One possible approach to this problem is to use an interpolation-based method to compute the missing data points. Interpolation is the process of estimating a value between two points on a curve or a line.

Here is a useful tutorial on statistical interpolation with several examples. This is another useful document with a slightly more advanced coverage of different interpolation models such as linear, polynomial and quadratic interpolation, cubic splines, methods based on divided differences and newton differences.

Libraries
Libraries available in our Machine Learning/Real Data challenges will be enabled for this contest and are listed here. Occasionally, a few functions or modules might not work within the constraints of our infrastructure. For instance, some modules try to run multiple threads (and fail). Please try importing the library and functions and cross checking if they work in our online editor in case you plan to develop a solution locally only to upload it and not have it work.


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