jieba库以及词云

程序如下：

import os
import codecs
import jieba
import pandas as pd
from wordcloud import WordCloud
from scipy.misc import imread
import matplotlib.pyplot as plt
os.chdir("/Users/Zhaohaibo/Desktop")

class Hlm(object): 
    # 字频前100，并写入writedoc
    # —————————————————————
    def Zipin(self, readdoc, writedoc):
        word_lst = []
        word_dict = {}       
        exclude_str = "，。！？、（）【】<>《》=：+-*—“”…" 
        with open(readdoc,"r") as fileIn ,open(writedoc,'w') as fileOut:

            # 添加每一个字到列表中
            for line in fileIn:
                for char in line:
                    word_lst.append(char)

            # 用字典统计每个字出现的个数       
            for char in word_lst:
                if char not in exclude_str:
                    if char.strip() not in word_dict: # strip去除各种空白
                        word_dict[char] = 1
                    else :
                        word_dict[char] += 1

            # 排序x[1]是按字频排序，x[0]则是按字排序
            lstWords = sorted(word_dict.items(), key=lambda x:x[1],  reverse=True) 

            # 输出结果 (前100)
            print ('字符\t字频')
            print ('=============')
            for e in lstWords[:100]:
                print ('%s\t%d' % e)
                fileOut.write('%s, %d\n' % e)
    # 词频表（DataFrame格式）
    # —————————————————————
    def Cipin(self, doc):
        wdict = {}
        f = open(doc,"r")
        for line in f.readlines():
            words = jieba.cut(line)
            for w in words:
                if(w not in wdict):
                    wdict[w] = 1
                else:
                    wdict[w] += 1                
        # 导入停用词表
        stop = pd.read_csv('stoplist.txt', encoding = 'utf-8', sep = 'zhao', header = None,engine = 'python') #sep:分割符号（需要用一个确定不会出现在停用词表中的单词）
        stop.columns = ['word']    
        stop = [' '] + list(stop.word) #python读取时不会读取到空格。但空格依旧需要去除。所以加上空格； 读取后的stop是series的结构，需要转成列表
        for i in range(len(stop)):
            if(stop[i] in wdict):
                wdict.pop(stop[i])

        ind = list(wdict.keys())
        val = list(wdict.values())
        ind = pd.Series(ind)
        val = pd.Series(val)
        data =  pd.DataFrame()
        data['词'] = ind
        data['词频'] = val
        return data
    # 词云图
    # —————————————————————
    def Ciyun(self,doc):
        g = open(doc,"r").read()
        back_pic = imread("aixin.jpg")  # 设置背景图片  
        wc = WordCloud( font_path='/System/Library/Fonts/STHeiti Medium.ttc',#设置字体  
                          background_color="white", #背景颜色  
                          max_words=2000,# 词云显示的最大词数  
                          mask=back_pic,#设置背景图片  
                          max_font_size=200, #字体最大值  
                          random_state=42,  
                         ).generate(g)   
        plt.figure(figsize=(64,32))
        plt.imshow(wc)
        plt.axis('off')
        plt.savefig("ciyun.jpg")
        plt.show()


    def main(self,readdoc):
        # self.Zipin(readdoc,writedoc)
        df = self.Cipin(readdoc)
        #self.Ciyun(readdoc)
        return df


if __name__ == '__main__':
    hlm = Hlm()
    hlm.Zipin("红楼梦.txt","红楼梦字频.txt")
    df_hlm1 = hlm.main("红楼梦.txt")

　　

　

效果图如下：