【发布时间】:2019-07-14 15:16:48
【问题描述】:
我有一个如下所示的日志:
**  Wed; Feb 20 2019 at 12:38:10:734 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:12:742 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:14:721 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:16:777 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:18:729 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:20:700 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:22:697 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:24:706 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
**  Wed; Feb 20 2019 at 12:38:26:783 PM : ** **  GnssLocationListener; \- 41** \- onSatelliteStatusChanged() : fixCount = 7
我正在尝试从中获取以下数据:
12:38:10 PM , 7
12:38:12 PM , 7
12:38:14 PM , 7
12:38:16 PM , 7
12:38:18 PM , 7
...
我正在尝试用我在 Python 中所知道的来做到这一点......这是非常初级的。
import matplotlib.pyplot as plt
import matplotlib.dates as md
import numpy as np
import datetime as dt
import time
import csv
data = []
datafile = open('fix_count_02-20-2019-day.txt' , 'r')
datareader = csv.reader((x.replace('\0','') for x in datafile), delimiter=':')
for row in datareader:
data.append(row)
np_data = np.asarray(data)
print(np_data)
plt.subplots_adjust(bottom=0.2)
plt.xticks( rotation=25 )
ax=plt.gca()
#xfmt = md.DateFormatter('%H:%M:%S')
#ax.xaxis.set_major_formatter(xfmt)
plt.plot(np_data)
plt.show()
我用split 和join 尝试了一些体操,但这对我来说并没有真正奏效......我最终想绘制类似于this 的问题,可能(我猜) 带有一个 numpy 数组:
【问题讨论】:
标签: python numpy datetime parsing timestamp