Missing values in Time Series in python

Question

I have a time series dataframe, the dataframe is quite big and contain some missing values in the 2 columns(\'Humidity\' and \'Pressure\'). I would like to impute this missing v

Answer 1

Looks like your data is by hour. How about just take the average of the hour before and the hour after? Or change the window size to 2, meaning the average of two hours before and after?

Imputing using other variables can be expensive and you should only consider those methods if the dummy methods do not work well (e.g. introducing too much noise).