仅对 DatetimeIndex、TimedeltaIndex 或 PeriodIndex 有效，但获得了 'Int64Index' 的实例

Question

我正在尝试对此数据帧的时间戳列进行重新采样：

  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

这是我所做的：

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

但是我得到了这个错误：

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

任何建议将不胜感激。

Answer 1

按DataFrame.set_index创建DatetimeIndex - 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

对于缩减采样是可以使用参数on：

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

编辑：要删除所有重复的行Timestamp请将参数subset添加到DataFrame.drop_duplicates：

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