In the chart, you may have noticed outliers. These are very important to note when looking at prototypes. Outliers can represent power fluctuations within a machine, bad sensor placement, or a number of other issues. The following example shows a simple standard deviation calculation on our data. From here, we are able to see two values that fall outside three standard deviations from the mean:
from numpy import mean
from numpy import std
data_mean, data_std = mean(pdf['dt']), std(pdf['dt'])
cut_off = data_std * 3
lower, upper = data_mean - cut_off, data_mean + cut_off
outliers = [x for x in pdf['dt'] if x < lower or x > upper]
print('Identified outliers: %d' % len(outliers))
print(outliers)
