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DataAnalysis.py
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DataAnalysis.py
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#!/usr/bin/python3.7
# -*- coding: utf-8 -*-
# @Time : 2019/11/30 下午 10:25
# @Email : [email protected]
# @Github : github.com/laishouchao
# @File : DataAnalysis.py
# @Software: PyCharm
from snownlp import SnowNLP
import visualization
class dataAnalysis:
def __init__(self):
# 初始化数组
self.temp0 = []
self.temp1 = []
self.temp2 = []
self.temp3 = []
self.temp4 = []
self.temp5 = []
self.temp6 = []
self.temp7 = []
self.temp8 = []
self.temp9 = []
def DataAnalysis(self, keywords):
# 情感分析，通过更换微博预料训练生成的.model.3模型可提高分析的精确度
Affective_value = SnowNLP(keywords)
# 计算消息的正负面情绪值，并写入Getvalue.xlsx中
Affective_value_good = Affective_value.sentiments
Affective_value_bad = 1 - Affective_value_good
List = [keywords, Affective_value_good, Affective_value_bad]
print(List[0], List[1], List[2]) # 输出事件及对应的情感值
# 对情感归类统计
if Affective_value.sentiments < 0.1:
self.temp0.append(keywords)
elif Affective_value_good < 0.2:
self.temp1.append(keywords)
elif Affective_value_good < 0.3:
self.temp2.append(keywords)
elif Affective_value_good < 0.4:
self.temp3.append(keywords)
elif Affective_value_good < 0.5:
self.temp4.append(keywords)
elif Affective_value_good < 0.6:
self.temp5.append(keywords)
elif Affective_value_good < 0.7:
self.temp6.append(keywords)
elif Affective_value_good < 0.8:
self.temp7.append(keywords)
elif Affective_value_good < 0.9:
self.temp8.append(keywords)
elif Affective_value_good >= 0.9:
self.temp9.append(keywords)
else:
return "err"
return List
def Statistics(self):
# elif endmark == "1":
# # final = []
# # final.append(temp0)
# # final.append(temp1)
# # final.append(temp2)
# # final.append(temp3)
# # final.append(temp4)
# # final.append(temp5)
# # final.append(temp6)
# # final.append(temp7)
# # final.append(temp8)
# # final.append(temp9)
# # # print(final)
# # list_len = [len(final[0]), len(final[1]), len(final[2]), len(final[3]), len(final[4]), len(final[5]),
# # len(final[6]),
# # len(final[7]), len(final[8]), len(final[9])]
list_len = [len(self.temp0), len(self.temp1), len(self.temp2), len(self.temp3), len(self.temp4),
len(self.temp5),
len(self.temp6), len(self.temp7), len(self.temp8), len(self.temp9)]
# print(list_len)
return list_len