python - 熊猫数据框每天重新采样，没有日期时间索引(pandas dataframe resample per day without date time index)

Question

I have a dataframe in pandas of the following form:

(我有以下形式的熊猫数据框：)

      timestamps         light
7   2004-02-28 00:58:45 150.88
26  2004-02-28 00:59:45 143.52
34  2004-02-28 01:00:45 150.88
42  2004-02-28 01:01:15 150.88
59  2004-02-28 01:02:15 150.88

Here note that the index is not the timestamps column.

(在这里请注意，索引不是时间戳列。)

But I want to resample (or bin the data somehow) to reflect the average value of the light column per minute , hour, day etc.. I have looked into the resample method that pandas offers and it requires the dataframe to have a datatime index for the method to work (unless I've misunderstood this).

(但是我想重新采样（或以某种方式对数据进行分箱）以反映每分钟，每小时，每天等的光柱的平均值。我研究了pandas提供的resample方法，它要求数据帧具有数据时间索引为工作方法（除非我误解了这一点）。)

1. So my first question is, can I re-index the dataframe to have timestamps as the index (note that not each row has a unique timestamp and for each timestamp, there are about 30 rows with the same timestamp,each representing a sensor).

   (所以我的第一个问题是，我可以重新索引数据帧以将时间戳记作为索引吗（请注意，并非每一行都有唯一的时间戳记，对于每个时间戳记，大约有30行具有相同的时间戳记，每行代表一个传感器）。)

2. If not, is there some other way to possibly achieve another dataframe which has the average value of light per hour , per day , per month etc..?

   (如果不是，是否有其他方法可以实现另一个具有每小时，每天，每月等的光平均值的数据帧？)

Any help would be appreciated.

(任何帮助，将不胜感激。)

  ask by Nikhil translate from so

Answer 1

You are right - need DatetimeIndex , TimedeltaIndex or PeriodIndex else error:

(您是对的-需要DatetimeIndex ， TimedeltaIndex或PeriodIndex否则错误：)

TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'Index'

(TypeError：仅对DatetimeIndex，TimedeltaIndex或PeriodIndex有效，但具有“ Index”的实例)

So you have to first reset_index and set_index if original index is important:

(因此，如果原始index很重要，则必须首先重设reset_index和set_index ：)

print (df.reset_index().set_index('timestamps'))
                     index   light
timestamps                        
2004-02-28 00:58:45      7  150.88
2004-02-28 00:59:45     26  143.52
2004-02-28 01:00:45     34  150.88
2004-02-28 01:01:15     42  150.88
2004-02-28 01:02:15     59  150.88

if not only set_index :

(如果不仅是set_index ：)

print (df.set_index('timestamps'))
                      light
timestamps                 
2004-02-28 00:58:45  150.88
2004-02-28 00:59:45  143.52
2004-02-28 01:00:45  150.88
2004-02-28 01:01:15  150.88
2004-02-28 01:02:15  150.88

and then resample :

(然后resample ：)

print (df.reset_index().set_index('timestamps').resample('1D').mean())
            index    light
timestamps                
2004-02-28   33.6  149.408