时间戳

首页 > 解决方案 > 当时间随日期更改时如何添加额外的时间列

python-3.x - 当时间随日期更改时如何添加额外的时间列

问题描述

这个问题与这个问题有关：How to add extra time into the time column with data using python

在这里，我有一个包含日期、时间和一个输入列的数据集。所以这里我的时间专栏不好。所以我想在那个时间列中给出时间范围。所以在这里我首先将开始时间转换为 0 并将整个时间列转换为分钟。

然后接下来我想给出时间范围0,60,120....

意思是我预期的输出是：

第一次转换

date	    time	    time convert
10/3/2018	6:15:00 	0
10/3/2018	6:45:00 	30
10/3/2018	7:45:00 	90
10/3/2018	9:00:00 	165
10/3/2018	9:25:00 	190
10/3/2018	9:30:00 	195
10/3/2018	11:00:00	285
10/3/2018	11:30:00	315
10/3/2018	13:30:00	435
10/3/2018	13:50:00	455
10/3/2018	15:00:00	525
10/3/2018	15:25:00	550
10/3/2018	16:25:00	610
10/3/2018	18:00:00	705
10/3/2018	19:00:00	765
10/3/2018	19:30:00	795
10/3/2018	20:00:00	825
10/3/2018	22:05:00	950
10/3/2018	22:15:00	960
10/3/2018	23:40:00	1045
10/4/2018	6:58:00  	0
10/4/2018	13:00:00	2
10/4/2018	16:00:00	47
10/4/2018	17:00:00	152

预期产出

                   expected time                            
                         0.0
                         30.0             
                         60
                         90.0 
                         120
                         165.0
                         180
                         190.0
                         195.0
                         240
                         285.0
                         300
                         315.0
                         360
                         420
                         435
                         455
                         480
                         525
                         540
                         550
                          :
                          :
                          :
                          :
                          0   new date ,start time=0
                          2
                          47
                          60
                          120
                          152
                          180

所以这里每个新的一天开始时间应该是 0 然后应该添加 60 分钟 60 分钟到时间。

在这里我尝试了一个代码，它给了我这个错误“无法从重复的轴重新索引”

代码 ：

data['date']= pd.to_datetime(data['date'] + " " + data['time'],
                    format='%d/%m/%Y %H:%M:%S', dayfirst=True)
lastday = data.loc[0, 'date']
def convert_time(x):
global lastday
if x.date() == lastday.date():
    tm = x - lastday
    return tm.total_seconds()/60
else:
    lastday = x
    return 0

data['time'] = data['date'].apply(convert_time).values


data = data.reset_index()
arr = np.arange(0, int(data['time'].max()), 60)
union = np.union1d(data['time'], arr)
data = data.set_index('time').reindex(union, fill_value=0).reset_index()

错误 ：

ValueError                                Traceback (most recent call last)
<ipython-input-27-bdb960d8efe1> in <module>()
     26 arr = np.arange(0, int(data['time'].max()), 60)
     27 union = np.union1d(data['time'], arr)
---> 28 data = data.set_index('time').reindex(union, fill_value=0).reset_index()

~\Anaconda3\lib\site-packages\pandas\util\_decorators.py in wrapper(*args, **kwargs)
    184         @wraps(func)
    185         def wrapper(*args, **kwargs):
--> 186             return func(*args, **kwargs)
    187 
    188         if not PY2:

~\Anaconda3\lib\site-packages\pandas\core\frame.py in reindex(self, *args, **kwargs)
   3561         kwargs.pop('axis', None)
   3562         kwargs.pop('labels', None)
-> 3563         return super(DataFrame, self).reindex(**kwargs)
   3564 
   3565     @Appender(_shared_docs['reindex_axis'] % _shared_doc_kwargs)

~\Anaconda3\lib\site-packages\pandas\core\generic.py in reindex(self, *args, **kwargs)
   3683         # perform the reindex on the axes
   3684         return self._reindex_axes(axes, level, limit, tolerance, method,
-> 3685                                   fill_value, copy).__finalize__(self)
   3686 
   3687     def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,

~\Anaconda3\lib\site-packages\pandas\core\frame.py in _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
   3496         if index is not None:
   3497             frame = frame._reindex_index(index, method, copy, level,
-> 3498                                          fill_value, limit, tolerance)
   3499 
   3500         return frame

~\Anaconda3\lib\site-packages\pandas\core\frame.py in _reindex_index(self, new_index, method, copy, level, fill_value, limit, tolerance)
   3507         return self._reindex_with_indexers({0: [new_index, indexer]},
   3508                                            copy=copy, fill_value=fill_value,
-> 3509                                            allow_dups=False)
   3510 
   3511     def _reindex_columns(self, new_columns, method, copy, level,

~\Anaconda3\lib\site-packages\pandas\core\generic.py in _reindex_with_indexers(self, reindexers, fill_value, copy, allow_dups)
   3804                                                 fill_value=fill_value,
   3805                                                 allow_dups=allow_dups,
-> 3806                                                 copy=copy)
   3807 
   3808         if copy and new_data is self._data:

~\Anaconda3\lib\site-packages\pandas\core\internals.py in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups, copy)
   4412         # some axes don't allow reindexing with dups
   4413         if not allow_dups:
-> 4414             self.axes[axis]._can_reindex(indexer)
   4415 
   4416         if axis >= self.ndim:

~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in _can_reindex(self, indexer)
   3557         # trying to reindex on an axis with duplicates
   3558         if not self.is_unique and len(indexer):
-> 3559             raise ValueError("cannot reindex from a duplicate axis")
   3560 
   3561     def reindex(self, target, method=None, level=None, limit=None,

ValueError: cannot reindex from a duplicate axis

我的 csv 的子集：

date	time	X3
10/3/2018	6:15:00	7
10/3/2018	6:45:00	5
10/3/2018	7:45:00	7
10/3/2018	9:00:00	7
10/3/2018	9:25:00	7
10/3/2018	9:30:00	5
10/3/2018	11:00:00	7
10/3/2018	11:30:00	7
10/3/2018	13:30:00	7
10/3/2018	13:50:00	5
10/3/2018	15:00:00	7
10/3/2018	15:25:00	7
10/3/2018	16:25:00	7
10/3/2018	18:00:00	7
10/3/2018	19:00:00	5

我的 csv ： 在此处输入链接描述

标签： python-3.xtime

解决方案

推荐阅读