python输出字体的大小_好玩又使用，使用Python生成漂亮的词云

词云是一种数据可视化技术&＃xff0c;用于表示文本数据&＃xff0c;其中每个单词的大小表示其出现的频率或重要性。可以使用词云突出显示重要的文本数据点。词云被广泛用于分析来自社交网络网站的数据。为了在Python中生成词云&＃xff0c;需要的模块是– matplotlib&＃xff0c;pandas和wordcloud。要安装这些软件包&＃xff0c;请运行以下命令&＃xff1a;pip install matplotlib
pip install pandas
pip install wordcloud代码1&＃xff1a;字数可以设置要在tagcloud上显示的最大单词数。为此&＃xff0c;请使用WordCloud()函数的max_words关键字参数。

# importing the necessery modulesfrom wordcloud import WordCloudimport matplotlib.pyplot as pltimport csv# file object is created
file_ob &＃61; open(r"linuxidc.com.csv")# reader object is created
reader_ob &＃61; csv.reader(file_ob)# contents of reader object is stored .# data is stored in list of list format.
reader_contents &＃61; list(reader_ob)# empty string is declare
text &＃61; ""# iterating through list of rowsfor row in reader_contents :# iterating through words in the rowfor word in row :# concatenate the words
text &＃61; text &＃43; " " &＃43; word# show only 10 words in the wordcloud .
wordcloud &＃61; WordCloud(width&＃61;480, height&＃61;480, max_words&＃61;10).generate(text)# plot the WordCloud image
plt.figure()
plt.imshow(wordcloud, interpolation&＃61;"bilinear")
plt.axis("off")
plt.margins(x&＃61;0, y&＃61;0)
plt.show()输出如下图&＃xff1a;代码2&＃xff1a;删除一些单词可以删除一些我们不想显示的词。为此&＃xff0c;请将这些单词传递给WordCloud()函数的停用词列表参数。

# importing the necessery modulesfrom wordcloud import WordCloudimport matplotlib.pyplot as pltimport csv# file object is created
file_ob &＃61; open(r"linuxidc.com.csv")# reader object is created
reader_ob &＃61; csv.reader(file_ob)# contents of reader object is stored .# data is stored in list of list format.
reader_contents &＃61; list(reader_ob)# empty string is declare
text &＃61; ""# iterating through list of rowsfor row in reader_contents :# iterating through words in the rowfor word in row :# concatenate the words
text &＃61; text &＃43; " " &＃43; word# remove Python , Matplotlib , Geeks Words from WordCloud .
wordcloud &＃61; WordCloud(width&＃61;480, height&＃61;480,
stopwords&＃61;["Python", "Matplotlib","Geeks"]).generate(text)# plot the WordCloud image
plt.figure()
plt.imshow(wordcloud, interpolation&＃61;"bilinear")
plt.axis("off")
plt.margins(x&＃61;0, y&＃61;0)
plt.show()输出效果如下&＃xff1a;代码3&＃xff1a;更改背景我们可以更改wordcloud背景的颜色。为此&＃xff0c;请使用WordCloud()函数的background_color关键字参数。

# importing the necessery modulesfrom wordcloud import WordCloudimport matplotlib.pyplot as pltimport csv# file object is created
file_ob &＃61; open(r"linuxidc.com.csv")# reader object is created
reader_ob &＃61; csv.reader(file_ob)# contents of reader object is stored .# data is stored in list of list format.
reader_contents &＃61; list(reader_ob)# empty string is declare
text &＃61; ""# iterating through list of rowsfor row in reader_contents :# iterating through words in the rowfor word in row :# concatenate the words
text &＃61; text &＃43; " " &＃43; word
wordcloud &＃61; WordCloud(width&＃61;480, height&＃61;480, background_color&＃61;"pink").generate(text)# plot the WordCloud image
plt.figure()
plt.imshow(wordcloud, interpolation&＃61;"bilinear")
plt.axis("off")
plt.margins(x&＃61;0, y&＃61;0)
plt.show()输出效果如下&＃xff1a;代码4&＃xff1a;更改单词的颜色我们可以使用WordCloud()函数的colormap关键字参数来更改单词的颜色。

# importing the necessery modulesfrom wordcloud import WordCloudimport matplotlib.pyplot as pltimport csv# file object is created
file_ob &＃61; open(r"linuxidc.com.csv")# reader object is created
reader_ob &＃61; csv.reader(file_ob)# contents of reader object is stored .# data is stored in list of list format.
reader_contents &＃61; list(reader_ob)# empty string is declare
text &＃61; ""# iterating through list of rowsfor row in reader_contents :# iterating through words in the rowfor word in row :# concatenate the words
text &＃61; text &＃43; " " &＃43; word
wordcloud &＃61; WordCloud(width&＃61;480, height&＃61;480, colormap&＃61;"Oranges_r").generate(text)# plot the WordCloud image
plt.figure()
plt.imshow(wordcloud, interpolation&＃61;"bilinear")
plt.axis("off")
plt.margins(x&＃61;0, y&＃61;0)
plt.show()输出效果如下&＃xff1a;代码5&＃xff1a;设置最大和最小字体我们可以控制wordcloud的最小和最大字体大小。为此&＃xff0c;请使用WordCloud()函数的max_font_size和min_font_size关键字参数。

# importing the necessery modulesfrom wordcloud import WordCloudimport matplotlib.pyplot as pltimport csv# file object is created
file_ob &＃61; open(r"linuxidc.com.csv")# reader object is created
reader_ob &＃61; csv.reader(file_ob)# contents of reader object is stored .# data is stored in list of list format.
reader_contents &＃61; list(reader_ob)# empty string is declare
text &＃61; ""# iterating through list of rowsfor row in reader_contents :# iterating through words in the rowfor word in row :# concatenate the words
text &＃61; text &＃43; " " &＃43; word
wordcloud &＃61; WordCloud(width&＃61;480, height&＃61;480, max_font_size&＃61;20, min_font_size&＃61;10).generate(text)
plt.figure()
plt.imshow(wordcloud, interpolation&＃61;"bilinear")
plt.axis("off")
plt.margins(x&＃61;0, y&＃61;0)
plt.show()OK&＃xff0c;暂时先这样&＃xff0c;中文乱码解决等请继续关注我们Linux公社的Python专题栏目&＃xff0c;谢谢阅读。商务合作联系&＃xff1a;root&＃64;linuxidc.net长按或扫描左图识别二维码关注Linux公社公众微信号更多Python相关信息见Python 专题页面 https://www.linuxidc.com/topicnews.aspx?tid&＃61;17
Linux公社的RSS地址&＃xff1a;https://www.linuxidc.com/rssFeed.aspx

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