我有一个df,如下所示。存在速度值,两个值之间的nan值不确定。我正在尝试用两个数值之间的平均值替换nan值。
timestamp ... Speed km h^-1
0 1434838676097.07006835937500000000 ... 53.02799834399999667767
1 1434838676130.07006835937500000000 ... nan
2 1434838676229.07006835937500000000 ... nan
3 1434838676328.07006835937500000000 ... nan
4 1434838676429.07006835937500000000 ... nan
5 1434838676526.07006835937500000000 ... nan
6 1434838676625.07006835937500000000 ... nan
7 1434838676726.07006835937500000000 ... nan
8 1434838676826.07006835937500000000 ... nan
9 1434838676924.07006835937500000000 ... nan
10 1434838676992.07006835937500000000 ... 51.19200097200000243447
答案 0 :(得分:0)
我认为您可以简单地使用pandas.Series.interpolate
因此,在这里,由于要用大于或小于它们的填充值的平均值来填充nan值,因此应如下所示:
df.Speed.interpolate()
这将返回一系列所有速度测量值以及nan值的插值。