python中文分词，生成标签云，生成指定形状图片标签云

亦凉 2022-07-12 05:28 283阅读 0赞

使用结巴分词  
[https://github.com/fxsjy/jieba][https_github.com_fxsjy_jieba]

可以直接pip 安装

pip install jieba

![这里写图片描述][SouthEast]

主要看到这么一篇文章

[https://zhuanlan.zhihu.com/p/20432734?columnSlug=666666][https_zhuanlan.zhihu.com_p_20432734_columnSlug_666666]

参考，测试我写的一个学习计划分析其关键词并给出权重

# -*- coding: UTF-8 -*-
    import jieba.analyse
    with open('ci.txt','r') as f:
        seg_list =jieba.analyse.extract_tags(f.read(), topK=20, withWeight=True, allowPOS=())
    
    for tag in seg_list:
            print("tag: %s\t\t weight: %f" % (tag[0],tag[1]))

![这里写图片描述][SouthEast 1]

基于 TF-IDF 算法的关键词抽取
    
    import jieba.analyse
    
    jieba.analyse.extract_tags(sentence, topK=20, withWeight=False, allowPOS=())
    sentence 为待提取的文本
    topK 为返回几个 TF/IDF 权重最大的关键词，默认值为 20
    withWeight 为是否一并返回关键词权重值，默认值为 False
    allowPOS 仅包括指定词性的词，默认值为空，即不筛选
    jieba.analyse.TFIDF(idf_path=None) 新建 TFIDF 实例，idf_path 为 IDF 频率文件

还可以自定义字典，有一些提取不好的可以改下。  
还有等等很多功能，需要的时候在学习。先了解下。  
[https://github.com/fxsjy/jieba][https_github.com_fxsjy_jieba]

然后将其生成标签云

# -*- coding: utf-8 -*-
    import codecs
    import random
    from pytagcloud import create_tag_image, create_html_data, make_tags, \
        LAYOUT_HORIZONTAL, LAYOUTS
    from pytagcloud.colors import COLOR_SCHEMES
    from pytagcloud.lang.counter import get_tag_counts
    
    wd = {}
    
    fp=codecs.open("rsa.txt", "r",'utf-8');
    
    alllines=fp.readlines();
    fp.close();
    
    for eachline in alllines:
        line = eachline.split(' ')
        #print eachline,
        wd[line[0]] = int(line[1])
    
    from operator import itemgetter
    swd = sorted(wd.iteritems(), key=itemgetter(1), reverse=True)
    tags = make_tags(swd,minsize = 50, maxsize = 240,colors=random.choice(COLOR_SCHEMES.values()))
    create_tag_image(tags, 'yun.png', background=(0, 0, 0, 255),
    size=(2400, 1000),layout=LAYOUT_HORIZONTAL,
    fontname="SimHei")

参考后

# -*- coding: utf-8 -*-
    import codecs
    import random
    from pytagcloud import create_tag_image, create_html_data, make_tags, \
        LAYOUT_HORIZONTAL, LAYOUTS
    from pytagcloud.colors import COLOR_SCHEMES
    from pytagcloud.lang.counter import get_tag_counts
    import jieba.analyse
    with open('ci.txt','r') as f:
        seg_list =jieba.analyse.extract_tags(f.read(), topK=20, withWeight=True, allowPOS=())
    wd={}
    for tag in seg_list:
            wd[tag[0]] = float(tag[1])
    from operator import itemgetter
    swd = sorted(wd.iteritems(), key=itemgetter(1), reverse=True)
    tags = make_tags(swd,minsize = 50, maxsize = 240,colors=random.choice(COLOR_SCHEMES.values()))
    create_tag_image(tags, 'yun.png', background=(0, 0, 0, 255),
    size=(2400, 1000),layout=LAYOUT_HORIZONTAL,
    fontname="SimHei")

输出

![这里写图片描述][SouthEast 2]

恩，像我参考的大佬说的那样，都是写入门基本的东西，我学习也是因为有趣。

还有一些标签云的解析参考  
[https://zhuanlan.zhihu.com/p/20436581?refer=666666][https_zhuanlan.zhihu.com_p_20436581_refer_666666]

然后继续学习，指定图片覆盖生成图片里的形状的标签云。  
就用的文章讲的图片学习。  
参考  
[https://zhuanlan.zhihu.com/p/20436642][https_zhuanlan.zhihu.com_p_20436642]  
使用的 是 wordcloud  
传入的是数组

