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I have to calculate the consistency of racing car drivers during the whole season. My DataFrame consists of 10 columns (10 circuit names) and for each of those columns I have the standard deviation in lap time the driver posted in that circuit. In other words, how consistent the driver is from lap to lap. In races the driver did not finish the field is blank.

So far I have calculated their average season consistency by averaging all 10 columns. However, not finishing a race should affect a driver's consistency negatively and I do not know how to implement that. If I fill it with the average value of the finished races I am not really penalizing him for crashing.

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  • $\begingroup$ The missing data should not impact estimates of consistency. More data means more precise estimates, if a driver did not finish then that will manifest in a less precise estimate of consistency. $\endgroup$ – Demetri Pananos Apr 15 at 14:27
  • $\begingroup$ Yeah but crashing makes you less consistent. How do you inclue missing data in the consistency? $\endgroup$ – jatrp5 Apr 16 at 15:16

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