Interpolating missing data in cumulative timeseries data
Answer taken from @Quang Hoang above wiht ffill()
I have a time-series dataframe with a cumulative data column. Data drops at night-time leaving me with NaN values, and picks up with first data read in the morning. 
I would like to interpolate the data so that all NaN values take on the value of the last known float/valid number. Is this readily possible with .interpolate()?