pandas 数据框每天重新采样，没有日期时间索引

问题描述

我有一个如下形式的熊猫数据框:

I have a dataframe in pandas of the following form:

      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

这里注意索引不是时间戳列.但我想重新采样(或以某种方式对数据进行分类)以反映每分钟、每小时、每天等光柱的平均值.我研究了 pandas 提供的 resample 方法，它需要数据框有一个数据时间索引以便该方法工作(除非我误解了这一点).

Here note that the index is not the timestamps column. 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).

1. 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作为索引(请注意，并非每一行都有唯一的时间戳，对于每个时间戳，大约有 30 行具有相同的时间戳，每个代表一个传感器).

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).

如果没有，是否有其他方法可以实现另一个数据帧，该数据帧具有每小时、每天、每月等的平均值?

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..?

任何帮助将不胜感激.

推荐答案

你是对的 - 需要 DatetimeIndex, TimedeltaIndex 或 PeriodIndex 否则错误:

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

TypeError:仅对 DatetimeIndex、TimedeltaIndex 或 PeriodIndex 有效，但获得了 'Index' 的实例

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

所以你必须先 reset_index 和 set_index 如果原始 index 很重要:

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

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

如果不只是 set_index:

if not only 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

然后 resample:

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

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