Warning: file_get_contents(/data/phpspider/zhask/data//catemap/2/python/359.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
Python:使用熊猫创建多列系列_Python_Pandas_Time Series - Fatal编程技术网

Python:使用熊猫创建多列系列

Python:使用熊猫创建多列系列,python,pandas,time-series,Python,Pandas,Time Series,我正在尝试使用pandas库创建多列系列: import pandas as pd import numpy as np StartTime = '2015-10-01' EndTime = '2016-01-01' step = '1min' Time= pd.date_range(StartTime,EndTime,freq=step) Value1 = np.random.choice(range(0,100),len(Time)) Value2 = np.random.choice(r

我正在尝试使用pandas库创建多列系列:

import pandas as pd
import numpy as np
StartTime = '2015-10-01'
EndTime = '2016-01-01'
step = '1min'

Time= pd.date_range(StartTime,EndTime,freq=step)
Value1 = np.random.choice(range(0,100),len(Time))
Value2 = np.random.choice(range(0,100),len(Time))
Value3 = np.random.choice(range(0,100),len(Time))
#Time series of one variable
TimeSeries = pd.Series(Time,Value1)
我想要的是每个时间点都有3个变量。我尝试了以下方法,但无效:

 TimeSeries = pd.Series(Time,Value1,Value2,Value3)
你知道如何实现这一点吗?

,尽管这样做可行:

>>> TimeSeries = pd.Series(tuple(zip(*(Value1, Value2, Value3))), index=Time)
>>> TimeSeries.head()
2015-10-01 00:00:00    (71, 58, 69)
2015-10-01 00:01:00     (59, 1, 94)
2015-10-01 00:02:00     (50, 65, 6)
2015-10-01 00:03:00     (16, 50, 7)
2015-10-01 00:04:00    (20, 36, 41)
Freq: T, dtype: object
最好使用数据帧:

>>> df = pd.DataFrame({'Value1': Value1, 'Value2': Value2, 'Value3':Value3}, index=Time)
>>> df.head()
                     Value1  Value2  Value3
2015-10-01 00:00:00      71      58      69
2015-10-01 00:01:00      59       1      94
2015-10-01 00:02:00      50      65       6
2015-10-01 00:03:00      16      50       7
2015-10-01 00:04:00      20      36      41

谢谢你的邀请。是的,您的第二个答案似乎更易于以后使用数据。是的,这就是数据帧的用途。@MpizosDimitris看起来您可以;)。很抱歉没有早点投票。我想我完成我的任务时太激动了:)