devicemxl

RawData['Type'] = 0
for i in range(len(RawData['χ2'])):
    if RawData['χ2'][i] > x2q: RawData['Type'][i] = 'Noise'
    else: RawData['Type'][i] = 'Data'

devicemxl

σ = variance(RawData['MeasurementAccuracy'])# the population variance σ²
x2 = []
for i in range(n):
        if i>0:
                σS = variance([RawData['MeasurementAccuracy'][i],RawData['MeasurementAccuracy'][i-1]])# Because the sample is this and the past data
                x2t = ( (n-1) * σS ) / σ
                x2.append(x2t)
        else: x2.append(0)

RawData['x2'] = x2

devicemxl

μ = RawData['Customers'].median()
n = len(RawData['Customers'])

MeasurementAccuracy = []
for i in range(n):
    MAtemp = (RawData['Customers'][i] / μ)
    MeasurementAccuracy.append(MAtemp)

RawData['MeasurementAccuracy'] = MeasurementAccuracy