-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathdata_preprocess.py
143 lines (124 loc) · 5.25 KB
/
data_preprocess.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
import pandas as pd
# HIV分地区数据
class HIVData:
def __init__(self, file_path):
self.year = None
self.data = pd.read_excel(file_path, header=None)
self.data = self.data.iloc[:, 1:6]
self.data = self.data.drop(self.data.index[:3])
self.data = self.data.drop(self.data.index[-1:])
self.data.columns = ['地区', '发病数', '死亡数', '发病率(1/10万)', '死亡率(1/10万)']
self.result_dict = {}
self.new_keys = {
'内蒙古': '内蒙古自治区',
'西 藏': '西藏自治区',
'新疆': '新疆维吾尔自治区',
'广 西': '广西壮族自治区',
'宁夏': '宁夏回族自治区',
'宁 夏': '宁夏回族自治区',
}
self._process_data()
def _process_data(self):
for index, row in self.data.iterrows():
region = row['地区']
values = [row['发病数'], row['死亡数'], float(row['发病率(1/10万)']), float(row['死亡率(1/10万)'])]
if region == '全 国':
self.result_dict['全 国'] = values
else:
self.result_dict[region] = values
# 更新自治区全称
for old_key, new_key in self.new_keys.items():
if old_key in self.result_dict:
self.result_dict.update({new_key: self.result_dict.pop(old_key)})
# 对发病率和死亡率进行三位小数保留
for key in self.result_dict.keys():
try:
for i in range(2, 4):
self.result_dict[key][i] = round(self.result_dict[key][i], 3)
except TypeError:
print(f"Key '{key}' has a None value.")
# 获取发病人数
def get_cases(self):
return {k: v[0] for k, v in self.result_dict.items()}
# 获取死亡人数
def get_death(self):
return {k: v[1] for k, v in self.result_dict.items()}
# 对发病数前十进行排列
def get_top_n_cities_by_cases(self, n=10):
cases = self.get_cases()
sorted_cases = sorted(list(cases.items())[1:], key=lambda x: x[1], reverse=True)
return sorted_cases[:n]
# 对死亡数前十进行排列
def get_top_n_cities_by_death(self, n=10):
death = self.get_death()
sorted_cases = sorted(list(death.items())[1:], key=lambda x: x[1], reverse=True)
return sorted_cases[:n]
# 获取发病率和死亡率
def get_rate(self):
country_values = self.result_dict['全 国']
return [country_values[2], country_values[3]]
def get_data(self):
return self.result_dict
# HIV分年龄数据
class HIVAgeData:
def __init__(self, file_path):
self.year = None
self.data = pd.read_excel(file_path, header=None)
self.data = self.data.iloc[:, 1:6]
self.data = self.data.drop(self.data.index[:3])
self.data = self.data.drop(self.data.index[-1:])
self.data.columns = ['年龄分组', '发病数', '死亡数', '发病率(1/10万)', '死亡率(1/10万)']
self.result_dict = {}
self.age_group_dict = {
'0-20岁': [],
'20-30岁': [],
'30-40岁': [],
'40-60岁': [],
'60-80岁': [],
'80岁及以上': []
}
self._process_data()
self._age_data()
def _process_data(self):
for index, row in self.data.iterrows():
age = row['年龄分组']
values = [row['发病数'], row['死亡数'], float(row['发病率(1/10万)']), float(row['死亡率(1/10万)'])]
self.result_dict[age] = values
# 对发病率和死亡率进行三位小数保留
for key in self.result_dict.keys():
try:
for i in range(2, 4):
self.result_dict[key][i] = round(self.result_dict[key][i], 3)
except TypeError:
print(f"Key '{key}' has a None value.")
# 按年龄段分组统计发病人数
def _age_data(self):
for k ,v in self.result_dict.items():
age_str = k[:-1] # 去除'-'
if age_str == '85及以':
age_str = '85'
elif age_str == '不':
continue
age = int(age_str)
if 0 <= age < 20:
self.age_group_dict['0-20岁'].append(v[:2])
elif 20 <= age < 30:
self.age_group_dict['20-30岁'].append(v[:2])
elif 30 <= age < 40:
self.age_group_dict['30-40岁'].append(v[:2])
elif 40 <= age < 60:
self.age_group_dict['40-60岁'].append(v[:2])
elif 60 <= age < 80:
self.age_group_dict['60-80岁'].append(v[:2])
elif age_str == '85':
self.age_group_dict['80岁及以上'].append(v[:2])
for k in self.age_group_dict.keys():
if self.age_group_dict[k]:
total_cases = sum(x[0] for x in self.age_group_dict[k])
total_deaths = sum(x[1] for x in self.age_group_dict[k])
self.age_group_dict[k] = [total_cases, total_deaths]
def get_data(self):
return self.result_dict
# 获得年龄分组
def get_age_group(self):
return self.age_group_dict