原标题：就这么简单！使用Python生成漂亮的词云
作者：Linux迷
链接：
词云是一种数据可视化技术，用于表示文本数据，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，需要的模块是– matplotlib，pandas和wordcloud。要安装这些软件包，请运行以下命令：
pip install matplotlib
pip install pandas
pip install wordcloud
代码1：字数
可以设置要在tagcloud上显示的最大单词数。为此，请使用WordCloud函数的max_words关键字参数。
# importing the necessery modules
fromwordcloud importWordCloud
importmatplotlib.pyplot asplt
importcsv
# file object is created
file_ob = open( r".csv")
# reader object is created
reader_ob = csv.reader(file_ob)
# contents of reader object is stored .
# data is stored in list of list format.
reader_contents = list(reader_ob)
# empty string is declare
text = ""
# iterating through list of rows
forrow inreader_contents :
# iterating through words in the row
forword inrow :
# concatenate the words
text = text + " "+ word
# show only 50 words in the wordcloud .
wordcloud = WordCloud(width= 480, height= 480, max_words= 50).generate(text)
# plot the WordCloud image
plt.figure
plt.imshow(wordcloud, interpolation= "bilinear")
plt.axis( "off")
plt.margins(x= 0, y= 0)
plt.show
输出如下图：
代码2：删除一些单词
可以删除一些我们不想显示的词。为此，请将这些单词传递给WordCloud函数的停用词列表参数。
# importing the necessery modules
fromwordcloud importWordCloud
importmatplotlib.pyplot asplt
importcsv
# file object is created
file_ob = open( r".csv")
# reader object is created
reader_ob = csv.reader(file_ob)
# contents of reader object is stored .
# data is stored in list of list format.
reader_contents = list(reader_ob)
# empty string is declare
text = ""
# iterating through list of rows
forrow inreader_contents :
# iterating through words in the row
forword inrow :
# concatenate the words
text = text + " "+ word
# remove Python , Matplotlib , Color Words from WordCloud .
wordcloud = WordCloud(width= 480, height= 480,
stopwords=[ "Python", "Matplotlib", "Color"]).generate(text)
# plot the WordCloud image
plt.figure
plt.imshow(wordcloud, interpolation= "bilinear")
plt.axis( "off")
plt.margins(x= 0, y= 0)
plt.show
输出效果如下：
代码3：更改背景
我们可以更改wordcloud背景的颜色。为此，请使用WordCloud函数的background_color关键字参数。
# importing the necessery modules
fromwordcloud importWordCloud
importmatplotlib.pyplot asplt
importcsv
# file object is created
file_ob = open( r".csv")
# reader object is created
reader_ob = csv.reader(file_ob)
# contents of reader object is stored .
# data is stored in list of list format.
reader_contents = list(reader_ob)
# empty string is declare
text = ""
# iterating through list of rows
forrow inreader_contents :
# iterating through words in the row
forword inrow :
# concatenate the words
text = text + " "+ word
wordcloud = WordCloud(width= 480, height= 480, background_color= "pink").generate(text)
# plot the WordCloud image
plt.figure
plt.imshow(wordcloud, interpolation= "bilinear")
plt.axis( "off")
plt.margins(x= 0, y= 0)
plt.show
输出效果如下：
代码4：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 modules
fromwordcloud importWordCloud
importmatplotlib.pyplot asplt
importcsv
# file object is created
file_ob = open( r".csv")
# reader object is created
reader_ob = csv.reader(file_ob)
# contents of reader object is stored .
# data is stored in list of list format.
reader_contents = list(reader_ob)
# empty string is declare
text = ""
# iterating through list of rows
forrow inreader_contents :
# iterating through words in the row
forword inrow :
# concatenate the words
text = text + " "+ word
wordcloud = WordCloud(width= 480, height= 480, colormap= "Oranges_r").generate(text)
# plot the WordCloud image
plt.figure
plt.imshow(wordcloud, interpolation= "bilinear")
plt.axis( "off")
plt.margins(x= 0, y= 0)
plt.show
输出效果如下：
代码5：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，请使用WordCloud函数的max_font_size和min_font_size关键字参数。
# importing the necessery modules
fromwordcloud importWordCloud
importmatplotlib.pyplot asplt
importcsv
# file object is created
file_ob = open( r".csv")
# reader object is created
reader_ob = csv.reader(file_ob)
# contents of reader object is stored .
# data is stored in list of list format.
reader_contents = list(reader_ob)
# empty string is declare
text = ""
# iterating through list of rows
forrow inreader_contents :
# iterating through words in the row
forword inrow :
# concatenate the words
text = text + " "+ word
wordcloud = WordCloud(width= 480, height= 480, max_font_size= 20, min_font_size= 10).generate(text)
plt.figure
plt.imshow(wordcloud, interpolation= "bilinear")
plt.axis( "off")
plt.margins(x= 0, y= 0)
plt.show
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