使用python将csv文件中的整个时间列转换为UTC(纪元)

数据挖掘 Python 时间序列 CSV
2022-02-24 01:17:28

我有一个包含时间和列的数据集。我想绘制一个带有时间和价值的图表。我尝试了很多方法,但没有得到正确的图表。因为我有时间序列。然后我想我会将时间转换为UTC,然后尝试绘制它。但我不知道如何将整列转换为 UTC。谁能帮我解决这个错误?

time.strftime("%Y-%m-%d %H:%M:%S", time.gmtime(time.mktime(time.strptime("2008-09-17 14:04:00", "%Y-%m-%d %H:%M:%S"))))

此代码仅用于一次。如果我想转换整个列,那么我应该怎么做?

def convertTime(s):
tm = ((datetime.datetime.strptime(s, '%d/%m/%Y %H:%M'))-datetime.datetime(1970,1,1)).total_seconds()*1000 
return 

我写了这段代码。但它给了我一个错误。我的 csv 文件

我的代码是:

 condition = ""
date_time  = []
x1 = []
x2 = []
x3 = []
def convertTime(s):
  tm = time.strptime(s, " %d/%m/%Y %H:%M")
  return datetime.datetime(tm.tm_year,tm.tm_mon, tm.tm_mday, tm.tm_hour, tm.tm_min, tm.tm_sec)
with open('data43.csv','r') as csv_file:
csv_data = csv.reader(csv_file, delimiter=',')
 row_num = 0
for row in csv_data:
 if(row_num == 0):
  condition = row[0]
elif(row_num > 1): #Data starts here
  if(row[0] != ''):
    date_time.append(convertTime(row[0]))
  if(row[1] != ''):
    x1.append(int(row[1]))
  if(row[2] != ''):
    x2.append(int(row[2]))
  if(row[3] != ''):
    x3.append(int(row[3]))
row_num = row_num + 1
fig1 = plt.figure(1)
ax = fig1.add_subplot(2,1,1)
ax.plot(date_time,x1)
ax.stem(date_time,x2,'C1--','C1o',linefmt=None, markerfmt=None, basefmt=None)
ax.stem(date_time,x3,'C2--','C2o',linefmt=None, markerfmt=None, basefmt=None)
ax.legend()
ax.xaxis_date()
ax.get_xaxis().set_major_formatter(DateFormatter('%d/%m/%Y %H:%M:%S'))
plt.xlabel('t')
plt.ylabel('k')
leg = plt.legend( loc = 'upper right')
plt.draw() # Draw the figure so you can find the positon of the legend. 
bb = leg.get_bbox_to_anchor().inverse_transformed(ax.transAxes)
xOffset = 0.3
bb.x0 += xOffset
bb.x1 += xOffset
leg.set_bbox_to_anchor(bb, transform = ax.transAxes)
plt.rcParams["figure.figsize"] = [20,20]
ax.plot(style='.-')
plt.show()
1个回答

解决绘制时间序列图问题的最简单方法之一是使用 pandas。您可以使用此代码

data = pd.read_csv('YOUR_FILENAME_HERE.csv')
data['datetime'] = data['date'] + ' ' + data['time']
data['datetime'] = pd.to_datetime(data['datetime'])
data.index = data['date_time']
data.drop(['date', 'time', 'datatime'], inplace = True, axis = 1)
data['x1'].plot()