Missing Values in Data
Yes there are so many approaches to handle missing data or missing values depending on the task and the property of the data itself. For example in time series you can think about forward filling or even backward filling, max, mean or median over a time lapse. There are also 'smarter' ways like training a model over the available data and try to predict the missing ones. The latest requires much data so can give efficient results. You can refer to these two links for more information.

How to Handle Missing Data with Python
Machine learning algorithms to handle missing data