我們正在嘗試刪除異常值，但出現(xiàn)了無限循環(huán)對(duì)于一個(gè)學(xué)校項(xiàng)目，我們（我和一個(gè)朋友）認(rèn)為創(chuàng)建一個(gè)基于數(shù)據(jù)科學(xué)的工具是個(gè)好主意。為此，我們開始清理數(shù)據(jù)庫（我不會(huì)在這里導(dǎo)入它，因?yàn)樗螅▁lsx 文件、csv 文件））。我們現(xiàn)在嘗試使用“duration_分鐘”列的“標(biāo)準(zhǔn)差*3 + 平均值”規(guī)則刪除異常值。這是我們用來計(jì)算標(biāo)準(zhǔn)差和平均值的代碼：def calculateSD(database, column):    column = database[[column]]    SD = column.std(axis=None, skipna=None, level=None, ddof=1, numeric_only=None)    return SDdef calculateMean(database, column):    column = database[[column]]    mean = column.mean()    return mean我們認(rèn)為要做到以下幾點(diǎn)：#Now we have to remove the outliers using the code from the SD.py and SDfunction.py filesminutes = trainsData['duration_minutes'].tolist() #takes the column duration_minutes and puts it in a listSD = int(calculateSD(trainsData, 'duration_minutes')) #calculates the SD of the columnmean = int(calculateMean(trainsData, 'duration_minutes'))SDhigh = mean+3*SD上面的代碼計(jì)算起始值。然后我們啟動(dòng)一個(gè) while 循環(huán)來刪除異常值。刪除異常值后，我們重新計(jì)算標(biāo)準(zhǔn)差、均值和 SDhigh。這是 while 循環(huán)：while np.any(i >= SDhigh for i in minutes): #used to be >=, it doesnt matter for the outcome    trainsData = trainsData[trainsData['duration_minutes'] < SDhigh] #used to be >=, this caused an infinite loop so I changed it to <=. Then to <    minutes = trainsData['duration_minutes'].tolist()    SD = int(calculateSD(trainsData, 'duration_minutes')) #calculates the SD of the column    mean = int(calculateMean(trainsData, 'duration_minutes'))    SDhigh = mean+3*SD    print(SDhigh) #to see how the values changed and to confirm it is an infinite loop輸出如下：611652428354322308300296296296296它繼續(xù)打印 296，經(jīng)過幾個(gè)小時(shí)的嘗試解決這個(gè)問題，我們得出的結(jié)論是我們沒有我們希望的那么聰明。