The Interpolation Experiment

After successfully merging the data files together, data interpolation had to be done. This meant that it was necessary to fill the missing values with values that were last obtained for a patient. This can be seen in the diagram below. This brought the data into a time series format. Model development was also doneContinue reading “The Interpolation Experiment”

The Merging Configuration

This week consisted of us generating Jupyter notebooks in order to efficiently merge and produce a combined data set with patient data. This involved us studying the best methods of joining tables and merging in pandas and by examining the data’s offset values. These offset values were all synced together in order to present timeContinue reading “The Merging Configuration”

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