如何使用时间戳与 pandas 一起按小时分组数据帧 [英] How to group dataframe by hour using timestamp with Pandas

问题描述

我具有以下以时间戳为索引的数据帧结构：

I have the following dataframe structure that is indexed with a timestamp:

    neg neu norm    pol pos date
time                        
1520353341  0.000   1.000   0.0000  0.000000    0.000   
1520353342  0.121   0.879   -0.2960 0.347851    0.000   
1520353342  0.217   0.783   -0.6124 0.465833    0.000   

我从时间戳创建日期：

data_frame['date'] = [datetime.datetime.fromtimestamp(d) for d in data_frame.time]

结果：

    neg neu norm    pol pos date
time                        
1520353341  0.000   1.000   0.0000  0.000000    0.000   2018-03-06 10:22:21
1520353342  0.121   0.879   -0.2960 0.347851    0.000   2018-03-06 10:22:22
1520353342  0.217   0.783   -0.6124 0.465833    0.000   2018-03-06 10:22:22

我想按小时分组，同时获取除时间戳记以外的所有值的平均值，这应该是从组开始的小时数。所以这是我要存档的结果：

I want to group by hour, while getting the mean for all the values, except the timestamp, that should be the hour from where the group started. So this is the result I want to archive:

    neg neu norm    pol pos
time                    
1520352000  0.027989    0.893233    0.122535    0.221079    0.078779
1520355600  0.028861    0.899321    0.103698    0.209353    0.071811

我到目前为止最接近的就是这个 answer ：

The closest I have gotten so far has been with this answer:

data = data.groupby(data.date.dt.hour).mean()

结果：

    neg neu norm    pol pos
date                    
0   0.027989    0.893233    0.122535    0.221079    0.078779
1   0.028861    0.899321    0.103698    0.209353    0.071811

但是我不知道如何保留考虑到古劳比开始时间的时间戳。

But I cant figure out how to keep the timestamp that takes in account he hour where the grouby started.

推荐答案

我遇到了 pd.DataFrame.resample 每小时的解决方案。

I came across this gem, pd.DataFrame.resample, after I posted my round-to-hour solution.

# Construct example dataframe
times = pd.date_range('1/1/2018', periods=5, freq='25min')
values = [4,8,3,4,1]
df = pd.DataFrame({'val':values}, index=times)

# Resample by hour and calculate medians
df.resample('H').median()

或者您可以使用 groupby 和 石斑鱼 ，如果您不希望将时间作为索引：

Or you can use groupby with Grouper if you don't want times as index:

df = pd.DataFrame({'val':values, 'times':times})
df.groupby(pd.Grouper(level='times', freq='H')).median()

这篇关于如何使用时间戳与 pandas 一起按小时分组数据帧的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！