詞雲wordcloud

直接pip總是會報錯，基本放棄了，還是乖乖下載下傳wheel檔案吧

一個超好用的網站，所有的wheel檔案都可以找到

https://pypi.org/

wordcloud    詞雲必須要有的包

用法：

必須有一個字元串，也可以讀取一個檔案

from wordcloud import WordCloud

file2 = open('../test.txt', encoding='utf-8').read()

wordcloud = WordCloud(font_path='C:\Windows\Fonts/FZSTK.TTF', background_color="white", height=20000, width=20000).generate(file2)

wordcloud.to_file('test.png')
           

參數說明：

font_path：字型路徑（中文必須要有，否則全是方框），height：圖檔高度，width：圖檔寬度，generate的參數為要生成詞雲的文章

隻要這四行就可以生成一個矩形的詞雲

如果想生成指定圖形的詞雲，隻需要再導入PIL包和numpy包即可

如果是Python3，在上邊那個網站找pillow，安裝之後用法和PIL一樣

from PIL import Image

import numpy as np
           

打開一張圖檔，并将其轉換成數組

img = Image.open('巴黎聖母院.jpg')

img_array = np.array(img)
           

然後在WordCloud的構造方法中加上 mask參數，值為由圖檔轉換成的數組

wordcloud = WordCloud(font_path='C:\Windows\Fonts/FZSTK.TTF', background_color="white", height=20000, width=20000, mask=img_array).generate(file2)
           

全部代碼為

#coding = utf-8

from wordcloud import WordCloud

from matplotlib import pyplot as plt

from PIL import Image

import numpy as np

string = "Importance of relative word frequencies for font-size. With relative_scaling=0, only word-ranks are considered. With relative_scaling=1, a word that is twice as frequent will have twice the size. If you want to consider the word frequencies and not only their rank, relative_scaling around .5 often looks good."





file1 = open('../files/test.txt', encoding='utf-8').read()

file2 = open('../test.txt', encoding='utf-8').read()





img = Image.open('巴黎聖母院.jpg')

img_array = np.array(img)

"""font_path：字型路徑（中文必須要有，否則全是方框），height：圖檔高度，width：圖檔寬度，mask：背景圖檔數組，generate的參數為要生成詞雲的文章"""

wordcloud = WordCloud(font_path='C:\Windows\Fonts/FZSTK.TTF', background_color="white", height=2000, width=2000, mask=img_array).generate(file2)

"""将生成的詞雲儲存成圖檔"""

wordcloud.to_file('test.png')

"""plt可以不用"""

plt.imshow(wordcloud)

plt.show()