-
Notifications
You must be signed in to change notification settings - Fork 0
/
Videoinfo.py
179 lines (159 loc) · 5.59 KB
/
Videoinfo.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 3 10:30:12 2020
@author: Scrachel
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from numpy.random import randn, chisquare
def read_Douyin_videoinfo(file_name):
file1 = open(file_name, 'r')
Lines = file1.readlines()
file1.close()
enter_count=0 #无用变量
#video_count=0
biaoti=[]
release_time=[]
bofang=[]
dianzan=[]
fenxiang=[]
pinglun=[]
#所有可能字符内容
probable_lines=['查看评论\n', '投放DOU+\n', '我的视频\n']
for i in range(len(Lines)):
if Lines[i] == '\n':
enter_count = enter_count + 1
# if enter_count == 2:
# video_count = video_count + 1
# enter_count = 0
elif Lines[i].find(':') > -1:
# print(i)
colon_pos = Lines[i].find(':')
line = Lines[i][colon_pos+2:]
if Lines[i].find('题') > -1:
biaoti.append(line)
# print(i,line)
elif Lines[i].find('时间') > -1:
release_time.append(pd.to_datetime(line))
elif Lines[i].find('播放') > -1:
bofang.append(int(line))
elif Lines[i].find('赞数') > -1:
dianzan.append(int(line.split('/')[0]))
elif Lines[i].find('享数') > -1:
fenxiang.append(int(line.split('/')[0]))
elif Lines[i].find('论数') > -1:
pinglun.append(int(line.split('/')[0]))
else:
print('Error.')
enter_count=0
elif Lines[i] in probable_lines:
pass
elif int(Lines[i]):
#这句尽可能放后面 也可以把这个elif分支注释掉
pass
else:
print('Error.')
print(Lines[i])
bofang_ = np.array(bofang)
dianzan_ = np.array(dianzan)
fenxiang_ = np.array(fenxiang)
pinglun_ = np.array(pinglun)
return bofang_, dianzan_, fenxiang_, pinglun_, biaoti, release_time
file_name = r'C:\\Users\Scrachel\.spyder\Video_info.txt'
bofang, dianzan, fenxiang, pinglun, biaoti, release_time = \
read_Douyin_videoinfo(file_name=file_name)
#####处理数据重复问题 假设不存在更复杂的重复性，即同一播放量只对应同一视频
bofang_0 = np.unique(bofang)
index_list = []
for i in bofang_0:
index_list.append(np.argwhere(bofang==i)[0][0])
bofang = bofang[index_list]
dianzan = dianzan[index_list]
pinglun = pinglun[index_list]
fenxiang = fenxiang[index_list]
# =============================================================================
# #####发布时间
# fig, ax = plt.subplots(figsize=(8,5))
# ax.set_xlabel('Release time', fontsize=15)
# ax.set_ylabel('Hits', fontsize=15)
# plt.yscale('log', nonposy='clip')
# ax.set_ylim(1e+4,1e+7)
# time_spread = max(release_time)-min(release_time)
# ax.set_xlim(min(release_time)-0.1*time_spread,
# max(release_time)+0.1*time_spread)
# ax.scatter(release_time, bofang)
# fig.tight_layout()
# =============================================================================
# =============================================================================
# #####评论量
# fig, ax = plt.subplots(figsize=(8,5))
# ax.set_ylabel('Comments', fontsize=15)
# ax.set_xlabel('Hits', fontsize=15)
# plt.yscale('log', nonposy='clip')
# plt.xscale('log')
# ax.set_xlim(1e+4,1e+7)
# ax.set_ylim(10,3500)
# ax.scatter(bofang, pinglun)
# fig.tight_layout()
# #plt.show()
# fig.savefig('pinglun_bofang.png', dpi=500)
# =============================================================================
######点赞量
#fig, ax = plt.subplots(figsize=(8,5))
#ax.set_ylabel('DianZan', fontsize=15)
#ax.set_xlabel('Hits', fontsize=15)
#plt.yscale('log', nonposy='clip')
#plt.xscale('log')
#ax.set_xlim(1e+4,1e+7)
#ax.set_ylim(500,1.5e5)
#ax.scatter(bofang, dianzan)
#fig.tight_layout()
##plt.show()
#fig.savefig('dianzan_bofang.png', dpi=500)
#
######点赞率
#condi=np.where(bofang>1e+4)
##plt.yscale('log', nonposy='clip')
#plt.xscale('log')
#ax.set_xlim(1e+4,1e+7)
#ax.set_ylim(0,0.05)
#ax.scatter(bofang[condi], dianzan[condi]*1.0/bofang[condi])
#fig.tight_layout()
#plt.show()
# =============================================================================
# #####分享量
# fig, ax = plt.subplots(figsize=(8,5))
# ax.set_ylabel('Sharing', fontsize=15)
# ax.set_xlabel('Hits', fontsize=15)
# plt.yscale('log', nonposy='clip')
# plt.xscale('log')
# ax.set_xlim(1e+4,1e+7)
# ax.set_ylim(10,2500)
# ax.scatter(bofang, fenxiang)
# fig.tight_layout()
# #plt.show()
# fig.savefig('fenxiang_bofang.png', dpi=500)
# =============================================================================
#desensitization
def random_modi(size):
x = randn(size)
range_y = np.exp2(0.3 * x**3 + np.sqrt(abs(x)))
range_y[np.where(range_y>1.3)] = 0.23 * \
chisquare(13,np.where(range_y>1.3)[0].size)
factor_y = range_y / 3.0 * randn(size) * 0.1
return(factor_y)
y = (random_modi(np.size(bofang)) * dianzan + dianzan) // 1
x = (random_modi(np.size(bofang)) * bofang + bofang) // 1
fig, ax = plt.subplots(figsize=(8,5))
ax.set_ylabel('DianZan', fontsize=15)
ax.set_xlabel('Hits', fontsize=15)
plt.yscale('log', nonposy='clip')
plt.xscale('log')
ax.set_xlim(1e+4,1e+7)
#ax.set_ylim(5,1.5e5)
ax.set_ylim(500,1.5e5)
ax.scatter(x, y)
fig.tight_layout()
#plt.show()
fig.savefig('dianzan_bofang_0.png', dpi=100)