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I have been trying some stuff out with PyPOTS lately and I was wondering if my data has to fill some type of criteria before I can use it as input, or PyPOTS can work with any kind of data? For example what if I have a signal which is always rising in the time segment that I used as input?
I have data which can last up to two hours and I have measurements each second - so what I did is I divided the data in strict segments of 300, or 600 or more seconds. And since that is short amount of time, the temperature can always rise or fall or stay the same. So would this signal be useful for data imputation, or would it just confuse the calculations? And keep in mind the temperature maybe influences slightly other signal and their measurements.
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Hi!
I have been trying some stuff out with PyPOTS lately and I was wondering if my data has to fill some type of criteria before I can use it as input, or PyPOTS can work with any kind of data? For example what if I have a signal which is always rising in the time segment that I used as input?
I have data which can last up to two hours and I have measurements each second - so what I did is I divided the data in strict segments of 300, or 600 or more seconds. And since that is short amount of time, the temperature can always rise or fall or stay the same. So would this signal be useful for data imputation, or would it just confuse the calculations? And keep in mind the temperature maybe influences slightly other signal and their measurements.
Thank you very much for your support!
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