python使用jieba进行中文分词wordcloud制作词云

准备工作

抓取数据存到txt文档中，了解jieba

问题

• jieba分词分的不太准确，比如机器学习会被切成机器和学习两个词，使用自定义词典，原本的想法是只切出自定义词典里的词，但实际上不行，所以首先根据jieba分词结果提取出高频词并自行添加部分词作为词典，切词完毕只统计自定义词典里出现过的词
• wordcloud自身不支持中文词云，需要指定中文字体，并且现在大部分的博客提供的generate_from_frequencies方法的参数与现在的wordcloud的参数不同，现在这个方法接收的是dict类型

代码

# -*- coding: utf-8 -*-
import jieba
import os
import codecs
from scipy.misc import imread
import matplotlib as mpl 
import matplotlib.pyplot as plt 
from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator

class GetWords(object):
    def __init__(self, dict_name, file_list , dic_list):
        self.dict_name = dict_name
        self.file_list = file_list
        self.dic_list = dic_list
    #获取自定义词典
    def get_dic(self):  
        dic = open(self.dict_name, 'r')
        while 1:
            line = dic.readline().decode('utf-8').strip()
            self.dic_list.append(line)
            if not line:
                break
            pass
            
    def get_word_to_cloud(self):
        for file in self.file_list:
            with codecs.open('../spider/' + file, "r",encoding='utf-8', errors='ignore') as string:
                string = string.read().upper()
                res = jieba.cut(string, HMM=False)
                reslist = list(res)
                wordDict = {}
                for i in reslist:
                    if i not in self.dic_list:
                        continue
                    if i in wordDict:
                        wordDict[i]=wordDict[i]+1
                    else:
                        wordDict[i] = 1

            coloring = imread('test.jpeg')

            wc = WordCloud(font_path='msyh.ttf',mask=coloring,
                    background_color="white", max_words=50,
                    max_font_size=40, random_state=42)

            wc.generate_from_frequencies(wordDict)

            wc.to_file("%s.png"%(file))

def set_dic():
    _curpath=os.path.normpath( os.path.join( os.getcwd(), os.path.dirname(__file__) ))
    settings_path = os.environ.get('dict.txt')
    if settings_path and os.path.exists(settings_path):
        jieba.set_dictionary(settings_path)
    elif os.path.exists(os.path.join(_curpath, 'data/dict.txt.big')):
        jieba.set_dictionary('data/dict.txt.big')
    else:
        print "Using traditional dictionary!"
 
if __name__ == '__main__':
    set_dic()
    file_list = ['data_visualize.txt', 'data_dev.txt', 'data_mining.txt', 'data_arc.txt', 'data_analysis.txt']
    dic_name = 'dict.txt'
    dic_list = []
    getwords = GetWords(dic_name, file_list, dic_list)
    getwords.get_dic()
    getwords.get_word_to_cloud()

词云示例

此图为爬取拉勾网数据挖掘工程师岗位需要制作的词云

源码

github