作者：段小草
    链接：https://zhuanlan.zhihu.com/p/20436642
    来源：知乎
    著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。
    
     -*- coding: utf-8 -*-
    """ Minimal Example =============== Generating a square wordcloud from the US constitution using default arguments. """
    
    from os import path
    from wordcloud import WordCloud
    
    d = path.dirname(__file__)
    
    # Read the whole text.
     此处原为处理英文文本，我们修改为传入中文数组
    #text = open(path.join(d, 'constitution.txt')).read()
    frequencies = [(u'知乎',5),(u'小段同学',4),(u'曲小花',3),(u'中文分词',2),(u'样例',1)]
    
    # Generate a word cloud image 此处原为 text 方法，我们改用 frequencies 
    #wordcloud = WordCloud().generate(text)
    wordcloud = WordCloud().fit_words(frequencies)
    
    # Display the generated image:
    # the matplotlib way:
    import matplotlib.pyplot as plt
    plt.imshow(wordcloud)
    plt.axis("off")
    
    # take relative word frequencies into account, lower max_font_size
    #wordcloud = WordCloud(max_font_size=40, relative_scaling=.5).generate(text)
    wordcloud = WordCloud(max_font_size=40, relative_scaling=.5).fit_words(frequencies)
    plt.figure()
    plt.imshow(wordcloud)
    plt.axis("off")
    plt.show()
    
    # The pil way (if you don't have matplotlib)
    #image = wordcloud.to_image()
    #image.show()

import numpy as np
    from PIL import Image
    from os import path
    import matplotlib.pyplot as plt
    import random
    
    from wordcloud import WordCloud, STOPWORDS
    
    
    def grey_color_func(word, font_size, position, orientation, random_state=None, **kwargs):
        return "hsl(0, 0%%, %d%%)" % random.randint(60, 100)
    
    d = path.dirname(__file__)
    
    # read the mask image
    # taken from
    # http://www.stencilry.org/stencils/movies/star%20wars/storm-trooper.gif
    mask = np.array(Image.open(path.join(d, "yun4.jpg")))
    
    # movie script of "a new hope"
    # http://www.imsdb.com/scripts/Star-Wars-A-New-Hope.html
    # May the lawyers deem this fair use.
    text = open("re.txt").read()
    
    # preprocessing the text a little bit
    text = text.replace("HAN", "Han")
    text = text.replace("LUKE'S", "Luke")
    
    # adding movie script specific stopwords
    stopwords = STOPWORDS.copy()
    stopwords.add("int")
    stopwords.add("ext")
    
    wc = WordCloud(max_words=1000, mask=mask, stopwords=stopwords, margin=10,
                   random_state=1).generate(text)
    # store default colored image
    default_colors = wc.to_array()
    plt.title("Custom colors")
    plt.imshow(wc.recolor(color_func=grey_color_func, random_state=3))
    wc.to_file("a_new_hope.png")
    plt.axis("off")
    plt.figure()
    plt.title("Default colors")
    plt.imshow(default_colors)
    plt.axis("off")
    plt.show()

生成图片

![这里写图片描述][SouthEast 3]

就是跟着文章学习然后做的。我想学习也是一点一点来的把。不过缺少了很多创新。等下次有机会用到结合实际需求碰撞出更好的东西把。

主要还是中文分词。记录下。方便以后用到。

[https_github.com_fxsjy_jieba]: https://github.com/fxsjy/jieba
[SouthEast]: /images/20220711/e4ab563e3d144b91b143979f6f5490ff.png
[https_zhuanlan.zhihu.com_p_20432734_columnSlug_666666]: https://zhuanlan.zhihu.com/p/20432734?columnSlug=666666
[SouthEast 1]: /images/20220711/7b1a170b8db84855824620e78145dfcc.png
[SouthEast 2]: /images/20220711/a25ab9b1f1124dae9d5fa9e2b11cc1d2.png
[https_zhuanlan.zhihu.com_p_20436581_refer_666666]: https://zhuanlan.zhihu.com/p/20436581?refer=666666
[https_zhuanlan.zhihu.com_p_20436642]: https://zhuanlan.zhihu.com/p/20436642
[SouthEast 3]: /images/20220711/5eb1871061be44c0aa97e1d0dbf2a510.png