-
Notifications
You must be signed in to change notification settings - Fork 37
/
Copy pathtest.py
201 lines (193 loc) · 6.16 KB
/
test.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
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
# # from threading import Timer
# import time
#
# #
# #
# # def hello():
# # print("hello, world")
# #
# #
# # class RepeatingTimer(Timer):
# # def run(self):
# # while not self.finished.is_set():
# # self.function(*self.args, **self.kwargs)
# # self.finished.wait(self.interval)
# #
# #
# # t = RepeatingTimer(10.0, hello)
# # t.start()
# # import datetime
# #
# # today = datetime.date.today()
# # print(today)
#
#
# # ts = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
#
#
# # ts = str(time.time()).split(".")[0]
# # print(ts)
#
# # encoding: utf-8
# import requests
# import json
# from pyecharts.charts import Pie
# from pyecharts import options as opts
# from pyecharts.charts import Radar
#
#
# # 获取官网英雄数据
# def request(url):
# headers = {
# "User-Agent": "Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; InfoPath.3)", }
# res = requests.get(url, headers=headers)
# return res
#
#
# def data_analysis(title, data):
# res = {}
# for hero in data:
# if hero['%s' % title] not in res:
# res[hero['%s' % title]] = hero['name']
# else:
# res[hero['%s' % title]] = res[hero['%s' % title]] + "," + hero['name']
# print(res)
# return res
#
#
# def draw_pie(title, attack):
# columns, data = [], []
# for k, v in attack.items():
# columns.append(title + k + '级')
# data.append(len(v.split(',')))
# if k in ['1', '10']:
# print(k, v)
# pie = (
# Pie()
# # 以[(lable,value),(lable,value),(lable,value)......]形式传入数据。
# .add(title, list(z for z in zip(columns, data)))
# .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
# )
# pie.render('%s.html' % title)
#
#
# def draw_Radar():
# from pyecharts.charts import Radar
# radar = Radar()
# # //由于雷达图传入的数据得为多维数据，所以这里需要做一下处理
# radar_data = [[10, 10, 10, 10, 10]]
# radar_data1 = [[2, 10, 3, 6, 3]]
# radar_data2 = [[1, 8, 7, 5, 8]]
#
# # //设置column的最大值，为了雷达图更为直观，这里的月份最大值设置有所不同
# schema = [
# ("物理", 100), ("魔法", 10), ("防御", 10), ("难度", 10), ("喜好", 10)
# ]
# # //传入坐标
# radar.add_schema(schema)
# radar.add("满分", radar_data)
# # //一般默认为同一种颜色，这里为了便于区分，需要设置item的颜色
# radar.add("安妮", radar_data1, color="#E37911")
# radar.add("卡尔玛", radar_data2, color="#1C86EE")
# radar.render()
#
#
# if __name__ == '__main__':
# url = "https://game.gtimg.cn/images/lol/act/img/js/heroList/hero_list.js"
# res = request(url)
# hero_message = json.loads(res.text)['hero']
# # print(hero_message)
#
# # 物理
# attack = data_analysis('attack', hero_message)
# draw_pie('物理', attack)
#
# # 防御
# defense = data_analysis('defense', hero_message)
# draw_pie('防御', defense)
#
# # 魔法
# magic = data_analysis('magic', hero_message)
# draw_pie('魔法', magic)
#
# # 难度
# difficulty = data_analysis('difficulty', hero_message)
# draw_pie('难度', difficulty)
#
# draw_Radar()
#
# print(8 >> 2)
# import json
#
# a = [{'a': 3, 'b': 4, 'c': '5'}]
# a = str(a).replace("]", "").replace("[", '')
# a = json.dumps(a)
# print(a)
# print(type(a))
# from openpyxl import Workbook
# import pandas as pd
#
# wb = Workbook()
# ws = wb.active
# ws.append([
# "粉丝数"
# ])
# if __name__ == '__main__':
# df = pd.read_excel(r"C:\python_project\dts-auto-brief\data\mweibo\展新时刻_微博_210925_211004_13851.xlsx")
# fans = df['粉丝数']
# for fan in fans:
# if "万" in str(fan):
# n_fans = fan.replace("万", "")
# l_fans = float(n_fans) * 10000
# ws.append([int(l_fans)])
# else:
# ws.append([int(fan)])
# wb.save(r"C:\python_project\dts-auto-brief\data\mweibo\fans.xlsx")
import pandas as pd
from pyecharts.charts import Pie, Bar, Line, WordCloud
from pyecharts.render import make_snapshot
from snapshot_selenium import snapshot
from pyecharts import options as opts
# bar = Bar()
# bar.add_xaxis(["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月"])
#
# bar.add_yaxis('自动化工单统计', ['755', '664', '1082', '692', '729', '941', '1131', '2022', '831', '760', '371'])
# # bar.render(path='erp.jpg')
# make_snapshot(snapshot, bar.render(), "automation_data.png")
df = pd.DataFrame({"分类": ["1月", "2月", "3月", "4月", "5月", "6月", "7月", "8月", "9月", "10月", "11月"],
"数据": [755, 664, 1082, 692, 729, 941, 1131, 2022, 831, 760, 371]})
# v1 = [18, 59, 26, 38, 9, 17]
x_data = df['分类'].tolist()
y_data = df['数据'].tolist()
line = Line()
line.add_xaxis(x_data)
line.add_yaxis("数据", y_data)
line.set_global_opts(title_opts=opts.TitleOpts(title="erp折线图", pos_top="48%"),
legend_opts=opts.LegendOpts(pos_top="48%"))
# c = (
# Pie()
# .add("", [list(z) for z in zip(x_data, y_data)]) # zip函数两个部分组合在一起list(zip(x,y))-----> [(x,y)]
# .set_global_opts(title_opts=opts.TitleOpts(title="自动化工单统计")) # 标题
# .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}%")) # 数据标签设置
# )
# make_snapshot(snapshot, line.render(), "erp_test.png")
# c.render("./erp.html")
data = [
("生活资源", "999"),
("供热管理", "888"),
("供气质量", "777"),
("生活用水管理", "688"),
("一次供水问题", "588"),
]
w = (
WordCloud()
.add(series_name="热点分析", data_pair=data, word_size_range=[6, 66])
.set_global_opts(
title_opts=opts.TitleOpts(
title="热点分析", title_textstyle_opts=opts.TextStyleOpts(font_size=23)
),
tooltip_opts=opts.TooltipOpts(is_show=True),
)
.render("词云图.html")
)
# make_snapshot(snapshot, line.render(), "erp_test.png")