Python制作关键字云+情感分析图

1、关键字云：

首先导入的需要的包：

import matplotlib.pyplot as plt
from wordcloud import WordCloud
import jieba

创建一个方法生成关键字云：

def createWordcloud(path):
    # 打开content.txt文件，并将编码设为utf-8
f = open(path, r, encoding=utf-8).read()
# jieba分词
    cut_text = .join(jieba.cut(f))
wc= WordCloud(
		# 设置字体
        font_path=C://Windows//Fonts//msyh.ttc,
		# 设置背景
        background_color="white", width=3000, height=2500).generate(cut_text)
plt.imshow(wc, interpolation=bilinear)
plt.axis("off")
plt.show()
wc.to_file(你的保存路径//1.jpg)

在main方法中对参数传值：

if __name__ == __main__:
    # 要读取的文件
    path_txt = 你的文件路径//content.txt
    createWordcloud(path_txt)

结果：

2、情感分析：

首先导入需要的包：

import matplotlib.pyplot as plt
from snownlp import SnowNLP
import pandas as pd

创建一个方法生成情感分析图，并在main方法中对参数传值：

import matplotlib.pyplot as plt
from snownlp import SnowNLP
import pandas as pd

def createSnowNLO(path):
    txt = open(path, r, encoding=UTF-8)
    text = txt.readlines()
txt.close()
print(读入成功)
    sentences = []
    senti_score = []
for i in text:
	a1 = SnowNLP(i)
	a2= a1.sentiments
	sentences.append(i) 
#语序...
senti_score.append(a2)
table = pd.DataFrame(sentences, senti_score)
plt.plot(senti_score, linestyle=-)
plt.show()
if __name__ == __main__:
    path_txt = r你的文件路径content.txt
    createSnowNLO(path_txt)

结果：