data_process.py

import pandas as pd

def mean(data):
    _sum = 0
    for value in data:
        _sum += value
    return _sum/len(data)

def devation(data):
    _mean = mean(data)
    total = 0
    for value in data:
        total += (value-_mean)**2
    return (total/len(data))**0.5

#string = "0 23 34 41 52 73 53 66 59 56 76 48 34 42 27 32 24 29 32 30 27 36 38 80 36 60 52 76 51 78 310 99 49 46 42 48 57 60 50 114 60 62 52 71 81 73 55 59 57 66 54 65 70 63 61 55 138 85 70 120 117 110 115 300 122 216 246 110 47 53 58 49 45 31 38 46 29 31 15 20 19 23 24 8 8"

#data = [int(i) for i in string.split(' ')]
#data2 = [0, 2.189938703094842, 2.414736402766418, 2.530439534435243, 2.68534961428265, 2.923012785691765, 2.6981678764080854, 2.8502698827717983, 2.771488002476036, 2.7355647997347607, 2.9525917237371897, 2.6321480259049848, 2.414736402766418, 2.5457298950218306, 2.2795070569547775, 2.378414230005442, 2.213363839400643, 2.320595787106084, 2.378414230005442, 2.340347319320716, 2.2795070569547775, 2.449489742783178, 2.4828237961983883, 2.990697562442441, 2.449489742783178, 2.783157683713741, 2.68534961428265, 2.9525917237371897, 2.6723451177837885, 2.9718278662008415, 4.19604776684668, 3.1543421455299043, 2.6457513110645907, 2.604290687140218, 2.5457298950218306, 2.6321480259049848, 2.7476962050544724, 2.783157683713741, 2.6591479484724942, 3.2675798769167543, 2.783157683713741, 2.806066263296683, 2.68534961428265, 2.9027831081870996, 3, 2.923012785691765, 2.7232698153315003, 2.771488002476036, 2.7476962050544724, 2.8502698827717983, 2.7108060108295344, 2.8394115144336776, 2.892507608519078, 2.8173132472612576, 2.794682392671241, 2.7232698153315003, 3.4274392955194304, 3.036370276710811, 2.892507608519078, 3.309750919646873, 3.288868167986058, 3.238531840464366, 3.2747221706220526, 4.161791450287818, 3.3234561855374687, 3.833658625477635, 3.9603518961524267, 3.238531840464366, 2.6183304986958853, 2.6981678764080854, 2.7596690210718946, 2.6457513110645907, 2.5900200641113513, 2.3596110617705666, 2.4828237961983883, 2.604290687140218, 2.320595787106084, 2.3596110617705666, 1.9679896712654306, 2.114742526881128, 2.087797629929844, 2.189938703094842, 2.213363839400643, 1.6817928305074292, 1.6817928305074292]

def smooth(data):
    new_data = [ i for i in data ]
    
    for i in range(0, len(data)):
        is_peak = False
        try: is_peak = (new_data[i-1]<new_data[i] and new_data[i]>new_data[i+1]) or (new_data[i-1]>new_data[i] and new_data[i]<new_data[i+1])
        except: pass
        if new_data[i] > mean(data)+devation(data)/2 or is_peak:
            try: new_data[i] = (new_data[i-1]+new_data[i+1])/2
            except: new_data[i] = mean(data)
        if new_data[i] < mean(data)-devation(data)/2 or is_peak:
            try: new_data[i] = (new_data[i-1]+new_data[i+1])/2
            except: new_data[i] = mean(data)
    return new_data

#data_processed = smooth(data)

#dataframe = pd.DataFrame({'original1':data,'original2':data2,'processed_once':data_processed,'processed_twice':smooth(data_processed),'processed_three_times':smooth(smooth(data_processed)),'processed_twelve_times':smooth(smooth(smooth(smooth(smooth(smooth(smooth(smooth(smooth(smooth(smooth(data_processed)))))))))))})

#dataframe.to_csv("video2.csv",sep=',')

#print ()

import csv

with open('video2.csv', newline='') as f:
    reader = csv.reader(f)
    data = list(reader)
data = [ float(i[1]) for i in data[1:]]
print(data)
#data = pd.read_csv('video2.csv')
#print(data)