import requestsfrom bs4 import BeautifulSoupimport jiebafrom wordcloud import WordCloudimport matplotlib.pyplot as plturl = 'https://www.gushiwen.org/gushi/tangshi.aspx'response = requests.get(url)html = response.textsoup = BeautifulSoup(html, 'html.parser')links = soup.select('.bookMl a')poem_links = [link['href'] for link in links]poems = []for link in poem_links: poem_url = 'https://www.gushiwen.org{}'.format(link) poem_response = requests.get(poem_url) poem_html = poem_response.text poem_soup = BeautifulSoup(poem_html, 'html.parser') poem_content = poem_soup.select_one('.contson').text.strip() poems.append(poem_content)text = ''.join(poems)words = jieba.cut(text)wordcloud = WordCloud(font_path='msyh.ttc').generate(' '.join(words))plt.imshow(wordcloud, interpolation='bilinear')plt.axis('off')plt.show()

翻译下面代码from wordcloud import WordCloudimport matplotlib.pyplot as plt with open('text.txt', 'r') as f: text = f.read()

从 matplotlib.pyplot 中导入 pyplot 模块并将其重命名为 plt 使用 open() 函数打开名为 'text.txt' 的文件，并将文件对象赋值给变量 f 使用 f.read() 函数读取文本文件的内容并将其赋值给变量 text

import numpy as np import matplotlib.pyplot as plt import math

import matplotlib.pyplot as plt import math # 解决图标题中文乱码问题 import matplotlib as mpl mpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体 mpl.rcParams['axes.unicode_minus'] = False #...

import pandas as pd from wordcloud import WordCloud import matplotlib.pyplot as plt import jieba df= pd.read_excel('海南疫情.xlsx') word_dict = dict(zip(df['地点'], df['感染人数'])) wc = WordCloud(width=800, height=400, background_color='white', max_words=100, font_path='msyh.ttc') wc.generate_from_frequencies(word_dict) plt.imshow(wc, interpolation='bilinear') plt.axis('off') plt.show()

这段代码是用来生成一个基于海南疫情数据的词云图。首先，它导入了 pandas ...需要注意的是，要使用该代码，需要确保安装了 pandas、WordCloud 和 matplotlib 库，并且确保有一个名为“海南疫情.xlsx”的 Excel 文件。

import matplotlib.pyplot as pit import matplotlib.pyplot as plt from wordcloud import WordCloud text = open().read() text = " ".join(jieba.cut(text)) wc = WordCloud(font_path = "",width = 500,height = 300,mode="RGBA",backgroud_color=None).generate(text) plt.imshw(wc,interpolation="") plt.axis("") plt.show() wc.to_file("")

1. import matplotlib.pyplot as pit 应该改为 import matplotlib.pyplot as plt。 2. text = open().read() 应该指定要读取的文本文件路径，比如 text = open('example.txt', encoding='utf-8').read()。 3...

import jieba import numpy import numpy as np from PIL import Image from wordcloud import WordCloud, STOPWORDS import matplotlib.pyplot as plt with open("comments.txt","r",encoding="utf-8") as f: comments = f.read() words = jieba.cut(comments) stopwords = set(STOPWORDS) stopwords.add('腾讯') stopwords.add('游戏') filtered_words = [] for word in words: if word not in stopwords: filtered_words.append(word) mask = np.array(Image.open("mask.png")) cloud = WordCloud( font_path="C:\Windows\Fonts\simsun.ttc", background_color="white", mask=mask ).generate(" ".join(filtered_words)) cloud.to_file("词云.png") print("词云绘制成功")这个代码怎么运行错误

import matplotlib.pyplot as plt with open("comments.txt","r",encoding="utf-8") as f: comments = f.read() words = jieba.cut(comments) stopwords = set(STOPWORDS) stopwords.add('腾讯') stopwords....

解决这段代码的错误 ##chinese from wordcloud import WordCloud import matplotlib.pyplot as plt import pandas as pd # 打开文本 text = pd.read_excel("huati.xlsx", encoding="utf-8").read() # 生成对象 wc = WordCloud(font_path="msyh.ttc", width=800, height=600, mode="RGBA", background_color=None).generate(text) # 显示词云 plt.imshow(wc, interpolation='bilinear') plt.axis("off") plt.show() # 保存到文件 wc.to_file("bulletchinese.png")

import matplotlib.pyplot as plt import pandas as pd import jieba # 打开文本 text = pd.read_excel("huati.xlsx", encoding="utf-8").to_string() # 对文本进行分词处理 text = " ".join(jieba.cut(text)) # ...

修改代码import jieba import numpy as np import matplotlib.pyplot as plt text = open('comment.txt', encoding='utf-8').read() from PIL import Image, ImageDraw, ImageFont from wordcloud import WordCloud text = ' '.join(jieba.cut(text)) # 生成对象 mask = np.array(Image.open("computer.jpg")) wc = WordCloud(ImageFont.truetype("arial.ttf")).generate(text) # 显示词云 # plt.imshow(wc, interpolation = 'bilinear') # plt.axis("off") # plt.show() # 保存文件 wc.to_file('rs_computer.png')

import matplotlib.pyplot as plt from PIL import Image, ImageDraw, ImageFont from wordcloud import WordCloud text = open('comment.txt', encoding='utf-8').read() text = ' '.join(jieba.cut(text)) #...

import jieba import wordcloud import matplotlib.pyplot as plt strs='君自故乡来，应知故乡事。来日绮窗前，寒梅着花未？每个人的心里，都有一方魂牵梦萦的土地。得意时想到它，失意时想到它。逢年逢节，触景生情，随时随地想到它。' words=jieba.lcut(strs) words=' '.join(words) img=plt.imread("D:\学习\heart.jpg") wc=wordcloud.WordCloud(background_color='white',font_path="simkai.ttf",mask=img) wc.generate(words) wc.to_file('img.png')

1. 首先导入了jieba、wordcloud和matplotlib.pyplot三个模块。 2. 定义一个字符串变量strs来存储文本内容。 3. 使用jieba.lcut()函数对strs进行分词，将分词结果存储在words变量中。 4. 将words中的分词结果用空格...

