As I understand it you want to impute the data using cross-sectional data rather than time series information.
There are actually quite a lot of imputation packages that can do this for you in R. (if you are using R)
You’d need equally spaced data. So 1 values per hour and if it is not present, then it needs to be NA. So ideally you have then multiple time series of qual length.
Then you merge these time series according to the time stamp / hour.
Afterwards you can apply an imputation package like e.g.
imputeR with basically one line of code. These packages will use the correlations between the different time series to estimate the missing values in these series.
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