-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathvote.py
114 lines (98 loc) · 4.21 KB
/
vote.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
#coding=utf-8
'''
Created on 2016年12月19日
@author: Administrator
'''
import numpy as np
import datetime
import matplotlib.pyplot as plt
"""
判断一个字符串能否转换为float
"""
def is_convert_float(s):
try:
float(s)
except:
return False
return True
"""
返回字符串数组中数字的总和
"""
def get_sum(str_array):
# 去掉不能转换成数字的数据, 过滤掉非数字
cleaned_data = filter(is_convert_float, str_array)
# 转换数据类型，将字符串转化为float
float_array = np.array(cleaned_data, np.float)
# 返回数组合
return np.sum(float_array)
def main():
'''
数据读取
'''
testFilename = './presidential_polls.csv'
with open(testFilename) as f:
# 读取标题
col_names_str = f.readline()[:-1] # [:-1]表示不读取末尾的换行符'\n'
# 将字符串拆分，并组成列表
col_names_list = col_names_str.split(',')
# 使用到的列名
user_col_list = ['enddate', 'rawpoll_clinton', 'rawpoll_trump','adjpoll_clinton', 'adjpoll_trump']
# 使用列在原列中的列表
user_col_index_list = [col_names_list.index(use_col_name) for use_col_name in user_col_list]
# 获取需要
data_arr = np.loadtxt(testFilename,
dtype = str,
delimiter = ',',
skiprows = 1,
usecols = user_col_index_list)
'''
数据处理
'''
# 日期处理
enddate_idx = user_col_list.index('enddate')
enddate_lst = data_arr[:, enddate_idx].tolist()
enddate_lst = [enddate.replace('-', '/') for enddate in enddate_lst]
date_list = [datetime.datetime.strptime(enddate, '%m/%d/%Y') for enddate in enddate_lst]
month_list = ['%d-%02d' %(date_obj.year, date_obj.month) for date_obj in date_list]
month_arr = np.array(month_list)
months = np.unique(month_arr)
# 获取需要的列数据
raw_data_clt = data_arr[:, user_col_list.index('rawpoll_clinton')]
adj_data_clt = data_arr[:, user_col_list.index('adjpoll_clinton')]
raw_data_trump = data_arr[:, user_col_list.index('rawpoll_trump')]
adj_data_trump = data_arr[:, user_col_list.index('adjpoll_trump')]
# 按月分组处理
result = []
for month in months:
raw_data_clt_month = raw_data_clt[month_arr == month]
raw_data_clt_month_sum = get_sum(raw_data_clt_month)
adj_data_clt_month = adj_data_clt[month_arr == month]
adj_data_clt_month_sum = get_sum(adj_data_clt_month)
raw_data_trump_month = raw_data_trump[month_arr == month]
raw_data_trump_month_sum = get_sum(raw_data_trump_month)
adj_data_trump_month = adj_data_trump[month_arr == month]
adj_data_trump_month_sum = get_sum(adj_data_trump_month)
result.append((month, raw_data_clt_month_sum, adj_data_clt_month_sum, raw_data_trump_month_sum, adj_data_trump_month_sum))
months, raw_cliton_sum, adj_cliton_sum, raw_trump_sum, adj_trump_sum = zip(*result)
#图像表示，两行两列四个图分别显示不同数据
fig, subplot_arr = plt.subplots(2, 2, figsize = (15, 10))
subplot_arr[0, 0].plot(raw_cliton_sum, color = 'r')
subplot_arr[0, 0].plot(raw_trump_sum, color = 'g')
width = 0.25
x = np.arange(len(months))
subplot_arr[0, 1].bar(x, raw_cliton_sum, width, color = 'r')
subplot_arr[0, 1].bar(x + width, raw_trump_sum, width, color = 'g')
subplot_arr[0, 1].set_xticks(x + width)
subplot_arr[0, 1].set_xticklabels(months, rotation = 'vertical')
subplot_arr[1, 0].plot(adj_cliton_sum, color = 'r')
subplot_arr[1, 0].plot(adj_trump_sum, color = 'g')
width = 0.25
x = np.arange(len(months))
subplot_arr[1, 1].bar(x, adj_cliton_sum, width, color = 'r')
subplot_arr[1, 1].bar(x + width, adj_trump_sum, width, color = 'g')
subplot_arr[1, 1].set_xticks(x + width)
subplot_arr[1, 1].set_xticklabels(months, rotation = 'vertical')
plt.subplots_adjust(wspace = 0.2)
plt.show()
if __name__ == "__main__" :
main()