将平均每五分钟数据作为 pandas 数据帧中的一个数据点 [英] averaging every five minutes data as one datapoint in pandas dataframe

问题描述

我有这样的熊猫数据框

  1。 2013-10-09 09:00:05 
 2. 2013-10-09 09:01:00 
 3. 2013-10-09 09:02:00 
 4. .. .......... 
 5. ............ 
 6. ............ 
 7. 2013-10-10 09:15:05 
 8. 2013-10-10 09:16:00 
 9. 2013-10-10 09:17:00 
  

我想通过平均每5分钟的数据并形成1个数据点来缩小Dataframe的大小。像这样





  1。 2013-10-09 09:05:00 
 2. 2013-10-09 09:10:00 
 3. 2013-10-09 09:15:00 
  

有人可以帮我吗？

解决方案>

您可能需要查看 pandas.resample ：

  df ['Data']。resample（'5Min'，how ='mean'）
  

或作为 how ='mean'是默认参数：

  df ['Data']。resample（'5Min'）
  

例如：

 >> ; rng = pd.date_range（'1/1/2012'，periods = 10，freq ='Min'）
>>> df = pd.DataFrame（{'Data'：np.random.randint（0，500，len（rng））}，index = rng）
>>> df 
数据
 2012-01-01 00:00:00 488 
 2012-01-01 00:01:00 172 
 2012-01-01 00:02:00 276 
 2012-01-01 00:03:00 5 
 2012-01-01 00:04:00 233 
 2012-01-01 00:05:00 266 
 2012-01-01 00:06:00 103 
 2012-01-01 00:07:00 40 
 2012-01-01 00:08:00 274 
 2012-01-01 00:09:00 494 
>>> 
>>> df ['Data']。resample（'5Min'）
 2012-01-01 00:00:00 234.8 
 2012-01-01 00:05:00 235.4 
  

您可以找到更多例子 here 。

I have a Dataframe in Pandas like this

1. 2013-10-09 09:00:05
2. 2013-10-09 09:01:00
3. 2013-10-09 09:02:00
4.  ............
5.   ............
6.   ............
7. 2013-10-10 09:15:05
8. 2013-10-10 09:16:00 
9. 2013-10-10 09:17:00

I would like reduce the size of the Dataframe by averaging every 5 mins data and forming 1 datapoint for it ..like this

1. 2013-10-09 09:05:00
2. 2013-10-09 09:10:00
3. 2013-10-09 09:15:00

Can someone help me with this ??

解决方案

you may want to look at pandas.resample:

df['Data'].resample('5Min', how='mean')

or, as how = 'mean' is default parameter:

df['Data'].resample('5Min')

For example:

>>> rng = pd.date_range('1/1/2012', periods=10, freq='Min')
>>> df = pd.DataFrame({'Data':np.random.randint(0, 500, len(rng))}, index=rng)
>>> df
                     Data
2012-01-01 00:00:00   488
2012-01-01 00:01:00   172
2012-01-01 00:02:00   276
2012-01-01 00:03:00     5
2012-01-01 00:04:00   233
2012-01-01 00:05:00   266
2012-01-01 00:06:00   103
2012-01-01 00:07:00    40
2012-01-01 00:08:00   274
2012-01-01 00:09:00   494
>>>
>>> df['Data'].resample('5Min')
2012-01-01 00:00:00    234.8
2012-01-01 00:05:00    235.4

You can find more examples here.

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