我有一个数据框，表示应该以100 Hz采样的1秒数据。
我想要
1）resample它以10毫秒的速率使用每一列的“ avg”方法，以及2）缺少时基于插值方法添加额外的行，如下所示：
DF_input：
ephoc_as_datatime att1 att2
2000-01-01 11:22:37.130 0 4
2000-01-01 11:22:37.138 1 5
2000-01-01 11:22:37.149 2 6
2000-01-01 11:22:37.156 3 7
2000-01-01 11:22:37.165 4 8
2000-01-01 11:22:37.168 5 9
2000-01-01 11:22:37.169 3 7
2000-01-01 11:22:37.567 7 3
2000-01-01 11:22:38.120 8 4
DF_output：
ephoc_as_datatime att1 att2
2000-01-01 11:22:37.130 0 4
2000-01-01 11:22:37.140 1 5
2000-01-01 11:22:37.150 2 6
2000-01-01 11:22:37.160 3 7
2000-01-01 11:22:37.170 4 8
....adding the missing one
2000-01-01 11:22:37.570 7 3
....adding the missing one
2000-01-01 11:22:38.120 8 4
我知道我应该使用
resample和interpolate。请，任何建议将不胜感激。
非常感谢，
最好的祝福，
卡洛
最佳答案
我认为您需要使用resample的10L和10ms的interpolate：
#if necessary convert to datetimes
#df['ephoc_as_datatime'] = pd.to_datetime(df['ephoc_as_datatime'])
df = df.resample('10L', on='ephoc_as_datatime').mean().interpolate()
print (df.head(20))
att1 att2
ephoc_as_datatime
2000-01-01 11:22:37.130 0.500 4.500
2000-01-01 11:22:37.140 2.000 6.000
2000-01-01 11:22:37.150 3.000 7.000
2000-01-01 11:22:37.160 4.000 8.000
2000-01-01 11:22:37.170 4.075 7.875
2000-01-01 11:22:37.180 4.150 7.750
2000-01-01 11:22:37.190 4.225 7.625
2000-01-01 11:22:37.200 4.300 7.500
2000-01-01 11:22:37.210 4.375 7.375
2000-01-01 11:22:37.220 4.450 7.250
2000-01-01 11:22:37.230 4.525 7.125
2000-01-01 11:22:37.240 4.600 7.000
2000-01-01 11:22:37.250 4.675 6.875
2000-01-01 11:22:37.260 4.750 6.750
2000-01-01 11:22:37.270 4.825 6.625
2000-01-01 11:22:37.280 4.900 6.500
2000-01-01 11:22:37.290 4.975 6.375
2000-01-01 11:22:37.300 5.050 6.250
2000-01-01 11:22:37.310 5.125 6.125
2000-01-01 11:22:37.320 5.200 6.000
详情：
print(df.resample('10L', on='ephoc_as_datatime').mean().head(20))
att1 att2
ephoc_as_datatime
2000-01-01 11:22:37.130 0.5 4.5
2000-01-01 11:22:37.140 2.0 6.0
2000-01-01 11:22:37.150 3.0 7.0
2000-01-01 11:22:37.160 4.0 8.0
2000-01-01 11:22:37.170 NaN NaN
2000-01-01 11:22:37.180 NaN NaN
2000-01-01 11:22:37.190 NaN NaN
2000-01-01 11:22:37.200 NaN NaN
2000-01-01 11:22:37.210 NaN NaN
2000-01-01 11:22:37.220 NaN NaN
2000-01-01 11:22:37.230 NaN NaN
2000-01-01 11:22:37.240 NaN NaN
2000-01-01 11:22:37.250 NaN NaN
2000-01-01 11:22:37.260 NaN NaN
2000-01-01 11:22:37.270 NaN NaN
2000-01-01 11:22:37.280 NaN NaN
2000-01-01 11:22:37.290 NaN NaN
2000-01-01 11:22:37.300 NaN NaN
2000-01-01 11:22:37.310 NaN NaN
2000-01-01 11:22:37.320 NaN NaN