优化这段代码：import requests from bs4 import BeautifulSoup import jieba url = "http://xc.hfut.edu.cn/1955/list{}.htm" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"} news_list = [] for i in range(1, 6): # 爬取前5页的新闻标题 res = requests.get(url.format(i), headers=headers) soup = BeautifulSoup(res.text, "html.parser") news = soup.find_all("span", {"class": "news_title"}) for n in news: news_list.append(n.a.string) # 对新闻标题进行分词 words_list = [] for news in news_list: words = jieba.cut(news) for word in words: words_list.append(word) from wordcloud import WordCloud import matplotlib.pyplot as plt from PIL import Image import numpy as np # 读入背景图片 image = Image.open("C:\\xhktSoft\huahua.jpg") graph = np.array(image) # 设置停用词 stop_words = ["的", "是", "在", "了", "和", "与", "也", "还", "有", "就", "等", "中", "及", "对", "是"] # 生成词云图 wc = WordCloud(font_path="msyh.ttc", background_color='white', max_words=200, mask=graph, stopwords=stop_words, max_font_size=200, random_state=42) wc.generate_from_text(" ".join(words_list)) # 绘制词云图 plt.imshow(wc, interpolation='bilinear') plt.axis("off") plt.show()

import matplotlib.pyplot as plt from PIL import Image import numpy as np # 定义函数获取新闻标题 def get_news_titles(url): headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) ...

import matplotlib.pyplot as plt import jieba import wordcloud from wordcloud import ImageColorGenerator import numpy as np from PIL import Image # 读取文本文件 text = open('4447.txt',encoding='utf-8'.read() cut_text = jieba.cut(text) word = ' '.join(cut_text) return txt_jieba #读取图片 pic = np.array(Image.open('aa.png')) image_colors = ImageColorGenerator(pic) wd = wordcloud.WordCloud( mask=pic, font_path='simhei.ttf', background_color='pink', ) wd.generate(word) plt.imshow(wd.recolor(color_func=image_colors), interpolation='bilinear') plt.axis('y off') plt.show('x on')

import matplotlib.pyplot as plt import jieba import wordcloud from wordcloud import ImageColorGenerator import numpy as np from PIL import Image # 读取文本文件 text = open('4447.txt', encoding='utf-8...

请写出以下代码的设计思路及步骤import jieba import wordcloud import matplotlib.pyplot as plt import numpy as np from PIL import Image mask = np.array(Image.open(r"C:\Users\28243\Desktop\zuoye\image.png")) img_array = np.array(mask) file = open(r"C:\Users\28243\Desktop\zuoye\i love china.txt", "r", encoding="utf-8") t = file.read() file.close() ls = jieba.lcut(t) txt = " ".join(ls) # 设置词云图 w = wordcloud.WordCloud( font_path="C:/Windows/Fonts/SIMSUN.TTC", # 词云字体 width=2400, # 图片宽度 height=2000, # 图片高度 contour_width=2, mask = img_array, contour_color='steelblue', background_color="white") # 图片背景颜色 # 将文字导入词云 w.generate(txt) # 保存词云图 w.to_file("wordcloud_19.png")

1. 导入需要的模块：导入jieba用于中文分词，wordcloud用于生成词云图，matplotlib.pyplot用于显示图像，numpy用于处理图像数组，PIL.Image用于打开和处理图像。 2. 加载背景图片：使用PIL.Image的open方法打开背景...

import pandas as pd import numpy as np import re import jieba from collections import Counter from wordcloud import WordCloud import matplotlib.pyplot as plt# 读取数据 # df = df[['text', 'label']] # df = df.dropna()# 分组 # groups = df.groupby('label')# 加载停用词 stop_words = set() with open('C:/Users/Administrator/Desktop/停用词/stopwords.txt', 'r', encoding='utf-8') as f: for line in f.readlines(): stop_words.add(line.strip())# 定义函数，用于去除停用词和提取关键词 def extract_keywords(text): words = [word for word in jieba.cut(text) if word not in stop_words] return Counter(words).most_common(10)# 提取关键词 keywords = {} for name, group in groups: keywords[name] = [] for text in group['text']: keywords[name].extend(extract_keywords(text)) keywords[name] = dict(keywords[name])# 绘制词云 for name, words in keywords.items(): wordcloud = WordCloud(width=800, height=400, font_path='msyh.ttc').generate_from_frequencies(words) plt.figure(figsize=(12, 8)) plt.imshow(wordcloud, interpolation='bilinear') plt.axis("off") plt.title(name) plt.show() 代码对吗

import matplotlib.pyplot as plt # 读取数据 df = pd.read_csv('data.csv') df = df[['text', 'label']] df = df.dropna() # 分组 groups = df.groupby('label') # 加载停用词 stop_words = set() with open('C:...

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