python编程：提取word、pdf、excel信息的动词与名词，制作词云图

工具类参数：
text：数据
mode：word文档选 选word
excel或者pdf选 mode=‘pdf’

import os
import re
import jieba.posseg as jpg
from wordcloud import WordCloud
from matplotlib import pyplot as plt
import imageio
import pandas as pd
import xlrd
import xlwt
import shutil


class Util:

    def __init__(self, text, mode, file_name):
        # self.pdf_text = pdf_text
        self.mode = mode
        self.text = text
        self.file_name = file_name

    # 划分词性
    def cut(self, content):
        if not os.path.exists(self.file_name):  # 判断是否存在文件夹如果不存在则创建为文件夹
            a = os.makedirs(self.file_name)
            print(a)

        # os.mkdir(self.file_name)
        n = []
        v = []
        for x in content:
            if x.flag == 'v':
                p = re.split('/', str(x))
                v.append(p[0])
            if x.flag == 'n':
                p1 = re.split('/', str(x))
                n.append(p1[0])
        noun = ' '.join(n)
        verb = ' '.join(v)

        return noun, verb

    def tiqu_word(self):
        content = ""
        if self.text != '':
            for i in self.text:
                content += i
            # content = re.findall(r'四(.*?)五', content)
            content = jpg.cut(str(content))
            noun, verb = self.cut(content)
            print(noun, '\n', verb)
            return noun, verb
        else:
            print("传入数据==null")
            return 0

    def tiqu_pdf(self):

        if self.text != '':
            # content = re.findall(r'四(.*?)五', pdf_text)
            content = jpg.cut(str(text))
            noun, verb = self.cut(content)
            print(noun, '\n', verb)
            return noun, verb
        else:
            print("传入数据==null")
            return 0

    # 词云图
    def draw(self):
        image = imageio.imread('demo1.jpeg')

        def generate_wordcloud(text, sign):

            wordcloud1 = WordCloud(background_color='white', font_path='ArialUnicode.ttf', mask=image,
                                   width=800, height=600).generate(text)

            mage_1 = wordcloud1.to_image()
            wordcloud1.to_file(self.file_name + sign + '.png')
            shutil.move(self.file_name + sign + '.png', self.file_name + '/' + self.file_name + sign + '.png')
            # image1.save('/Users/hanze/Desktop/未命名文件夹/1a.png')
            # plt.axis('off')
            # plt.imshow(wordcloud)
            # plt.show()

        if self.mode == 'word':
            noun, verb = self.tiqu_word()
            generate_wordcloud(noun, 'n')
            generate_wordcloud(verb, 'v')

        if self.mode == 'pdf':
            noun, verb = self.tiqu_pdf()
            generate_wordcloud(noun, 'n')
            generate_wordcloud(verb, 'v')

    # vocabulary txt
    def write_vocabtxt(self):
        # path = '/Users/hanze/cloud'
        if self.mode == 'word':
            noun, verb = self.tiqu_word()
            # new_name = os.path.join(self.file_name)
            f = open(self.file_name + '_n.txt', 'w')
            f.write(noun)
            f.close()
            f1 = open(self.file_name + '_v.txt', 'w')
            f1.write(verb)
            f1.close()
            shutil.move(self.file_name + '_n.txt', self.file_name + '/' + self.file_name + '_n.txt')
            shutil.move(self.file_name + '_v.txt', self.file_name + '/' + self.file_name + '_v.txt')

        if self.mode == 'pdf':
            noun, verb = self.tiqu_pdf()
            # new_name = os.path.join(path, self.file_name)
            f = open(self.file_name + '_n.txt', 'w')
            f.write(noun)
            f.close()
            f1 = open(self.file_name + '_v.txt', 'w')
            f1.write(verb)
            f1.close()
            shutil.move(self.file_name + '_n.txt', self.file_name + '/' + self.file_name + '_n.txt')
            shutil.move(self.file_name + '_v.txt', self.file_name + '/' + self.file_name + '_v.txt')


if __name__ == '__main__':

    text = pd.read_excel('firstData_T.xls')
    content = []
    grade = ['0', '1']
    temp_content = ['', '']
    total_content = []
    for i in text.values:

        temp_list = [i[0], i[1]]
        content.append(temp_list)
		提取前两位数字
        temp_grade = re.findall('([0-9])', i[0])
		汇总每个学院数据
        if grade[0] == temp_grade[0] and temp_grade[1] == grade[1]:
            # print(temp_grade[0:2],grade[0:2])
            temp_content[0] = i[0][0:3] + 'total'
            # print(temp_content[0])
            temp_content[1] += i[1]
            # print(temp_content[0], len(temp_content[1]))

            # print(total_content[0], len(total_content[1]))
        if grade[0] != temp_grade[0] or temp_grade[1] != grade[1]:
            total_content.append([temp_content[0], temp_content[1]])
            # print(temp_content[0])

            # print('----下一个学院-----')
            grade = temp_grade
            temp_content[0] = ''
            temp_content[1] = ''
    total_content.append([temp_content[0], temp_content[1]])
    # print(temp_content)
    #
    for i in total_content:
        print(i[0], len(i[1]))
    # print(len(total_content))

    total_content += content
    for i in total_content:
        print(i[0], len(i[1]))
        print(len(total_content))
        print(len(content))

    for i in total_content:
        Util(i[1], 'pdf', i[0]).draw()
        Util(i[1], 'pdf', i[0]).write_vocabtxt()