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I am analyzing an aws log file with http request logs, and I need to predict the expected load (number of requests) in the next minute. However, I see there are spans of times that doesn't have any logs. In this kind of case, do I assume that loads during those times were just 0, or do I need to do some sort of interpolation?

time                     load
2018-11-07 09:45:00      40
2018-11-07 09:46:00      45
2018-11-07 09:47:00      34
2018-11-07 09:48:00      56

and then no logs for the next 2 hours and then again:

time                     load
2018-11-07 11:50:00      54
2018-11-07 11:51:00      34
2018-11-07 11:52:00      23
2018-11-07 11:53:00      21

Let's say when I read this file to a pandas dataframe for my prediction model, do I fill in all the minutes for those 2 hours with 0? Or are there better intelligent ways of dealing with this sort of situations?

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