotlib.pyplot as plt

# 读取文本文件
with open('text.txt', 'r', encoding='utf-8') as f:
    text = f.read()

# 分词
words = jieba.cut(text)

# 去除停用词表
stopwords = ['的', '了', '是', '我', '你', '他', '她', '它', '我们', '你们', '他们', '她们', '它们']
filtered_words = []
for word in words:
    if word not in stopwords:
        filtered_words.append(word)

# 词频分析
word_freq = {}
for word in filtered_words:
    if word in word_freq:
        word_freq[word] += 1
    else:
        word_freq[word] = 1

# 生成词云图
wordcloud = WordCloud(font_path='msyh.ttc', background_color='white', width=800, height=600).generate_from_frequencies(word_freq)
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()

希望能对你有所帮助！

python数据预处理，词频分析，并生成词云图代码

您好，以下是 Python 数据预处理、词频分析并生成词云图的代码：

import jieba
from wordcloud import WordCloud
import matplotlib.pyplot as plt

# 读取文本文件
with open('text.txt', 'r', encoding='utf-8') as f:
    text = f.read()

# 使用 jieba 分词
words = jieba.cut(text)

# 统计词频
word_counts = {}
for word in words:
    if len(word) == 1:  # 排除单个字符的词
        continue
    word_counts[word] = word_counts.get(word, ) + 1

# 生成词云图
wordcloud = WordCloud(font_path='simhei.ttf', width=800, height=600, background_color='white')
wordcloud.generate_from_frequencies(word_counts)
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()

希望能对您有所帮助。