I have a dataset of 5,000 records and each of those records consists of a series of continuous measurements collected over a decade at various times. Each of the measurements was originally entered by manually and, as might be expected, there are a number of errors that need to be corrected.
Typically the incorrect data change by >50% from point to point, while data that is correct changes at most by 10% at any one time. If I visualize the data individually, these are very obvious in an X/Y plot with time on the X-axis.
It's not feasible to graph each of these individually, and I'm trying to figure out if there's a faster way to automate and flag the data that are obviously in error and need to be corrected/removed.
Does anyone have any experience with a problem like this?