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This package is awesome!!! Is there an ability to apply an identifying factor on the cycles in the data set? I didn't see anything digging through what you have.
Below illustrates what I am looking for and how I was able to rig together a solution for my application with time series data. This is a small sample of my dataset df.txt which represents about 3 days of a dataset that covers a few years.
An example of the data looks like:
Time
Value
2018-08-10 06:00:00
760.6917
2018-08-10 06:01:00
761.0291
2018-08-10 06:02:00
760.9166
2018-08-10 06:03:00
761.2542
2018-08-10 06:04:00
761.1416
2018-08-10 06:05:00
762.5291
I used the indices from the FindPeaks() function and converted those to matching timestamps from my dataset and then used row_number() to apply a quick and dirty identifying factor.
This package is awesome!!! Is there an ability to apply an identifying factor on the cycles in the data set? I didn't see anything digging through what you have.
Below illustrates what I am looking for and how I was able to rig together a solution for my application with time series data. This is a small sample of my dataset df.txt which represents about 3 days of a dataset that covers a few years.
An example of the data looks like:
I used the indices from the
FindPeaks()
function and converted those to matching timestamps from my dataset and then usedrow_number()
to apply a quick and dirty identifying factor.The output looks like this with the new ID variable.
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