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import pandas as pd from wordcloud import WordCloud from matplotlib import pyplot as plt pd.set_option('display.float_format', lambda x: '%.4f' % x) # 取消科学计数法 data=pd.read_excel('./GDP.xlsx',sheet_name='2021',usecols=['国家/地区','GDP总量(人民币核算)']) print(data.head()) list_country=data['国家/地区'].tolist() list_gdp=data['GDP总量(人民币核算)'].tolist() dic=dict(zip(list_country,list_gdp)) print(dic) font=r'C:\Windows\Fonts\simhei.ttf' wordcloud=WordCloud(background_color='black',width=800,height=800,margin=1,font_path=font).generate_from_frequencies(dic) plt.imshow(wordcloud) plt.axis('off') plt.show()
import pandas as pd import numpy as np from wordcloud import WordCloud from matplotlib import pyplot as plt from PIL import Image pd.set_option('display.float_format', lambda x: '%.4f' % x) # 取消科学计数法 data=pd.read_excel('./GDP.xlsx',sheet_name='2021',usecols=['国家/地区','GDP总量(人民币核算)']) print(data.head()) list_country=data['国家/地区'].tolist() list_gdp=data['GDP总量(人民币核算)'].tolist() dic=dict(zip(list_country,list_gdp)) print(dic) font=r'C:\Windows\Fonts\simhei.ttf' MASK=np.array(Image.open('./rmb.jpg')) wordcloud=WordCloud(background_color='white',scale=1,max_words=500,max_font_size=100,font_path=font,mask=MASK,repeat=False,mode='RGB',colormap='winter').generate_from_frequencies(dic) plt.imshow(wordcloud,interpolation='bilinear') plt.axis('off') plt.show()
import re import jieba import pandas as pd from wordcloud import WordCloud from matplotlib import pyplot as plt text=pd.read_csv('zfgzbg.txt',index_col=0) print(text) text2=str(text) # 去除特殊字符、数字和字母,只保留汉字 text3=re.sub("[a-zA-Z0-9'!""#$%&\'()*+,-./:;<=>?@,。?★、…【】《》:?“”‘'![\\]^_`{|}~\s]+","",text2) print(text3) text4=jieba.lcut(text3) print(text4) text5=' '.join(text4) print(text5) # 暂时列举以下停用词,可根据实际需要进行补充删改 stopwords=['我','和','你','的','地','得','了','都','对','向','在','可','能','为','要','再','是','等','一','二','三','四','五','六','七','八','九','十','各位','代表','一年','请予'] font=r'C:\Windows\Fonts\simhei.ttf' wordcloud=WordCloud(background_color='white',scale=1,max_words=500,max_font_size=100,font_path=font,stopwords=stopwords).generate_from_text(text5) plt.imshow(wordcloud,interpolation='bilinear') plt.axis('off') plt.show()
import re import jieba import pandas as pd import numpy as np from PIL import Image from wordcloud import WordCloud from matplotlib import pyplot as plt text=pd.read_csv('zfgzbg.txt',index_col=0) print(text) text2=str(text) # 去除特殊字符、数字和字母,只保留汉字 text3=re.sub("[a-zA-Z0-9'!""#$%&\'()*+,-./:;<=>?@,。?★、…【】《》:?“”‘'![\\]^_`{|}~\s]+","",text2) print(text3) text4=jieba.lcut(text3) print(text4) text5=' '.join(text4) print(text5) # 暂时列举以下停用词,可根据实际需要进行补充删改 stopwords=['我','和','你','的','地','得','了','都','对','向','在','可','能','为','要','再','是','等','一','二','三','四','五','六','七','八','九','十','各位','代表','一年','请予'] font=r'C:\Windows\Fonts\simhei.ttf' MASK=np.array(Image.open('./map.jpg')) wordcloud=WordCloud(background_color='white',scale=2,max_words=500,max_font_size=150,font_path=font,stopwords=stopwords,mask=MASK,colormap='brg').generate_from_text(text5) plt.imshow(wordcloud,interpolation='bilinear') plt.axis('off') plt.show()
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