Filling no-data values while data mining

Question

I am working on predictive maintenance and get temperature data from assets. In few months or few days asset remains down and we do not get temperature value. In this scenario i cannot fill data with missing value techniques. Also cannot give some number because even 0 and -1 are valid values for temperature. How to deal with such data?

I am thinking of putting very big value for such columns which is not possible as temperature.

Answer 1

The value that you should put there is NA.

The data is missing, and must be treated as missing.

Even if you'd put an impossible value there (say, -10000 degrees, below absolute zero) this will cause much more havoc than properly encoding missing values as missing values (NA). There is no good reason to encore them as any other value, is there?