title: Missing values in Time Series in python
body: <p>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 values in a clever way, for example using the value of the nearest neighbor or the average of the previous and following timestamp.Is there an easy way to do it? I have tried with fancyimpute but the dataset contain around 180000 examples and give a memory error <a href="https://i.stack.imgur.com/WCdT4.png" rel="noreferrer"><img src="https://i.stack.imgur.com/WCdT4.png" alt="enter image description here"></a></p>