如何从 pandas 的第一个元素开始重新采样? [英] How to resample starting from the first element in pandas?
问题描述
我正在重新采样以下表格/数据:
I am resampling the following table/data:
Timestamp L_x L_y L_a R_x R_y R_a
2403950 621.3 461.3 313 623.3 461.8 260
2403954 622.5 461.3 312 623.3 462.6 260
2403958 623.1 461.5 311 623.4 464 261
2403962 623.6 461.7 310 623.7 465.4 261
2403966 623.8 461.5 309 623.9 466.1 261
2403970 620.9 461.4 309 623.8 465.9 259
2403974 621.7 461.1 308 623 464.8 258
2403978 622.1 461.1 308 621.9 463.9 256
2403982 622.5 461.5 308 621 463.4 255
2403986 622.4 462.1 307 620.7 463.3 254
桌子就这样继续下去. 时间戳以毫秒为单位.我进行了以下操作以将其重新采样为100毫秒的bin时间:
The table goes on and on like that. The timestamps are in milliseconds. I did the following to resample it into 100milliseconds bin time:
-
我将时间戳索引更改为日期时间格式
I changed the timestamp index into a datetime format
df.index = pd.to_datetime((df.index.values*1e6).astype(int))
我在100毫秒内对其进行了重新采样:
I resampled it in 100milliseconds:
df = df.resample('100L')
重新采样后的数据如下:
The resulting resampled data look like the following:
Timestamp L_x L_y L_a R_x R_y R_a
2403900 621.3 461.3 313 623.3 461.8 260
2404000 622.5 461.3 312 623.3 462.6 260
2404100 623.1 461.5 311 623.4 464 261
2404200 623.6 461.7 310 623.7 465.4 261
2404300 623.8 461.5 309 623.9 466.1 261
我们可以看到第一个bin时间是2403900，比原始表的第一个时间戳索引晚50毫秒.但我希望bin时间从原始表的第一个时间戳索引2403950开始.如下所示:
As we can see the first bin time is 2403900, which is 50milliseconds behind the first timestamp index of the original table. But i wanted the bin time to start from the first timestamp index from the original table, which is 2403950. like the following:
Timestamp L_x L_y L_a R_x R_y R_a
2403950 621.3 461.3 313 623.3 461.8 260
2404050 622.5 461.3 312 623.3 462.6 260
2404150 623.1 461.5 311 623.4 464 261
2404250 623.6 461.7 310 623.7 465.4 261
2404350 623.8 461.5 309 623.9 466.1 261
推荐答案
您可以指定一个偏移量:
You can specify an offset:
df.resample('100L', loffset='50L')
更新
当然，您始终可以计算出偏移量:
Of course you can always calculate the offset:
offset = df.index[0] % 100
df.index = pd.to_datetime((df.index.values*1e6).astype(int))
df.resample('100L', loffset='{}L'.format(offset))
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