计算两行之间的时差 [英] Calculating time difference between two rows

问题描述

我正在尝试使用shift()计算两行之间的时间差，但出现意外错误.我可能缺少明显的东西

I'm trying to calculate the time difference between two rows using shift(), but I get an unexpected error. I may be missing something obvious

df['Delta'] = (df.index - df.index.shift(1))

此语句产生一个ValueError: Cannot shift with no offset.我想念什么?

This statement produces a ValueError: Cannot shift with no offset. What am I missing?

推荐答案

两件事:

• 如果您有DatetimeIndex，则shift会在一段时间内移动数据.如果索引没有频率，则必须使用freq关键字将其提供给shift方法(例如freq='s'将数据移动一秒钟)
• 您不能像这样减去两个索引对象，因为这会给您带来差异设置操作:

• If you have a DatetimeIndex, the shift shifts your data with a period of time. If your index has no frequency, you have to provide that to the shift method with the freq keyword (eg freq='s' to shift the data one second)
• You cannot substract two index objects like that, as this gives you a difference set operation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#set-operations-on-index-objects

如果只希望索引中两个连续值之间的差，则可以使用diff方法(对于Series，比移位和减法容易一些):

If you just want the difference between two consecutive values in the index, you can use the diff method (of a Series, a bit easier than shift and substract):

df['index_col'] = df.index
df['Delta'] = df['index_col'].diff()

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