Missing values
Quite often we miss values for certain features. This could happen for various reasons. It can be inconvenient, expensive, or even impossible to always have a value. Maybe we were not able to measure a certain quantity in the past, because we didn't have the right equipment, or we just didn't know that the feature was relevant. However, we are stuck with missing values from the past. Sometimes it's easy to figure out that we miss values and we can discover this just by scanning the data, or counting the number of values we have for a feature and comparing to the number of values we expect based on the number of rows. Certain systems encode missing values with, for example, values such as 999999. This makes sense if the valid ...
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