仅对DatetimeIndex,TimedeltaIndex或PeriodIndex有效,但得到'Int64Index'的实例

问题描述 投票:0回答:1

我正在尝试重新采样此Dataframe的Timestamp列:

  Transit.head():

      Timestamp                            Plate           Gate
  0 2013-11-01 21:02:17 4f5716dcd615f21f658229a8570483a8    65
  1 2013-11-01 16:12:39 0abba297ac142f63c604b3989d0ce980    64
  2 2013-11-01 11:06:10 faafae756ce1df66f34f80479d69411d    57

这就是我所做的:

  Transit.drop_duplicates(inplace=True)
  Transit.Timestamp = pd.to_datetime(Transit.Timestamp)
  Transit['Timestamp'].resample('1H').pad()

但我得到了这个错误:

  Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'Int64Index'

任何建议都会得到很多赞赏。

python-3.x pandas datetime dataframe resampling
1个回答
1
投票

通过DatetimeIndex创建DataFrame.set_index - 上采样和下采样的解决方案:

df = Transit.set_index('Timestamp').resample('1H').pad()
print (df)
                                                Plate  Gate
Timestamp                                                  
2013-11-01 11:00:00                               NaN   NaN
2013-11-01 12:00:00  faafae756ce1df66f34f80479d69411d  57.0
2013-11-01 13:00:00  faafae756ce1df66f34f80479d69411d  57.0
2013-11-01 14:00:00  faafae756ce1df66f34f80479d69411d  57.0
2013-11-01 15:00:00  faafae756ce1df66f34f80479d69411d  57.0
2013-11-01 16:00:00  faafae756ce1df66f34f80479d69411d  57.0
2013-11-01 17:00:00  0abba297ac142f63c604b3989d0ce980  64.0
2013-11-01 18:00:00  0abba297ac142f63c604b3989d0ce980  64.0
2013-11-01 19:00:00  0abba297ac142f63c604b3989d0ce980  64.0
2013-11-01 20:00:00  0abba297ac142f63c604b3989d0ce980  64.0
2013-11-01 21:00:00  0abba297ac142f63c604b3989d0ce980  64.0

对于下采样,可以使用参数on

df = Transit.resample('D', on='Timestamp').mean()
print (df)
            Gate
Timestamp       
2013-11-01    62

编辑:删除所有重复Timestamp的行添加参数subsetDataFrame.drop_duplicates

Transit.drop_duplicates(subset=['Timestamp'], inplace=True)
Transit.Timestamp = pd.to_datetime(Transit.Timestamp)
df = Transit.set_index('Timestamp').resample('1H').pad()
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