python提取特定时间段内的数据
尝试一下：
data['Date'] = pd.to_datetime(data['Date'])
data = data[(data['Date'] >=pd.to_datetime('20120701')) & (data['Date'] <= pd.to_datetime('20120831'))]
实际测试
'''
Created on 2019年1月3日
@author: hcl
'''
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'one_20axyz.csv'
if __name__ == '__main__':
msg = pd.read_csv(data_path)
# ID_set = set(msg['Time'].tolist())
# ID_list = list(ID_set)
# print(len(msg['Time'].tolist()),len(ID_list),len(msg['Time'].tolist())/len(ID_list))#打印数据量 多少秒 平均每秒多少个
# print(msg.head(10))
# left_a = msg[msg['leg'] == 1]['az']# right_a = msg[msg['leg'] == 2]['az']# plt.plot(left_a,label = 'left_a')
# plt.plot(right_a,label = 'right_a')
# plt.legend(loc = 'best')
# plt.show()
left_msg = msg[msg['leg'] == 1] #DataFrame
data = left_msg[(pd.to_datetime(left_msg['Time'] ,format = '%H:%M:%S')>= pd.to_datetime('16:23:42',format = '%H:%M:%S')) & (pd.to_datetime(left_msg['Time'] ,format = '%H:%M:%S') <= pd.to_datetime('16:23:52',format = '%H:%M:%S'))]# print(msg.head())
print(data)
输出：
Time ID leg ax ay az a Rssi
1 16:23:42 5 1 0.6855 -0.6915 0.1120 0.980116 -34
3 16:23:42 5 1 0.6800 -0.6440 0.1365 0.946450 -31
5 16:23:42 5 1 0.7145 -0.7240 0.1095 1.023072 -34
7 16:23:42 5 1 0.7050 -0.6910 0.1080 0.993061 -30
9 16:23:42 5 1 0.7120 -0.6400 0.0920 0.961773 -31
10 16:23:42 5 1 0.7150 -0.6810 0.1290 0.995805 -34
12 16:23:42 5 1 0.7250 -0.6655 0.1890 1.002116 -32
13 16:23:42 5 1 0.7160 -0.7065 0.1000 1.010840 -31
15 16:23:42 5 1 0.7545 -0.6990 0.1715 1.042729 -30
17 16:23:42 5 1 0.7250 -0.6910 0.1325 1.010278 -31
19 16:23:42 5 1 0.7520 -0.7260 0.1820 1.060992 -33
21 16:23:42 5 1 0.7005 -0.7150 0.0605 1.002789 -33
23 16:23:42 5 1 0.7185 -0.6630 0.1430 0.988059 -30
25 16:23:42 5 1 0.7170 -0.7040 0.0920 1.009044 -34
27 16:23:42 5 1 0.7230 -0.6810 0.1060 0.998862 -31
29 16:23:42 5 1 0.7230 -0.6720 0.0940 0.991539 -31
31 16:23:42 5 1 0.6955 -0.6975 0.0720 0.987629 -33
32 16:23:42 5 1 0.7430 -0.6895 0.1495 1.024602 -34
34 16:23:43 5 1 0.7360 -0.6855 0.1200 1.012920 -32
36 16:23:43 5 1 0.7160 -0.7000 0.1330 1.010121 -30
38 16:23:43 5 1 0.7095 -0.7165 0.1090 1.014221 -31
40 16:23:43 5 1 0.7195 -0.6895 0.1270 1.004599 -34
44 16:23:43 5 1 0.7315 -0.6855 0.1000 1.007473 -34
46 16:23:43 5 1 0.7240 -0.7020 0.0960 1.013013 -31
48 16:23:43 5 1 0.7240 -0.7010 0.0970 1.012416 -32
50 16:23:43 5 1 0.7380 -0.6820 0.1480 1.015713 -34